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Henry B, Merz M, Hoang H, Abdulkarim G, Wosik J, Schoettker P. Cuffless Blood Pressure in clinical practice: challenges, opportunities and current limits. Blood Press 2024; 33:2304190. [PMID: 38245864 DOI: 10.1080/08037051.2024.2304190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/07/2024] [Indexed: 01/22/2024]
Abstract
Background: Cuffless blood pressure measurement technologies have attracted significant attention for their potential to transform cardiovascular monitoring.Methods: This updated narrative review thoroughly examines the challenges, opportunities, and limitations associated with the implementation of cuffless blood pressure monitoring systems.Results: Diverse technologies, including photoplethysmography, tonometry, and ECG analysis, enable cuffless blood pressure measurement and are integrated into devices like smartphones and smartwatches. Signal processing emerges as a critical aspect, dictating the accuracy and reliability of readings. Despite its potential, the integration of cuffless technologies into clinical practice faces obstacles, including the need to address concerns related to accuracy, calibration, and standardization across diverse devices and patient populations. The development of robust algorithms to mitigate artifacts and environmental disturbances is essential for extracting clear physiological signals. Based on extensive research, this review emphasizes the necessity for standardized protocols, validation studies, and regulatory frameworks to ensure the reliability and safety of cuffless blood pressure monitoring devices and their implementation in mainstream medical practice. Interdisciplinary collaborations between engineers, clinicians, and regulatory bodies are crucial to address technical, clinical, and regulatory complexities during implementation. In conclusion, while cuffless blood pressure monitoring holds immense potential to transform cardiovascular care. The resolution of existing challenges and the establishment of rigorous standards are imperative for its seamless incorporation into routine clinical practice.Conclusion: The emergence of these new technologies shifts the paradigm of cardiovascular health management, presenting a new possibility for non-invasive continuous and dynamic monitoring. The concept of cuffless blood pressure measurement is viable and more finely tuned devices are expected to enter the market, which could redefine our understanding of blood pressure and hypertension.
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Affiliation(s)
- Benoit Henry
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Maxime Merz
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Harry Hoang
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ghaith Abdulkarim
- Neuro-Informatics Laboratory, Mayo Clinic College of Medicine and Science, Rochester, MN, USA
- Department of Neurological Surgery, Mayo Clinic, Rochester, MN, USA
| | - Jedrek Wosik
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Patrick Schoettker
- Service of Anesthesiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Triantafyllidis A, Kondylakis H, Katehakis D, Kouroubali A, Alexiadis A, Segkouli S, Votis K, Tzovaras D. Smartwatch interventions in healthcare: A systematic review of the literature. Int J Med Inform 2024; 190:105560. [PMID: 39033723 DOI: 10.1016/j.ijmedinf.2024.105560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 06/25/2024] [Accepted: 07/16/2024] [Indexed: 07/23/2024]
Abstract
OBJECTIVE The use of smartwatches has attracted considerable interest in developing smart digital health interventions and improving health and well-being during the past few years. This work presents a systematic review of the literature on smartwatch interventions in healthcare. The main characteristics and individual health-related outcomes of smartwatch interventions within research studies are illustrated, in order to acquire evidence of their benefit and value in patient care. METHODS A literature search in the bibliographic databases of PubMed and Scopus was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, in order to identify research studies incorporating smartwatch interventions. The studies were grouped according to the intervention's target disease, main smartwatch features, study design, target age and number of participants, follow-up duration, and outcome measures. RESULTS The literature search identified 13 interventions incorporating smartwatches within research studies with people of middle and older age. The interventions targeted different conditions: cardiovascular diseases, diabetes, depression, stress and anxiety, metastatic gastrointestinal cancer and breast cancer, knee arthroplasty, chronic stroke, and allergic rhinitis. The majority of the studies (76%) were randomized controlled trials. The most used smartwatch was the Apple Watch utilized in 4 interventions (31%). Positive outcomes for smartwatch interventions concerned foot ulcer recurrence, severity of symptoms of depression, utilization of healthcare resources, lifestyle changes, functional assessment and shoulder range of motion, medication adherence, unplanned hospital readmissions, atrial fibrillation diagnosis, adherence to self-monitoring, and goal attainment for emotion regulation. Challenges in using smartwatches included frequency of charging, availability of Internet and synchronization with a mobile app, the burden of using a smartphone in addition to a patient's regular phone, and data quality. CONCLUSION The results of this review indicate the potential of smartwatches to bring positive health-related outcomes for patients. Considering the low number of studies identified in this review along with their moderate quality, we implore the research community to carry out additional studies in intervention settings to show the utility of smartwatches in clinical contexts.
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Affiliation(s)
- Andreas Triantafyllidis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece.
| | - Haridimos Kondylakis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Dimitrios Katehakis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Angelina Kouroubali
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Anastasios Alexiadis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Sofia Segkouli
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Konstantinos Votis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Dimitrios Tzovaras
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
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Singh B, Chastin S, Miatke A, Curtis R, Dumuid D, Brinsley J, Ferguson T, Szeto K, Simpson C, Eglitis E, Willems I, Maher C. Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth 2024; 12:e56972. [PMID: 39213525 DOI: 10.2196/56972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/03/2024] [Accepted: 06/26/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Wearable activity trackers, including fitness bands and smartwatches, offer the potential for disease detection by monitoring physiological parameters. However, their accuracy as specific disease diagnostic tools remains uncertain. OBJECTIVE This systematic review and meta-analysis aims to evaluate whether wearable activity trackers can be used to detect disease and medical events. METHODS Ten electronic databases were searched for studies published from inception to April 1, 2023. Studies were eligible if they used a wearable activity tracker to diagnose or detect a medical condition or event (eg, falls) in free-living conditions in adults. Meta-analyses were performed to assess the overall area under the curve (%), accuracy (%), sensitivity (%), specificity (%), and positive predictive value (%). Subgroup analyses were performed to assess device type (Fitbit, Oura ring, and mixed). The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Diagnostic Test Accuracy Studies. RESULTS A total of 28 studies were included, involving a total of 1,226,801 participants (age range 28.6-78.3). In total, 16 (57%) studies used wearables for diagnosis of COVID-19, 5 (18%) studies for atrial fibrillation, 3 (11%) studies for arrhythmia or abnormal pulse, 3 (11%) studies for falls, and 1 (4%) study for viral symptoms. The devices used were Fitbit (n=6), Apple watch (n=6), Oura ring (n=3), a combination of devices (n=7), Empatica E4 (n=1), Dynaport MoveMonitor (n=2), Samsung Galaxy Watch (n=1), and other or not specified (n=2). For COVID-19 detection, meta-analyses showed a pooled area under the curve of 80.2% (95% CI 71.0%-89.3%), an accuracy of 87.5% (95% CI 81.6%-93.5%), a sensitivity of 79.5% (95% CI 67.7%-91.3%), and specificity of 76.8% (95% CI 69.4%-84.1%). For atrial fibrillation detection, pooled positive predictive value was 87.4% (95% CI 75.7%-99.1%), sensitivity was 94.2% (95% CI 88.7%-99.7%), and specificity was 95.3% (95% CI 91.8%-98.8%). For fall detection, pooled sensitivity was 81.9% (95% CI 75.1%-88.1%) and specificity was 62.5% (95% CI 14.4%-100%). CONCLUSIONS Wearable activity trackers show promise in disease detection, with notable accuracy in identifying atrial fibrillation and COVID-19. While these findings are encouraging, further research and improvements are required to enhance their diagnostic precision and applicability. TRIAL REGISTRATION Prospero CRD42023407867; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=407867.
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Affiliation(s)
- Ben Singh
- Allied Health & Human Performance, University of South Australia, Adelaide, Australia
| | - Sebastien Chastin
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Aaron Miatke
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Rachel Curtis
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Dorothea Dumuid
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Jacinta Brinsley
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Ty Ferguson
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Kimberley Szeto
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Catherine Simpson
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Emily Eglitis
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Iris Willems
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
| | - Carol Maher
- Department of Rehabilitation Sciences and Physiotherapy, Ghent University, Ghent, Belgium
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Denysyuk HV, Pires IM, Garcia NM. A roadmap for empowering cardiovascular disease patients: a 5P-Medicine approach and technological integration. PeerJ 2024; 12:e17895. [PMID: 39224824 PMCID: PMC11368085 DOI: 10.7717/peerj.17895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 07/19/2024] [Indexed: 09/04/2024] Open
Abstract
This article explores the multifaceted concept of cardiovascular disease (CVD) patients' empowerment, emphasizing a shift from compliance-oriented models to active patient participation. In recognizing that cardiovascular disease is a paramount global health challenge, this study illuminates the pressing need for empowering patients, underscoring their role as active participants in their healthcare journey. Grounded in 5P-Medicine principles-Predictive, Preventive, Participatory, Personalized, and Precision Medicine-the importance of empowering CVD patients through analytics, prevention, participatory decision making, and personalized treatments is highlighted. Incorporating a comprehensive overview of patient empowerment strategies, including self-management, health literacy, patient involvement, and shared decision making, the article advocates for tailored approaches aligned with individual needs, cultural contexts, and healthcare systems. Technological integration is examined to enhance patient engagement and personalized healthcare experiences. The critical role of patient-centered design in integrating digital tools for CVD management is emphasized, ensuring successful adoption and meaningful impact on healthcare outcomes. The conclusion proposes vital research questions addressing challenges and opportunities in CVD patient empowerment. These questions stress the importance of medical community research, understanding user expectations, evaluating existing technologies, defining ideal empowerment scenarios, and conducting a literature review for informed advancements. This article lays the foundation for future research, contributing to ongoing patient-centered healthcare evolution, especially in empowering individuals with a 5P-Medicine approach to cardiovascular diseases.
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Affiliation(s)
- Hanna V. Denysyuk
- Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã, Portugal
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, Águeda, Portugal
| | - Nuno M. Garcia
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal
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5
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Jia B, Chen J, Luan Y, Wang H, Wei Y, Hu Y. Artificial intelligence and atrial fibrillation: A bibliometric analysis from 2013 to 2023. Heliyon 2024; 10:e35067. [PMID: 39157317 PMCID: PMC11328043 DOI: 10.1016/j.heliyon.2024.e35067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 06/12/2024] [Accepted: 07/22/2024] [Indexed: 08/20/2024] Open
Abstract
Background In the study of atrial fibrillation (AF), a prevalent cardiac arrhythmia, the utilization of artificial intelligence (AI) in diagnostic and therapeutic strategies holds the potential to address existing limitations. This research employs bibliometrics to objectively investigate research hotspots, development trends, and existing issues in the application of AI within the AF field, aiming to provide targeted recommendations for relevant researchers. Methods Relevant publications on the application of AI in AF field were retrieved from the Web of Science Core Collection (WoSCC) database from 2013 to 2023. The bibliometric analysis was conducted by the R (4.2.2) "bibliometrix" package and VOSviewer(1.6.19). Results Analysis of 912 publications reveals that the field of AI in AF is currently experiencing rapid development. The United States, China, and the United Kingdom have made outstanding contributions to this field. Acharya UR is a notable contributor and pioneer in the area. The following topics have been elucidated: AI's application in managing the risk of AF complications is a hot mature topic; AI-electrocardiograph for AF diagnosis and AI-assisted catheter ablation surgery are the emerging and booming topics; smart wearables for real-time AF monitoring and AI for individualized AF medication are niche and well-developed topics. Conclusion This study offers comprehensive analysis of the origin, current status, and future trends of AI applications in AF, aiming to advance the development of the field.
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Affiliation(s)
- Bochao Jia
- Department of Cardiovascular Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
- Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jiafan Chen
- Department of Cardiovascular Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
| | - Yujie Luan
- Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Huan Wang
- Department of Cardiovascular Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
| | - Yi Wei
- Department of Cardiovascular Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
| | - Yuanhui Hu
- Department of Cardiovascular Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, 100053, China
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Chinni BK, Manlhiot C. Emerging Analytical Approaches for Personalized Medicine Using Machine Learning In Pediatric and Congenital Heart Disease. Can J Cardiol 2024:S0828-282X(24)00585-3. [PMID: 39097187 DOI: 10.1016/j.cjca.2024.07.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/25/2024] [Accepted: 07/26/2024] [Indexed: 08/05/2024] Open
Abstract
Precision and personalized medicine, the process by which patient management is tailored to individual circumstances, are now terms that are familiar to cardiologists, despite it still being an emerging field. Although precision medicine relies most often on the underlying biology and pathophysiology of a patient's condition, personalized medicine relies on digital biomarkers generated through algorithms. Given the complexity of the underlying data, these digital biomarkers are most often generated through machine-learning algorithms. There are a number of analytic considerations regarding the creation of digital biomarkers that are discussed in this review, including data preprocessing, time dependency and gating, dimensionality reduction, and novel methods, both in the realm of supervised and unsupervised machine learning. Some of these considerations, such as sample size requirements and measurements of model performance, are particularly challenging in small and heterogeneous populations with rare outcomes such as children with congenital heart disease. Finally, we review analytic considerations for the deployment of digital biomarkers in clinical settings, including the emerging field of clinical artificial intelligence (AI) operations, computational needs for deployment, efforts to increase the explainability of AI, algorithmic drift, and the needs for distributed surveillance and federated learning. We conclude this review by discussing a recent simulation study that shows that, despite these analytic challenges and complications, the use of digital biomarkers in managing clinical care might have substantial benefits regarding individual patient outcomes.
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Affiliation(s)
- Bhargava K Chinni
- The Blalock-Taussig-Thomas Pediatric and Congenital Heart Center, Department of Pediatrics, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Cedric Manlhiot
- The Blalock-Taussig-Thomas Pediatric and Congenital Heart Center, Department of Pediatrics, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Research Institute, SickKids Hospital, Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada.
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Średnicka-Tober D, Góralska-Walczak R, Kopczyńska K, Kazimierczak R, Oczkowski M, Strassner C, Elsner F, Matthiessen LE, Bruun TSK, Philippi Rosane B, Zanasi C, Van Vliet M, Dragsted LO, Husain S, Damsgaard CT, Lairon D, Kesse-Guyot E, Baudry J, Leclercq C, Stefanovic L, Welch A, Bügel SG. Identifying Future Study Designs and Indicators for Somatic Health Associated with Diets of Cohorts Living in Eco-Regions: Findings from the INSUM Expert Workshop. Nutrients 2024; 16:2528. [PMID: 39125406 PMCID: PMC11314491 DOI: 10.3390/nu16152528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Revised: 07/26/2024] [Accepted: 07/30/2024] [Indexed: 08/12/2024] Open
Abstract
Diets, but also overall food environments, comprise a variety of significant factors with direct and indirect impacts on human health. Eco-Regions are geographical areas with a territorial approach to rural development, utilizing organic food and farming practices, and principles and promoting sustainable communities and food systems. However, so far, little attention has been given to quantifying aspects of the health of citizens living in these sustainable transition territories. The project "Indicators for Assessment of Health Effects of Consumption of Sustainable, Organic School Meals in Eco-Regions" (INSUM) aims to identify and discuss research approaches and indicators that could be applied to effectively measure the somatic, mental, and social health dimensions of citizens in Eco-Regions, linked to the intake of organic foods in their diets. In this paper, we focus on the somatic (physical) health dimension. A two-day workshop was held to discuss suitable methodology with an interdisciplinary, international group of experts. The results showed the limitations of commonly used tools for measuring dietary intake (e.g., relying on the memory of participants), and nutritional biomarkers (e.g., variations in correlations with specific intakes) for research understanding dietary intake and the health effects of diets. To investigate the complexity of this issue, the most suitable approach seems to be the combination of traditional markers of physical and mental health alongside emerging indicators such as the microbiome, nutrigenomics, metabolomics, or inflammatory biomarkers. Using new, digital, non-invasive, and wearable technologies to monitor indicators could complement future research. We conclude that future studies should adopt systemic, multidisciplinary approaches by combining not only indicators of somatic and mental health and social wellbeing (MHSW) but also considering the potential benefits of organic diets for health as well as aspects of sustainability connected to food environments.
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Affiliation(s)
- Dominika Średnicka-Tober
- Department of Functional and Organic Food, Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, 02-776 Warsaw, Poland; (R.G.-W.); (K.K.); (R.K.)
| | - Rita Góralska-Walczak
- Department of Functional and Organic Food, Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, 02-776 Warsaw, Poland; (R.G.-W.); (K.K.); (R.K.)
| | - Klaudia Kopczyńska
- Department of Functional and Organic Food, Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, 02-776 Warsaw, Poland; (R.G.-W.); (K.K.); (R.K.)
| | - Renata Kazimierczak
- Department of Functional and Organic Food, Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, 02-776 Warsaw, Poland; (R.G.-W.); (K.K.); (R.K.)
| | - Michał Oczkowski
- Department of Dietetics, Institute of Human Nutrition Sciences, Warsaw University of Life Sciences, 02-776 Warsaw, Poland;
| | - Carola Strassner
- Department of Food—Nutrition—Facilities, FH Münster University of Applied Sciences, 48149 Münster, Germany; (C.S.); (F.E.); (S.H.)
| | - Friederike Elsner
- Department of Food—Nutrition—Facilities, FH Münster University of Applied Sciences, 48149 Münster, Germany; (C.S.); (F.E.); (S.H.)
| | - Lea Ellen Matthiessen
- Department of Nutrition, Exercise and Sports, University of Copenhagen, 1958 Frederiksberg, Denmark; (L.E.M.); (B.P.R.); (L.O.D.); (C.T.D.); (S.G.B.)
| | - Thea Steenbuch Krabbe Bruun
- Department of Nutrition, Exercise and Sports, University of Copenhagen, 1958 Frederiksberg, Denmark; (L.E.M.); (B.P.R.); (L.O.D.); (C.T.D.); (S.G.B.)
| | - Beatriz Philippi Rosane
- Department of Nutrition, Exercise and Sports, University of Copenhagen, 1958 Frederiksberg, Denmark; (L.E.M.); (B.P.R.); (L.O.D.); (C.T.D.); (S.G.B.)
| | - Cesare Zanasi
- Department of Agricultural and Food Sciences, University of Bologna, 40127 Bologna, Italy;
| | - Marja Van Vliet
- Stichting Institute for Positive Health, 3521 AL Utrecht, The Netherlands;
| | - Lars Ove Dragsted
- Department of Nutrition, Exercise and Sports, University of Copenhagen, 1958 Frederiksberg, Denmark; (L.E.M.); (B.P.R.); (L.O.D.); (C.T.D.); (S.G.B.)
| | - Sarah Husain
- Department of Food—Nutrition—Facilities, FH Münster University of Applied Sciences, 48149 Münster, Germany; (C.S.); (F.E.); (S.H.)
| | - Camilla Trab Damsgaard
- Department of Nutrition, Exercise and Sports, University of Copenhagen, 1958 Frederiksberg, Denmark; (L.E.M.); (B.P.R.); (L.O.D.); (C.T.D.); (S.G.B.)
| | - Denis Lairon
- Inserm, INRAE, C2VN, Aix Marseille Université, 13331 Marseille, France;
| | - Emmanuelle Kesse-Guyot
- Inserm, INRAE, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center—Paris Cité University (CRESS), Sorbonne Paris Nord University, 93000 Bobigny, France; (E.K.-G.); (J.B.)
| | - Julia Baudry
- Inserm, INRAE, Cnam, Nutritional Epidemiology Research Team (EREN), Epidemiology and Statistics Research Center—Paris Cité University (CRESS), Sorbonne Paris Nord University, 93000 Bobigny, France; (E.K.-G.); (J.B.)
| | - Catherine Leclercq
- Food and Nutrition Center, Council for Research in Agriculture and the Analysis of the Agriculture Economy (CREA), 00178 Rome, Italy
| | - Lilliana Stefanovic
- Section of Organic Food Quality, Faculty of Organic Agriculture Sciences, University of Kassel, 37213 Witzenhausen, Germany;
| | - Ailsa Welch
- Norwich Medical School, Centre for Population Health Research, Faculty of Health, University of East Anglia, Norwich, Norfolk NR4 7TJ, UK;
| | - Susanne Gjedsted Bügel
- Department of Nutrition, Exercise and Sports, University of Copenhagen, 1958 Frederiksberg, Denmark; (L.E.M.); (B.P.R.); (L.O.D.); (C.T.D.); (S.G.B.)
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8
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Albulushi A, Al Kindi DI, Moawwad N, Kamel AM, Khan A, Moustafa MA, Al Kalbani A. Digital health technologies in enhancing patient and caregiver engagement in heart failure management: Opportunities and challenges. Int J Cardiol 2024; 408:132116. [PMID: 38703898 DOI: 10.1016/j.ijcard.2024.132116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 04/04/2024] [Accepted: 04/29/2024] [Indexed: 05/06/2024]
Abstract
The management of heart failure has undergone significant evolution, advancing from the initial utilization of digitalis and diuretics to the contemporary practice of personalized medicine and sophisticated device therapy. Despite these advancements, the persistent challenge of high hospitalization and readmission rates underscores an urgent need for innovative solutions. This manuscript explores how the integration of digital health technologies into interventional cardiology marks a paradigm shift in the management of heart failure. These technologies are no longer mere adjuncts but have become foundational to a modern approach, providing tools for continuous monitoring, patient education, and improved outcomes post-intervention. Through an examination of current trends, this perspective article highlights the transformative impact of wearable technologies, telehealth platforms, and advanced analytical tools in reshaping patient engagement and enabling proactive care strategies. Case studies illustrate the practical advantages, including enhanced medication adherence, early detection of heart failure signs, and a reduction in healthcare facility burdens. Central to this new digital health landscape is the Information Technology Management (ITM) system, a framework poised to revolutionize patient and caregiver engagement and pave the way for the future of interventional cardiology. This manuscript delineates the ITM system's innovative architecture and its consequential role in refining current and prospective cardiological interventions.
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Affiliation(s)
- Arif Albulushi
- Division of Adult Cardiology, National Heart Center, The Royal Hospital, Muscat, Oman.
| | - Dawoud I Al Kindi
- Division of Adult Cardiology, National Heart Center, The Royal Hospital, Muscat, Oman
| | - Nader Moawwad
- Division of Adult Cardiology, National Heart Center, The Royal Hospital, Muscat, Oman
| | - Adel M Kamel
- Division of Adult Cardiology, National Heart Center, The Royal Hospital, Muscat, Oman
| | - Asif Khan
- Division of Adult Cardiology, National Heart Center, The Royal Hospital, Muscat, Oman
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9
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Van Der Donckt J, Vandenbussche N, Van Der Donckt J, Chen S, Stojchevska M, De Brouwer M, Steenwinckel B, Paemeleire K, Ongenae F, Van Hoecke S. Mitigating data quality challenges in ambulatory wrist-worn wearable monitoring through analytical and practical approaches. Sci Rep 2024; 14:17545. [PMID: 39079945 PMCID: PMC11289092 DOI: 10.1038/s41598-024-67767-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 07/15/2024] [Indexed: 08/02/2024] Open
Abstract
Chronic disease management and follow-up are vital for realizing sustained patient well-being and optimal health outcomes. Recent advancements in wearable technologies, particularly wrist-worn devices, offer promising solutions for longitudinal patient monitoring, replacing subjective, intermittent self-reporting with objective, continuous monitoring. However, collecting and analyzing data from wearables presents several challenges, such as data entry errors, non-wear periods, missing data, and wearable artifacts. In this work, we explore these data analysis challenges using two real-world datasets (mBrain21 and ETRI lifelog2020). We introduce practical countermeasures, including participant compliance visualizations, interaction-triggered questionnaires to assess personal bias, and an optimized pipeline for detecting non-wear periods. Additionally, we propose a visualization-oriented approach to validate processing pipelines using scalable tools such as tsflex and Plotly-Resampler. Lastly, we present a bootstrapping methodology to evaluate the variability of wearable-derived features in the presence of partially missing data segments. Prioritizing transparency and reproducibility, we provide open access to our detailed code examples, facilitating adaptation in future wearable research. In conclusion, our contributions provide actionable approaches for improving wearable data collection and analysis.
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Affiliation(s)
- Jonas Van Der Donckt
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium.
| | - Nicolas Vandenbussche
- Department of Neurology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Basic and Applied Medical Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | | | - Stephanie Chen
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium
| | - Marija Stojchevska
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium
| | - Mathias De Brouwer
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium
| | - Bram Steenwinckel
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium
| | - Koen Paemeleire
- Department of Neurology, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, Belgium
- Department of Basic and Applied Medical Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Femke Ongenae
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium
| | - Sofie Van Hoecke
- IDLab, Ghent University - Imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium
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10
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Pérez-Guerrero EJ, Mehrotra I, Jain SS, Perez MV. Introduction to wearable technology in arrhythmia management. Heart Rhythm 2024:S1547-5271(24)03074-1. [PMID: 39053750 DOI: 10.1016/j.hrthm.2024.07.098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 07/16/2024] [Accepted: 07/18/2024] [Indexed: 07/27/2024]
Affiliation(s)
| | - Isha Mehrotra
- Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Sneha S Jain
- Cardiovascular Division, Department of Medicine, Stanford University School of Medicine, Stanford, California; Cardiovascular Institute, Stanford University, Stanford, California
| | - Marco V Perez
- Cardiovascular Division, Department of Medicine, Stanford University School of Medicine, Stanford, California; Cardiovascular Institute, Stanford University, Stanford, California
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11
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Papalamprakopoulou Z, Stavropoulos D, Moustakidis S, Avgerinos D, Efremidis M, Kampaktsis PN. Artificial intelligence-enabled atrial fibrillation detection using smartwatches: current status and future perspectives. Front Cardiovasc Med 2024; 11:1432876. [PMID: 39077110 PMCID: PMC11284169 DOI: 10.3389/fcvm.2024.1432876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Accepted: 07/02/2024] [Indexed: 07/31/2024] Open
Abstract
Atrial fibrillation (AF) significantly increases the risk of stroke and heart failure, but is frequently asymptomatic and intermittent; therefore, its timely diagnosis poses challenges. Early detection in selected patients may aid in stroke prevention and mitigate structural heart complications through prompt intervention. Smartwatches, coupled with powerful artificial intelligence (AI)-enabled algorithms, offer a promising tool for early detection due to their widespread use, easiness of use, and potential cost-effectiveness. Commercially available smartwatches have gained clearance from the FDA to detect AF and are becoming increasingly popular. Despite their promise, the evolving landscape of AI-enabled smartwatch-based AF detection raises questions about the clinical value of this technology. Following the ongoing digital transformation of healthcare, clinicians should familiarize themselves with how AI-enabled smartwatches function in AF detection and navigate their role in clinical settings to deliver optimal patient care. In this review, we provide a concise overview of the characteristics of AI-enabled smartwatch algorithms, their diagnostic performance, clinical value, limitations, and discuss future perspectives in AF diagnosis.
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Affiliation(s)
- Zoi Papalamprakopoulou
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, United States
| | - Dimitrios Stavropoulos
- Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| | | | | | | | - Polydoros N. Kampaktsis
- Department of Medicine, Aristotle University of Thessaloniki Medical School, Thessaloniki, Greece
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12
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Zhang K, Huang Q, Wang Q, Li C, Zheng Q, Li Z, Xu D, Xie C, Zhang M, Lin R. Telemedicine in Improving Glycemic Control Among Children and Adolescents With Type 1 Diabetes Mellitus: Systematic Review and Meta-Analysis. J Med Internet Res 2024; 26:e51538. [PMID: 38981114 PMCID: PMC11267117 DOI: 10.2196/51538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 02/28/2024] [Accepted: 05/21/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Type 1 diabetes mellitus (T1DM) is the most common chronic autoimmune disease among children and adolescents. Telemedicine has been widely used in the field of chronic disease management and can benefit patients with T1DM. However, existing studies lack high-level evidence related to the effectiveness of telemedicine for glycemic control in children and adolescents with T1DM. OBJECTIVE This study aims to systematically review the evidence on the effectiveness of telemedicine interventions compared with usual care on glycemic control among children and adolescents with T1DM. METHODS In this systematic review and meta-analysis, we searched PubMed, Cochrane Library, Embase, Web of Science (all databases), and CINAHL Complete from database inception to May 2023. We included randomized controlled trials (RCTs) that evaluated the effectiveness of a telemedicine intervention on glycemic control in children and adolescents with T1DM. In total, 2 independent reviewers performed the study selection and data extraction. Study quality was assessed using the Cochrane Risk of Bias 2 tool. Our primary outcome was glycated hemoglobin (HbA1c) levels. Secondary outcomes were quality of life, self-monitoring of blood glucose, the incidence of hypoglycemia, and cost-effectiveness. A random-effects model was used for this meta-analysis. RESULTS Overall, 20 RCTs (1704 participants from 12 countries) were included in the meta-analysis. Only 5% (1/20) of the studies were at high risk of bias. Compared to usual care, telemedicine was found to reduce HbA1c levels by 0.22 (95% CI -0.33 to -0.10; P<.001; I2=35%). There was an improvement in self-monitoring of blood glucose (mean difference [MD] 0.54, 95% CI -0.72 to 1.80; P=.40; I2=67.8%) and the incidence of hypoglycemia (MD -0.15, 95% CI -0.57 to 0.27; P=.49; I2=70.7%), although this was not statistically significant. Moreover, telemedicine had no convincing effect on the Diabetes Quality of Life for Youth score (impact of diabetes: P=.59; worries about diabetes: P=.71; satisfaction with diabetes: P=.68), but there was a statistically significant improvement in non-youth-specific quality of life (MD -0.24, 95% CI -0.45 to -0.02; P=.04; I2=0%). Subgroup analyses revealed that the effect of telemedicine on HbA1c levels appeared to be greater in studies involving children (MD -0.41, 95% CI -0.62 to -0.20; P<.001), studies that lasted <6 months (MD -0.32, 95% CI -0.48 to -0.17; P<.001), studies where providers used smartphone apps to communicate with patients (MD -0.37, 95% CI -0.53 to -0.21; P<.001), and studies with medication dose adjustment (MD -0.25, 95% CI -0.37 to -0.12; P<.001). CONCLUSIONS Telemedicine can reduce HbA1c levels and improve quality of life in children and adolescents with T1DM. Telemedicine should be regarded as a useful supplement to usual care to control HbA1c levels and a potentially cost-effective mode. Meanwhile, researchers should develop higher-quality RCTs using large samples that focus on hard clinical outcomes, cost-effectiveness, and quality of life.
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Affiliation(s)
- Kun Zhang
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Qiyuan Huang
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Qiaosong Wang
- School of Nursing, Fujian Medical University, Fuzhou, China
- Department of Nursing, The First Affiliated Hospital of Fujian Medical University, Fujian Medical University, Fuzhou, China
| | - Chengyang Li
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Qirong Zheng
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Zhuoyue Li
- Department of Infectious diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Dan Xu
- Foreign Language Department, Xuzhou Medical University, Xuzhou, China
| | - Cuiling Xie
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Mingqi Zhang
- School of Nursing, Fujian Medical University, Fuzhou, China
| | - Rongjin Lin
- School of Nursing, Fujian Medical University, Fuzhou, China
- Department of Nursing, The First Affiliated Hospital of Fujian Medical University, Fujian Medical University, Fuzhou, China
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13
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Zhao F, Balthazaar S, Hiremath SV, Nightingale TE, Panza GS. Enhancing Spinal Cord Injury Care: Using Wearable Technologies for Physical Activity, Sleep, and Cardiovascular Health. Arch Phys Med Rehabil 2024:S0003-9993(24)01076-1. [PMID: 38972475 DOI: 10.1016/j.apmr.2024.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 06/13/2024] [Accepted: 06/24/2024] [Indexed: 07/09/2024]
Abstract
Wearable devices have the potential to advance health care by enabling real-time monitoring of biobehavioral data and facilitating the management of an individual's health conditions. Individuals living with spinal cord injury (SCI) have impaired motor function, which results in deconditioning and worsening cardiovascular health outcomes. Wearable devices may promote physical activity and allow the monitoring of secondary complications associated with SCI, potentially improving motor function, sleep, and cardiovascular health. However, several challenges remain to optimize the application of wearable technologies within this population. One is striking a balance between research-grade and consumer-grade devices in terms of cost, accessibility, and validity. Additionally, limited literature supports the validity and use of wearable technology in monitoring cardio-autonomic and sleep outcomes for individuals with SCI. Future directions include conducting performance evaluations of wearable devices to precisely capture the additional variation in movement and physiological parameters seen in those with SCI. Moreover, efforts to make the devices small, lightweight, and inexpensive for consumer ease of use may affect those with severe motor impairments. Overcoming these challenges holds the potential for wearable devices to help individuals living with SCI receive timely feedback to manage their health conditions and help clinicians gather comprehensive patient health information to aid in diagnosis and treatment.
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Affiliation(s)
- Fei Zhao
- Department of Health Care Sciences, Program of Occupational Therapy, Wayne State University, Detroit, MI; John D. Dingell VA Medical Center, Research and Development, Detroit, MI
| | - Shane Balthazaar
- School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada; Department of Cardiology, University Hospitals Birmingham National Health Service (NHS) Foundation Trust, Birmingham, United Kingdom
| | - Shivayogi V Hiremath
- Department of Health and Rehabilitation Sciences, Temple University, Philadelphia, PA
| | - Tom E Nightingale
- School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.
| | - Gino S Panza
- Department of Health Care Sciences, Program of Occupational Therapy, Wayne State University, Detroit, MI; John D. Dingell VA Medical Center, Research and Development, Detroit, MI.
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14
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Li Z, Cheng S, Guo B, Ding L, Liang Y, Shen Y, Li J, Hu Y, Long T, Guo X, Ge J, Gao R, Pibarot P, Zhang B, Xu H, Clavel MA, Wu Y. Wearable device-measured moderate to vigorous physical activity and risk of degenerative aortic valve stenosis. Eur Heart J 2024:ehae406. [PMID: 38953786 DOI: 10.1093/eurheartj/ehae406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 04/04/2024] [Accepted: 06/17/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND AND AIMS Physical activity has proven effective in preventing atherosclerotic cardiovascular disease, but its role in preventing degenerative valvular heart disease (VHD) remains uncertain. This study aimed to explore the dose-response association between moderate to vigorous physical activity (MVPA) volume and the risk of degenerative VHD among middle-aged adults. METHODS A full week of accelerometer-derived MVPA data from 87 248 UK Biobank participants (median age 63.3, female: 56.9%) between 2013 and 2015 were used for primary analysis. Questionnaire-derived MVPA data from 361 681 UK Biobank participants (median age 57.7, female: 52.7%) between 2006 and 2010 were used for secondary analysis. The primary outcome was the diagnosis of incident degenerative VHD, including aortic valve stenosis (AS), aortic valve regurgitation (AR), and mitral valve regurgitation (MR). The secondary outcome was VHD-related intervention or mortality. RESULTS In the accelerometer-derived MVPA cohort, 555 incident AS, 201 incident AR, and 655 incident MR occurred during a median follow-up of 8.11 years. Increased MVPA volume showed a steady decline in AS risk and subsequent AS-related intervention or mortality risk, levelling off beyond approximately 300 min/week. In contrast, its association with AR or MR incidence was less apparent. The adjusted rates of AS incidence (95% confidence interval) across MVPA quartiles (Q1-Q4) were 11.60 (10.20, 13.20), 7.82 (6.63, 9.23), 5.74 (4.67, 7.08), and 5.91 (4.73, 7.39) per 10 000 person-years. The corresponding adjusted rates of AS-related intervention or mortality were 4.37 (3.52, 5.43), 2.81 (2.13, 3.71), 1.93 (1.36, 2.75), and 2.14 (1.50, 3.06) per 10 000 person-years, respectively. Aortic valve stenosis risk reduction was also observed with questionnaire-based MVPA data [adjusted absolute difference Q4 vs. Q1: AS incidence, -1.41 (-.67, -2.14) per 10 000 person-years; AS-related intervention or mortality, -.38 (-.04, -.88) per 10 000 person-years]. The beneficial association remained consistent in high-risk populations for AS, including patients with hypertension, obesity, dyslipidaemia, and chronic kidney disease. CONCLUSIONS Higher MVPA volume was associated with a lower risk of developing AS and subsequent AS-related intervention or mortality. Future research needs to validate these findings in diverse populations with longer durations and repeated periods of activity monitoring.
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Affiliation(s)
- Ziang Li
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China
- Research Center, Institut Universitaire de Cardiologie et de Pneumologie de Québec (Quebec Heart & Lung Institute), Université Laval, 2725 Chemin Sainte-Foy, Québec City, Québec, Canada G1V-4G5
| | - Sijing Cheng
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China
| | - Bo Guo
- Department of Medicine for Sports and Performing Arts, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Lu Ding
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
- Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yu Liang
- Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yinghan Shen
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Jinyue Li
- Key Laboratory of Cardiovascular Epidemiology, Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Yiqing Hu
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China
| | - Tianxin Long
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China
| | - Xinli Guo
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China
| | - Junbo Ge
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, Shanghai, China
| | - Runlin Gao
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, No.167 Beilishi Road, Beijing 100037, China
| | - Philippe Pibarot
- Research Center, Institut Universitaire de Cardiologie et de Pneumologie de Québec (Quebec Heart & Lung Institute), Université Laval, 2725 Chemin Sainte-Foy, Québec City, Québec, Canada G1V-4G5
| | - Bin Zhang
- State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, Beijing, China
- Research Center, Institut Universitaire de Cardiologie et de Pneumologie de Québec (Quebec Heart & Lung Institute), Université Laval, 2725 Chemin Sainte-Foy, Québec City, Québec, Canada G1V-4G5
| | - Haiyan Xu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, No.167 Beilishi Road, Beijing 100037, China
| | - Marie-Annick Clavel
- Research Center, Institut Universitaire de Cardiologie et de Pneumologie de Québec (Quebec Heart & Lung Institute), Université Laval, 2725 Chemin Sainte-Foy, Québec City, Québec, Canada G1V-4G5
| | - Yongjian Wu
- Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science, Peking Union Medical College, No.167 Beilishi Road, Beijing 100037, China
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15
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Gill SK, Barsky A, Guan X, Bunting KV, Karwath A, Tica O, Stanbury M, Haynes S, Folarin A, Dobson R, Kurps J, Asselbergs FW, Grobbee DE, Camm AJ, Eijkemans MJC, Gkoutos GV, Kotecha D. Consumer wearable devices for evaluation of heart rate control using digoxin versus beta-blockers: the RATE-AF randomized trial. Nat Med 2024; 30:2030-2036. [PMID: 39009776 PMCID: PMC11271403 DOI: 10.1038/s41591-024-03094-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 05/24/2024] [Indexed: 07/17/2024]
Abstract
Consumer-grade wearable technology has the potential to support clinical research and patient management. Here, we report results from the RATE-AF trial wearables study, which was designed to compare heart rate in older, multimorbid patients with permanent atrial fibrillation and heart failure who were randomized to treatment with either digoxin or beta-blockers. Heart rate (n = 143,379,796) and physical activity (n = 23,704,307) intervals were obtained from 53 participants (mean age 75.6 years (s.d. 8.4), 40% women) using a wrist-worn wearable linked to a smartphone for 20 weeks. Heart rates in participants treated with digoxin versus beta-blockers were not significantly different (regression coefficient 1.22 (95% confidence interval (CI) -2.82 to 5.27; P = 0.55); adjusted 0.66 (95% CI -3.45 to 4.77; P = 0.75)). No difference in heart rate was observed between the two groups of patients after accounting for physical activity (P = 0.74) or patients with high activity levels (≥30,000 steps per week; P = 0.97). Using a convolutional neural network designed to account for missing data, we found that wearable device data could predict New York Heart Association functional class 5 months after baseline assessment similarly to standard clinical measures of electrocardiographic heart rate and 6-minute walk test (F1 score 0.56 (95% CI 0.41 to 0.70) versus 0.55 (95% CI 0.41 to 0.68); P = 0.88 for comparison). The results of this study indicate that digoxin and beta-blockers have equivalent effects on heart rate in atrial fibrillation at rest and on exertion, and suggest that dynamic monitoring of individuals with arrhythmia using wearable technology could be an alternative to in-person assessment. ClinicalTrials.gov identifier: NCT02391337 .
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Affiliation(s)
- Simrat K Gill
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | - Andrey Barsky
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Xin Guan
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Karina V Bunting
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
- West Midlands NHS Secure Data Environment, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Andreas Karwath
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- West Midlands NHS Secure Data Environment, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Otilia Tica
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK
| | | | | | - Amos Folarin
- Department of Biostatistics & Health Informatics, King's College London, London, UK
- Health Data Research UK, University College London, London, UK
| | - Richard Dobson
- Department of Biostatistics & Health Informatics, King's College London, London, UK
- Health Data Research UK, University College London, London, UK
| | - Julia Kurps
- Real World Data team, The Hyve, Utrecht, the Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Amsterdam University Medical Center, Department of Cardiology, University of Amsterdam, Amsterdam, the Netherlands
| | - Diederick E Grobbee
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - A John Camm
- Cardiology Clinical Academic Group, St George's University of London, London, UK
| | - Marinus J C Eijkemans
- Amsterdam University Medical Center, Department of Cardiology, University of Amsterdam, Amsterdam, the Netherlands
| | - Georgios V Gkoutos
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Dipak Kotecha
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.
- West Midlands NHS Secure Data Environment, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
- Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
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16
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Pastorino R, Pezzullo AM, Agodi A, de Waure C, Mazzucco W, Russo L, Bianchi M, Maio A, Farina S, Porcelli M, Tona DM, Di Pumpo M, Amore R, Wachocka M, Pasciuto T, Barchitta M, Magnano San Lio R, Favara G, Tuttolomondo A, Tramuto F, Morello G, De Bella DD, Fruscione S, Severino A, Liuzzo G, Boccia S. Efficacy of polygenic risk scores and digital technologies for INNOvative personalized cardiovascular disease PREVention in high-risk adults: protocol of a randomized controlled trial. Front Public Health 2024; 12:1335894. [PMID: 38947346 PMCID: PMC11211566 DOI: 10.3389/fpubh.2024.1335894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 05/28/2024] [Indexed: 07/02/2024] Open
Abstract
Background Cardiovascular diseases (CVDs) pose a significant global health challenge, necessitating innovative approaches for primary prevention. Personalized prevention, based on genetic risk scores (PRS) and digital technologies, holds promise in revolutionizing CVD preventive strategies. However, the clinical efficacy of these interventions requires further investigation. This study presents the protocol of the INNOPREV randomized controlled trial, aiming to evaluate the clinical efficacy of PRS and digital technologies in personalized cardiovascular disease prevention. Methods The INNOPREV trial is a four-arm RCT conducted in Italy. A total of 1,020 participants, aged 40-69 with high 10-year CVD risk based on SCORE 2 charts, will be randomly assigned to traditional CVD risk assessment, genetic testing (CVD PRS), digital intervention (app and smart band), or a combination of genetic testing and digital intervention. The primary objective is to evaluate the efficacy of providing CVD PRS information, measured at baseline, either alone or in combination with the use of an app and a smart band, on two endpoints: changes in lifestyle patterns, and modification in CVD risk profiles. Participants will undergo a comprehensive assessment and cardiovascular evaluation at baseline, with follow-up visits at one, five, and 12 months. Lifestyle changes and CVD risk profiles will be assessed at different time points beyond the initial assessment, using the Life's Essential 8 and SCORE 2, respectively. Blood samples will be collected at baseline and at study completion to evaluate changes in lipid profiles. The analysis will employ adjusted mixed-effect models for repeated measures to assess significant differences in the data collected over time. Additionally, potential moderators and mediators will be examined to understand the underlying mechanisms of behavior change. Discussion As the largest trial in this context, the INNOPREV trial will contribute to the advancement of personalized cardiovascular disease prevention, with the potential to positively impact public health and reduce the burden of CVDs on healthcare systems. By systematically examining the clinical efficacy of PRS and digital interventions, this trial aims to provide valuable evidence to guide future preventive strategies and enhance population health outcomes.
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Affiliation(s)
- Roberta Pastorino
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Angelo Maria Pezzullo
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Antonella Agodi
- Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia”, University of Catania, Catania, Italy
- Azienda Ospedaliero Universitaria Policlinico “G. Rodolico-San Marco”, Programme: Hospital Epidemiology and Translational Research: Epidemiological Surveillance, Risk Assessment and Control, Catania, Italy
| | - Chiara de Waure
- Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Walter Mazzucco
- Azienda Ospedaliera Universitaria Policlinico “Paolo Giaccone” di Palermo, Palermo, Italy
- Dipartimento PROMISE, Università degli Studi di Palermo, Palermo, Italy
| | - Luigi Russo
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Martina Bianchi
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Alessandra Maio
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Sara Farina
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Martina Porcelli
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Diego Maria Tona
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Matteo Di Pumpo
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Rosarita Amore
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Malgorzata Wachocka
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Tina Pasciuto
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
- Research Core Facilty Data Collection G-STeP, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Martina Barchitta
- Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia”, University of Catania, Catania, Italy
| | - Roberta Magnano San Lio
- Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia”, University of Catania, Catania, Italy
| | - Giuliana Favara
- Department of Medical and Surgical Sciences and Advanced Technologies “GF Ingrassia”, University of Catania, Catania, Italy
| | - Antonino Tuttolomondo
- Azienda Ospedaliera Universitaria Policlinico “Paolo Giaccone” di Palermo, Palermo, Italy
- Dipartimento PROMISE, Università degli Studi di Palermo, Palermo, Italy
| | - Fabio Tramuto
- Azienda Ospedaliera Universitaria Policlinico “Paolo Giaccone” di Palermo, Palermo, Italy
- Dipartimento PROMISE, Università degli Studi di Palermo, Palermo, Italy
| | - Gaia Morello
- Azienda Ospedaliera Universitaria Policlinico “Paolo Giaccone” di Palermo, Palermo, Italy
| | | | - Santo Fruscione
- Dipartimento PROMISE, Università degli Studi di Palermo, Palermo, Italy
| | - Anna Severino
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario A. Gemelli—IRCCS, Rome, Italy
- Department of Cardiovascular and Pulmonary Sciences, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Giovanna Liuzzo
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario A. Gemelli—IRCCS, Rome, Italy
- Department of Cardiovascular and Pulmonary Sciences, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Stefania Boccia
- Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
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Zhang WY, Zhuang SC, Chen YM, Wang HN. Validity and reliability of a wearable blood flow restriction training device for arterial occlusion pressure assessment. Front Physiol 2024; 15:1404247. [PMID: 38911327 PMCID: PMC11191424 DOI: 10.3389/fphys.2024.1404247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 05/20/2024] [Indexed: 06/25/2024] Open
Abstract
Purpose The blood flow restriction (BFR) training is an effective approach to promoting muscle strength, muscle hypertrophy, and regulating the peripheral vascular system. It is recommended to use to the percentage of individual arterial occlusion pressure (AOP) to ensure safety and effectiveness. The gold standard method for assessing arterial occlusive disease is typically measured using Doppler ultrasound. However, its high cost and limited accessibility restrict its use in clinical and practical applications. A novel wearable BFR training device (Airbands) with automatic AOP assessment provides an alternative solution. This study aims to examine the reliability and validity of the wearable BFR training device. Methods Ninety-two participants (46 female and 46 male) were recruited for this study. Participants were positioned in the supine position with the wearable BFR training device placed on the proximal portion of the right thigh. AOP was measured automatically by the software program and manually by gradually increasing the pressure until the pulse was no longer detected by color Doppler ultrasound, respectively. Validity, inter-rater reliability, and test-retest reliability were assessed by intraclass correlation coefficients (ICC) and Bland-Altman analysis. Results The wearable BFR training device demonstrated good validity (ICC = 0.85, mean difference = 4.1 ± 13.8 mmHg [95% CI: -23.0 to 31.2]), excellent inter-rater reliability (ICC = 0.97, mean difference = -1.4 ± 6.7 mmHg [95% CI: -14.4 to 11.7]), and excellent test-retest reliability (ICC = 0.94, mean difference = 0.6 ± 8.6 mmHg [95% CI: -16.3 to 17.5]) for the assessment of AOP. These results were robust in both male and female subgroups. Conclusion The wearable BFR training device can be used as a valid and reliable tool to assess the AOP of the lower limb in the supine position during BFR training.
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Affiliation(s)
- Wei-Yang Zhang
- School of Sports Medicine and Health, Chengdu Sport University, Chengdu, Sichuan, China
- Sports Medicine Key Laboratory of Sichuan Province, Chengdu, Sichuan, China
| | - Shu-Can Zhuang
- School of Sports Medicine and Health, Chengdu Sport University, Chengdu, Sichuan, China
| | - Yuan-Ming Chen
- School of Sports Medicine and Health, Chengdu Sport University, Chengdu, Sichuan, China
| | - Hao-Nan Wang
- Sports Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Orthopedics and Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Hurtado L, Gonzalez Concepcion M, Flix-Valle A, Ruiz-Romeo M, Gonzalez-Rodriguez S, Peña M, Paviglianiti A, Pera Jambrina MA, Sureda A, Ochoa-Arnedo C, Mussetti A. Telemedicine With Wearable Technologies in Patients Undergoing Hematopoietic Cell Transplantation and Chimeric Antigen Receptor T-Cell Therapy (TEL-HEMATO Study): Prospective Noninterventional Single-Center Study. JMIR Form Res 2024; 8:e55918. [PMID: 38833696 PMCID: PMC11185900 DOI: 10.2196/55918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/28/2024] [Accepted: 04/04/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Patients with hematological malignancies receiving hematopoietic cell transplantation (HCT) or chimeric antigen receptor (CAR) T-cell therapy are at risk of developing serious clinical complications after discharge. OBJECTIVE The aim of the TEL-HEMATO study was to improve our telehealth platform for the follow-up of patients undergoing HCT or CAR T-cell therapy during the first 3 months after discharge with the addition of wearable devices. METHODS Eleven patients who received autologous (n=2) or allogeneic (n=5) HCT or CAR T-cell therapy (n=4) for hematological malignancies were screened from November 2022 to July 2023. Two patients discontinued the study after enrollment. The telehealth platform consisted of the daily collection of vital signs, physical symptoms, and quality of life assessment up to 3 months after hospital discharge. Each patient received a clinically validated smartwatch (ScanWatch) and a digital thermometer, and a dedicated smartphone app was used to collect these data. Daily revision of the data was performed through a web-based platform by a hematologist or a nurse specialized in HCT and CAR T-cell therapy. RESULTS Vital signs measured through ScanWatch were successfully collected with medium/high adherence: heart rate was recorded in 8/9 (89%) patients, oxygen saturation and daily steps were recorded in 9/9 (100%) patients, and sleeping hours were recorded in 7/9 (78%) patients. However, temperature recorded manually by the patients was associated with lower compliance, which was recorded in 5/9 (55%) patients. Overall, 5/9 (55%) patients reported clinical symptoms in the app. Quality of life assessment was completed by 8/9 (89%) patients at study enrollment, which decreased to 3/9 (33%) at the end of the third month. Usability was considered acceptable through ratings provided on the System Usability Scale. However, technological issues were reported by the patients. CONCLUSIONS While the addition of wearable devices to a telehealth clinical platform could have potentially synergic benefits for HCT and CAR T-cell therapy patient monitoring, noncomplete automation of the platform and the absence of a dedicated telemedicine team still represent major limitations to be overcome. This is especially true in our real-life setting where the target population generally comprises patients of older age with a low digital education level.
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Affiliation(s)
- Lidia Hurtado
- Clinical Hematology Department, Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain
| | - Melinda Gonzalez Concepcion
- Department of Fundamental and Clinical Nursing, Faculty of Nursing, Bellvitge Campus, Universitat de Barcelona, Barcelona, Spain
- Psychooncology and Digital Health Research Group, Barcelona, Spain
| | - Aida Flix-Valle
- ICOnnecta't Digital Health Program and Psycho-Oncology Service, Institut Català d'Oncologia, Barcelona, Spain
- Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
| | - Marina Ruiz-Romeo
- ICOnnecta't Digital Health Program and Psycho-Oncology Service, Institut Català d'Oncologia, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
| | - Sonia Gonzalez-Rodriguez
- Clinical Hematology Department, Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain
| | - Marta Peña
- Clinical Hematology Department, Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
| | - Annalisa Paviglianiti
- Clinical Hematology Department, Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
- Department of Medicine, Unit of Endocrinology and Diabetes, Università Campus Bio-Medico di Roma, Rome, Italy
| | | | - Anna Sureda
- Clinical Hematology Department, Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain
- Department of Fundamental and Clinical Nursing, Faculty of Nursing, Bellvitge Campus, Universitat de Barcelona, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
| | - Cristian Ochoa-Arnedo
- Psychooncology and Digital Health Research Group, Barcelona, Spain
- ICOnnecta't Digital Health Program and Psycho-Oncology Service, Institut Català d'Oncologia, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
| | - Alberto Mussetti
- Clinical Hematology Department, Institut Català d'Oncologia, Hospital Duran i Reynals, Barcelona, Spain
- Institut d'Investigació Biomèdica de Bellvitge, Barcelona, Spain
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Zhi C, Shi S, Wu H, Si Y, Zhang S, Lei L, Hu J. Emerging Trends of Nanofibrous Piezoelectric and Triboelectric Applications: Mechanisms, Electroactive Materials, and Designed Architectures. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2401264. [PMID: 38545963 DOI: 10.1002/adma.202401264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 03/19/2024] [Indexed: 04/13/2024]
Abstract
Over the past few decades, significant progress in piezo-/triboelectric nanogenerators (PTEGs) has led to the development of cutting-edge wearable technologies. Nanofibers with good designability, controllable morphologies, large specific areas, and unique physicochemical properties provide a promising platform for PTEGs for various advanced applications. However, the further development of nanofiber-based PTEGs is limited by technical difficulties, ranging from materials design to device integration. Herein, the current developments in PTEGs based on electrospun nanofibers are systematically reviewed. This review begins with the mechanisms of PTEGs and the advantages of nanofibers and nanodevices, including high breathability, waterproofness, scalability, and thermal-moisture comfort. In terms of materials and structural design, novel electroactive nanofibers and structure assemblies based on 1D micro/nanostructures, 2D bionic structures, and 3D multilayered structures are discussed. Subsequently, nanofibrous PTEGs in applications such as energy harvesters, personalized medicine, personal protective equipment, and human-machine interactions are summarized. Nanofiber-based PTEGs still face many challenges such as energy efficiency, material durability, device stability, and device integration. Finally, the research gap between research and practical applications of PTEGs is discussed, and emerging trends are proposed, providing some ideas for the development of intelligent wearables.
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Affiliation(s)
- Chuanwei Zhi
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
| | - Shuo Shi
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
| | - Hanbai Wu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
| | - Yifan Si
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
| | - Shuai Zhang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
| | - Leqi Lei
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
| | - Jinlian Hu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, Hong Kong SAR, 999077, China
- City University of Hong Kong Shenzhen Research Institute, Shenzhen, 518057, P. R. China
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20
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Phan V, Song K, Silva RS, Silbernagel KG, Baxter JR, Halilaj E. Seven Things to Know About Exercise Classification With Inertial Sensing Wearables. IEEE J Biomed Health Inform 2024; 28:3411-3421. [PMID: 38381640 PMCID: PMC11284806 DOI: 10.1109/jbhi.2024.3368042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
OBJECTIVE Exercise monitoring with low-cost wearables could improve the efficacy of remote physical-therapy prescriptions by tracking compliance and informing the delivery of tailored feedback. While a multitude of commercial wearables can detect activities of daily life, such as walking and running, they cannot accurately detect physical-therapy exercises. The goal of this study was to build open-source classifiers for remote physical-therapy monitoring and provide insight on how data collection choices may impact classifier performance. METHODS We trained and evaluated multi-class classifiers using data from 19 healthy adults who performed 37 exercises while wearing 10 inertial measurement units (IMUs) on the chest, pelvis, wrists, thighs, shanks, and feet. We investigated the effect of sensor density, location, type, sampling frequency, output granularity, feature engineering, and training-data size on exercise-classification performance. RESULTS Exercise groups (n = 10) could be classified with 96% accuracy using a set of 10 IMUs and with 89% accuracy using a single pelvis-worn IMU. Multiple sensor modalities (i.e., accelerometers and gyroscopes), high sampling frequencies, and more data from the same population did not improve model performance, but in the future data from diverse populations and better feature engineering could. CONCLUSIONS Given the growing demand for exercise monitoring systems, our sensitivity analyses, along with open-source tools and data, should reduce barriers for product developers, who are balancing accuracy with product formfactor, and increase transparency and trust in clinicians and patients.
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Affiliation(s)
- Vu Phan
- Mechanical Engineering Department, Carnegie Mellon University Pittsburgh, PA, USA
| | - Ke Song
- Orthopaedic Surgery Department, University of Pennsylvania, Philadelphia, PA, USA
| | - Rodrigo Scattone Silva
- Postgraduate Program in Rehabilitation Sciences, Federal University of Rio Grande do Norte, Santa Cruz, Brazil
| | | | - Josh R. Baxter
- Orthopaedic Surgery Department, University of Pennsylvania, Philadelphia, PA, USA
| | - Eni Halilaj
- Mechanical Engineering Department, Carnegie Mellon University Pittsburgh, PA, USA
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Armbruster A, Mohamed AM, Phan HT, Weber W. Lighting the way: recent developments and applications in molecular optogenetics. Curr Opin Biotechnol 2024; 87:103126. [PMID: 38554641 DOI: 10.1016/j.copbio.2024.103126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/27/2024] [Accepted: 03/08/2024] [Indexed: 04/02/2024]
Abstract
Molecular optogenetics utilizes genetically encoded, light-responsive protein switches to control the function of molecular processes. Over the last two years, there have been notable advances in the development of novel optogenetic switches, their utilization in elucidating intricate signaling pathways, and their progress toward practical applications in biotechnological processes, material sciences, and therapeutic applications. In this review, we discuss these areas, offer insights into recent developments, and contemplate future directions.
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Affiliation(s)
- Anja Armbruster
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany; CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Schänzlestr. 18, 79104 Freiburg, Germany; Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104 Freiburg, Germany
| | - Asim Me Mohamed
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany
| | - Hoang T Phan
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany
| | - Wilfried Weber
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany; CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Schänzlestr. 18, 79104 Freiburg, Germany; Saarland University, Department of Materials Science and Engineering, Campus D2 2, 66123 Saarbrücken, Germany.
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22
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Du Y, Kim JH, Kong H, Li AA, Jin ML, Kim DH, Wang Y. Biocompatible Electronic Skins for Cardiovascular Health Monitoring. Adv Healthc Mater 2024; 13:e2303461. [PMID: 38569196 DOI: 10.1002/adhm.202303461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/27/2024] [Indexed: 04/05/2024]
Abstract
Cardiovascular diseases represent a significant threat to the overall well-being of the global population. Continuous monitoring of vital signs related to cardiovascular health is essential for improving daily health management. Currently, there has been remarkable proliferation of technology focused on collecting data related to cardiovascular diseases through daily electronic skin monitoring. However, concerns have arisen regarding potential skin irritation and inflammation due to the necessity for prolonged wear of wearable devices. To ensure comfortable and uninterrupted cardiovascular health monitoring, the concept of biocompatible electronic skin has gained substantial attention. In this review, biocompatible electronic skins for cardiovascular health monitoring are comprehensively summarized and discussed. The recent achievements of biocompatible electronic skin in cardiovascular health monitoring are introduced. Their working principles, fabrication processes, and performances in sensing technologies, materials, and integration systems are highlighted, and comparisons are made with other electronic skins used for cardiovascular monitoring. In addition, the significance of integrating sensing systems and the updating wireless communication for the development of the smart medical field is explored. Finally, the opportunities and challenges for wearable electronic skin are also examined.
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Affiliation(s)
- Yucong Du
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, 266071, China
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Ji Hong Kim
- Department of Chemical Engineering, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Nano Science and Technology, Hanyang University, Seoul, 04763, Republic of Korea
- Clean-Energy Research Institute, Hanyang University, Seoul, 04763, Republic of Korea
| | - Hui Kong
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Anne Ailina Li
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Ming Liang Jin
- Institute for Future, Shandong Key Laboratory of Industrial Control Technology, School of Automation, Qingdao University, Qingdao, 266071, China
| | - Do Hwan Kim
- Department of Chemical Engineering, Hanyang University, Seoul, 04763, Republic of Korea
- Institute of Nano Science and Technology, Hanyang University, Seoul, 04763, Republic of Korea
- Clean-Energy Research Institute, Hanyang University, Seoul, 04763, Republic of Korea
| | - Yin Wang
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, Qingdao, 266071, China
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23
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Armoundas AA, Ahmad FS, Bennett DA, Chung MK, Davis LL, Dunn J, Narayan SM, Slotwiner DJ, Wiley KK, Khera R. Data Interoperability for Ambulatory Monitoring of Cardiovascular Disease: A Scientific Statement From the American Heart Association. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e000095. [PMID: 38779844 DOI: 10.1161/hcg.0000000000000095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
Wearable devices are increasingly used by a growing portion of the population to track health and illnesses. The data emerging from these devices can potentially transform health care. This requires an interoperability framework that enables the deployment of platforms, sensors, devices, and software applications within diverse health systems, aiming to facilitate innovation in preventing and treating cardiovascular disease. However, the current data ecosystem includes several noninteroperable systems that inhibit such objectives. The design of clinically meaningful systems for accessing and incorporating these data into clinical workflows requires strategies to ensure the quality of data and clinical content and patient and caregiver accessibility. This scientific statement aims to address the best practices, gaps, and challenges pertaining to data interoperability in this area, with considerations for (1) data integration and the scope of measures, (2) application of these data into clinical approaches/strategies, and (3) regulatory/ethical/legal issues.
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Coles CE, Earl H, Anderson BO, Barrios CH, Bienz M, Bliss JM, Cameron DA, Cardoso F, Cui W, Francis PA, Jagsi R, Knaul FM, McIntosh SA, Phillips KA, Radbruch L, Thompson MK, André F, Abraham JE, Bhattacharya IS, Franzoi MA, Drewett L, Fulton A, Kazmi F, Inbah Rajah D, Mutebi M, Ng D, Ng S, Olopade OI, Rosa WE, Rubasingham J, Spence D, Stobart H, Vargas Enciso V, Vaz-Luis I, Villarreal-Garza C. The Lancet Breast Cancer Commission. Lancet 2024; 403:1895-1950. [PMID: 38636533 DOI: 10.1016/s0140-6736(24)00747-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 12/18/2023] [Accepted: 04/09/2024] [Indexed: 04/20/2024]
Affiliation(s)
| | - Helena Earl
- Department of Oncology, University of Cambridge, Cambridge, UK
| | - Benjamin O Anderson
- Global Breast Cancer Initiative, World Health Organisation and Departments of Surgery and Global Health Medicine, University of Washington, Seattle, WA, USA
| | - Carlos H Barrios
- Oncology Research Center, Hospital São Lucas, Porto Alegre, Brazil
| | - Maya Bienz
- Mount Vernon Cancer Centre, East and North Hertfordshire NHS Trust, London, UK; Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - David A Cameron
- Institute of Genetics and Cancer and Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Fatima Cardoso
- Breast Unit, Champalimaud Clinical Center/Champalimaud Foundation, Lisbon, Portugal
| | - Wanda Cui
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Prudence A Francis
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Reshma Jagsi
- Emory University School of Medicine, Atlanta, GA, USA
| | - Felicia Marie Knaul
- Institute for Advanced Study of the Americas, University of Miami, Miami, FL, USA; Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA; Tómatelo a Pecho, Mexico City, Mexico
| | - Stuart A McIntosh
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Kelly-Anne Phillips
- Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Lukas Radbruch
- Department of Palliative Medicine, University Hospital Bonn, Bonn, Germany
| | | | | | - Jean E Abraham
- Department of Oncology, University of Cambridge, Cambridge, UK
| | | | | | - Lynsey Drewett
- Royal Devon University Healthcare NHS Foundation Trust, Exeter, UK
| | | | - Farasat Kazmi
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
| | | | | | - Dianna Ng
- Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Szeyi Ng
- The Institute of Cancer Research, London, UK
| | | | - William E Rosa
- Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | | | | | | | | | | | - Cynthia Villarreal-Garza
- Breast Cancer Center, Hospital Zambrano Hellion TecSalud, Tecnologico de Monterrey, Monterrey, Mexico
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Tandon A, Avari Silva JN, Bhatt AB, Drummond CK, Hill AC, Paluch AE, Waits S, Zablah JE, Harris KC. Advancing Wearable Biosensors for Congenital Heart Disease: Patient and Clinician Perspectives: A Science Advisory From the American Heart Association. Circulation 2024; 149:e1134-e1142. [PMID: 38545775 DOI: 10.1161/cir.0000000000001225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Wearable biosensors (wearables) enable continual, noninvasive physiologic and behavioral monitoring at home for those with pediatric or congenital heart disease. Wearables allow patients to access their personal data and monitor their health. Despite substantial technologic advances in recent years, issues with hardware design, data analysis, and integration into the clinical workflow prevent wearables from reaching their potential in high-risk congenital heart disease populations. This science advisory reviews the use of wearables in patients with congenital heart disease, how to improve these technologies for clinicians and patients, and ethical and regulatory considerations. Challenges related to the use of wearables are common to every clinical setting, but specific topics for consideration in congenital heart disease are highlighted.
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Mangold KE, Carter RE, Siontis KC, Noseworthy PA, Lopez-Jimenez F, Asirvatham SJ, Friedman PA, Attia ZI. Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age-related changes, anomaly detection, and data authenticity in mobile health platforms. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2024; 5:314-323. [PMID: 38774362 PMCID: PMC11104462 DOI: 10.1093/ehjdh/ztae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 03/05/2024] [Accepted: 03/12/2024] [Indexed: 05/24/2024]
Abstract
Aims Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record. Methods and results We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively. Conclusion The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.
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Affiliation(s)
- Kathryn E Mangold
- Department of Cardiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA
| | - Rickey E Carter
- Department of Quantitative Health Sciences, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, USA
| | | | - Peter A Noseworthy
- Department of Cardiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA
| | | | - Samuel J Asirvatham
- Department of Cardiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA
| | - Paul A Friedman
- Department of Cardiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA
| | - Zachi I Attia
- Department of Cardiology, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA
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Bhaltadak V, Ghewade B, Yelne S. A Comprehensive Review on Advancements in Wearable Technologies: Revolutionizing Cardiovascular Medicine. Cureus 2024; 16:e61312. [PMID: 38947726 PMCID: PMC11212841 DOI: 10.7759/cureus.61312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Accepted: 05/28/2024] [Indexed: 07/02/2024] Open
Abstract
Wearable technologies have emerged as powerful tools in healthcare, offering continuous monitoring and personalized insights outside traditional clinical settings. These devices have garnered significant attention in cardiovascular medicine for their potential to transform patient care and improve outcomes. This comprehensive review provides an overview of wearable technologies' evolution, advancements, and applications in cardiovascular medicine. We examine the miniaturization of sensors, integration of artificial intelligence (AI), and proliferation of remote patient monitoring solutions. Key findings include the role of wearables in the early detection of cardiovascular conditions, personalized health tracking, and remote patient management. Challenges such as data privacy concerns and regulatory hurdles are also addressed. The adoption of wearable technologies holds promise for shifting healthcare from reactive to proactive, enabling precision diagnostics, treatment optimization, and preventive strategies. Collaboration among healthcare stakeholders is essential to harnessing the full potential of wearables in cardiovascular medicine and ushering in a new era of personalized, proactive healthcare.
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Affiliation(s)
- Vaishnavi Bhaltadak
- Respiratory Medicine, School of Allied Health Science, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Babaji Ghewade
- Respiratory Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Seema Yelne
- Nursing, Shalinitai Meghe College of Nursing, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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28
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Mah DY. Wearable technology for heart rhythm monitoring in children. Heart Rhythm 2024; 21:590-591. [PMID: 38331305 DOI: 10.1016/j.hrthm.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 02/02/2024] [Indexed: 02/10/2024]
Affiliation(s)
- Douglas Y Mah
- Department of Cardiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
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Lingawi S, Hutton J, Khalili M, Shadgan B, Christenson J, Grunau B, Kuo C. Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review. Ann Biomed Eng 2024; 52:1136-1158. [PMID: 38358559 DOI: 10.1007/s10439-024-03442-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/03/2024] [Indexed: 02/16/2024]
Abstract
Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.
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Affiliation(s)
- Saud Lingawi
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.
- Centre for Aging SMART, University of British Columbia, 2635 Laurel St., Vancouver, BC, V5Z 1M9, Canada.
| | - Jacob Hutton
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada
- British Columbia Emergency Health Services, Vancouver, Canada
- Department of Emergency Medicine, University of British Columbia and St. Paul's Hospital, Vancouver, BC, Canada
- Centre for Advancing Health Outcomes, University of British Columbia, Vancouver, BC, Canada
| | - Mahsa Khalili
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada
- Centre for Aging SMART, University of British Columbia, 2635 Laurel St., Vancouver, BC, V5Z 1M9, Canada
- Department of Emergency Medicine, University of British Columbia and St. Paul's Hospital, Vancouver, BC, Canada
- Centre for Advancing Health Outcomes, University of British Columbia, Vancouver, BC, Canada
| | - Babak Shadgan
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
- Department of Orthopedic Surgery, University of British Columbia, Vancouver, BC, Canada
- International Collaboration on Repair Discoveries, Vancouver, BC, Canada
| | - Jim Christenson
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada
- British Columbia Emergency Health Services, Vancouver, Canada
- Department of Emergency Medicine, University of British Columbia and St. Paul's Hospital, Vancouver, BC, Canada
- Centre for Advancing Health Outcomes, University of British Columbia, Vancouver, BC, Canada
| | - Brian Grunau
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada
- British Columbia Emergency Health Services, Vancouver, Canada
- Department of Emergency Medicine, University of British Columbia and St. Paul's Hospital, Vancouver, BC, Canada
- Centre for Advancing Health Outcomes, University of British Columbia, Vancouver, BC, Canada
| | - Calvin Kuo
- British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
- Centre for Aging SMART, University of British Columbia, 2635 Laurel St., Vancouver, BC, V5Z 1M9, Canada
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30
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Zhao Z, Yang C, Li D. Skin Electrodes Based on TPU Fiber Scaffolds with Conductive Nanocomposites with Stretchability, Breathability, and Washability. MICROMACHINES 2024; 15:598. [PMID: 38793171 PMCID: PMC11122800 DOI: 10.3390/mi15050598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/25/2024] [Accepted: 04/26/2024] [Indexed: 05/26/2024]
Abstract
In the context of an aging population and escalating work pressures, cardiovascular diseases pose increasing health risks. Electrocardiogram (ECG) monitoring presents a preventive tool, but conventional devices often compromise comfort. This study proposes an approach using Ag NW/TPU composites for flexible and breathable epidermal electronics. In this new structure, TPU fibers are used to support Ag NWs/TPU nanocomposites. The TPU fiber-reinforced Ag NW/TPU (TFRAT) nanocomposites exhibit excellent conductivity, stretchability, and electromechanical durability. The composite ensures high steam permeability, maintaining stable electrical performance after washing cycles. Employing this technology, a flexible ECG detection system is developed, augmented with a convolutional neural network (CNN) for automated signal analysis. The experimental results demonstrate the system's reliability in capturing physiological signals. Additionally, a CNN model trained on ECG data achieves over 99% accuracy in diagnosing arrhythmias. This study presents TFRAT as a promising solution for wearable electronics, offering both comfort and functionality in long-term epidermal applications, with implications for healthcare and beyond.
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Affiliation(s)
| | - Chaopeng Yang
- School of Chemical Engineering and Technology, Hebei University of Technology, No. 5340, Xiping Road, Tianjin 300130, China;
| | - Dongchan Li
- School of Chemical Engineering and Technology, Hebei University of Technology, No. 5340, Xiping Road, Tianjin 300130, China;
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Armoundas AA, Narayan SM, Arnett DK, Spector-Bagdady K, Bennett DA, Celi LA, Friedman PA, Gollob MH, Hall JL, Kwitek AE, Lett E, Menon BK, Sheehan KA, Al-Zaiti SS. Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association. Circulation 2024; 149:e1028-e1050. [PMID: 38415358 PMCID: PMC11042786 DOI: 10.1161/cir.0000000000001201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
A major focus of academia, industry, and global governmental agencies is to develop and apply artificial intelligence and other advanced analytical tools to transform health care delivery. The American Heart Association supports the creation of tools and services that would further the science and practice of precision medicine by enabling more precise approaches to cardiovascular and stroke research, prevention, and care of individuals and populations. Nevertheless, several challenges exist, and few artificial intelligence tools have been shown to improve cardiovascular and stroke care sufficiently to be widely adopted. This scientific statement outlines the current state of the art on the use of artificial intelligence algorithms and data science in the diagnosis, classification, and treatment of cardiovascular disease. It also sets out to advance this mission, focusing on how digital tools and, in particular, artificial intelligence may provide clinical and mechanistic insights, address bias in clinical studies, and facilitate education and implementation science to improve cardiovascular and stroke outcomes. Last, a key objective of this scientific statement is to further the field by identifying best practices, gaps, and challenges for interested stakeholders.
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Fujiyoshi K, Yamaoka-Tojo M, Fujiyoshi K, Komatsu T, Oikawa J, Kashino K, Tomoike H, Ako J. Beat-to-beat alterations of acoustic intensity and frequency at the maximum power of heart sounds are associated with NT-proBNP levels. Front Cardiovasc Med 2024; 11:1372543. [PMID: 38628311 PMCID: PMC11018890 DOI: 10.3389/fcvm.2024.1372543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 03/18/2024] [Indexed: 04/19/2024] Open
Abstract
Background Auscultatory features of heart sounds (HS) in patients with heart failure (HF) have been studied intensively. Recent developments in digital and electrical devices for auscultation provided easy listening chances to recognize peculiar sounds related to diastolic HS such as S3 or S4. This study aimed to quantitatively assess HS by acoustic measures of intensity (dB) and audio frequency (Hz). Methods Forty consecutive patients aged between 46 and 87 years (mean age, 74 years) with chronic cardiovascular disease (CVD) were enrolled in the present study after providing written informed consent during their visits to the Kitasato University Outpatient Clinic. HS were recorded at the fourth intercostal space along the left sternal border using a highly sensitive digital device. Two consecutive heartbeats were quantified on sound intensity (dB) and audio frequency (Hz) at the peak power of each spectrogram of S1-S4 using audio editing and recording application software. The participants were classified into three groups, namely, the absence of HF (n = 27), HF (n = 8), and high-risk HF (n = 5), based on the levels of NT-proBNP < 300, ≥300, and ≥900 pg/ml, respectively, and also the levels of ejection fraction (EF), such as preserved EF (n = 22), mildly reduced EF (n = 12), and reduced EF (n = 6). Results The intensities of four components of HS (S1-S4) decreased linearly (p < 0.02-0.001) with levels of body mass index (BMI) (range, 16.2-33.0 kg/m2). Differences in S1 intensity (ΔS1) and its frequency (ΔfS1) between two consecutive beats were non-audible level and were larger in patients with HF than those in patients without HF (ΔS1, r = 0.356, p = 0.024; ΔfS1, r = 0.356, p = 0.024). The cutoff values of ΔS1 and ΔfS1 for discriminating the presence of high-risk HF were 4.0 dB and 5.0 Hz, respectively. Conclusions Despite significant attenuations of all four components of HS by BMI, beat-to-beat alterations of both intensity and frequency of S1 were associated with the severity of HF. Acoustic quantification of HS enabled analyses of sounds below the audible level, suggesting that sound analysis might provide an early sign of HF.
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Affiliation(s)
- Kazuhiro Fujiyoshi
- Department of Cardiovascular Medicine, Kitasato University School of Medicine, Sagamihara, Japan
| | - Minako Yamaoka-Tojo
- Department of Rehabilitation, Kitasato University School of Allied Health Sciences, Sagamihara, Japan
| | - Kanako Fujiyoshi
- Department of Rehabilitation, Kitasato University School of Allied Health Sciences, Sagamihara, Japan
| | - Takumi Komatsu
- Department of Functional Restoration Science, Kitasato University Graduate School of Medical Sciences, Sagamihara, Japan
| | - Jun Oikawa
- Department of Kitasato Clinical Research Center, Kitasato University School of Medicine, Sagamihara, Japan
| | - Kunio Kashino
- Bio-Medical Informatics Research Center, NTT Basic Research Laboratories, Atsugi, Japan
| | - Hitonobu Tomoike
- Bio-Medical Informatics Research Center, NTT Basic Research Laboratories, Atsugi, Japan
| | - Junya Ako
- Department of Cardiovascular Medicine, Kitasato University School of Medicine, Sagamihara, Japan
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Muse ED, Topol EJ. Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management. Cell Metab 2024; 36:670-683. [PMID: 38428435 PMCID: PMC10990799 DOI: 10.1016/j.cmet.2024.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 01/25/2024] [Accepted: 02/06/2024] [Indexed: 03/03/2024]
Abstract
The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpretation of diagnostic studies such as chest X-rays and electrocardiograms in addition to predicting patient outcomes and future disease onset. However, AI has evolved with the introduction of transformer models, allowing analysis of the diverse, multimodal data sources existing in medicine today. Multimodal AI holds great promise in more accurate disease risk assessment and stratification as well as optimizing the key driving factors in cardiometabolic disease: blood pressure, sleep, stress, glucose control, weight, nutrition, and physical activity. In this article we outline the current state of medical AI in cardiometabolic disease, highlighting the potential of multimodal AI to augment personalized prevention and treatment strategies in cardiometabolic disease.
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Affiliation(s)
- Evan D Muse
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA 92037, USA; Division of Cardiovascular Diseases, Scripps Clinic, La Jolla, CA 92037, USA
| | - Eric J Topol
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA 92037, USA; Division of Cardiovascular Diseases, Scripps Clinic, La Jolla, CA 92037, USA.
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Alkhodari M, Hadjileontiadis LJ, Khandoker AH. Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms. IEEE J Biomed Health Inform 2024; 28:1803-1814. [PMID: 38261492 DOI: 10.1109/jbhi.2024.3357506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
One in every four newborns suffers from congenital heart disease (CHD) that causes defects in the heart structure. The current gold-standard assessment technique, echocardiography, causes delays in the diagnosis owing to the need for experts who vary markedly in their ability to detect and interpret pathological patterns. Moreover, echo is still causing cost difficulties for low- and middle-income countries. Here, we developed a deep learning-based attention transformer model to automate the detection of heart murmurs caused by CHD at an early stage of life using cost-effective and widely available phonocardiography (PCG). PCG recordings were obtained from 942 young patients at four major auscultation locations, including the aortic valve (AV), mitral valve (MV), pulmonary valve (PV), and tricuspid valve (TV), and they were annotated by experts as absent, present, or unknown murmurs. A transformation to wavelet features was performed to reduce the dimensionality before the deep learning stage for inferring the medical condition. The performance was validated through 10-fold cross-validation and yielded an average accuracy and sensitivity of 90.23 % and 72.41 %, respectively. The accuracy of discriminating between murmurs' absence and presence reached 76.10 % when evaluated on unseen data. The model had accuracies of 70 %, 88 %, and 86 % in predicting murmur presence in infants, children, and adolescents, respectively. The interpretation of the model revealed proper discrimination between the learned attributes, and AV channel was found important (score 0.75) for the murmur absence predictions while MV and TV were more important for murmur presence predictions. The findings potentiate deep learning as a powerful front-line tool for inferring CHD status in PCG recordings leveraging early detection of heart anomalies in young people. It is suggested as a tool that can be used independently from high-cost machinery or expert assessment.
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Huerne K, Eisenberg MJ. Advancing telemedicine in cardiology: A comprehensive review of evolving practices and outcomes in a postpandemic context. CARDIOVASCULAR DIGITAL HEALTH JOURNAL 2024; 5:96-110. [PMID: 38765624 PMCID: PMC11096655 DOI: 10.1016/j.cvdhj.2024.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024] Open
Abstract
Telemedicine, telehealth, e-Health, and other related terms refer to the exchange of medical information or medical care from one site to another through electronic communication between a patient and a health care provider. As telemedicine infrastructure has changed since the coronavirus disease 2019 (COVID-19) pandemic, this review provides an overview of telemedicine use and effectiveness in cardiology, with emphasis on coronary artery disease in the postpandemic context. Prepandemic studies tend to report statistically insignificant or modest improvements in cardiovascular disease outcome from telemedicine use to usual care. In contrast, postpandemic studies tend to report positive outcomes or comparable acceptance of telemedicine use to usual care. Today, telemedicine can effectively replace in person follow-up visits to produce comparable (but not necessarily superior) outcomes in cardiovascular disease management. A benefit of telemedicine is the potential reduction in follow-up time or time to intervention, which may lead to earlier detection and prevention of adverse events. Nonetheless, barriers remain to effective telemedicine implementation in the postpandemic context. Ensuring accessible and user-friendly telemedicine devices, maintaining adherence to remote rehabilitation procedures, and normalizing use of telemedicine in routine follow-up visits are examples. Current knowledge gaps include the true economic cost of telemedicine infrastructure, feasibility of use in specific cardiology contexts, and sex/gender differences in telemedicine use. Future telemedicine developments will need to address these concerns before acceptance of telemedicine as the new standard of care.
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Affiliation(s)
- Katherine Huerne
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Mark J. Eisenberg
- Departments of Medicine and of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
- Division of Cardiology, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
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Victor OA, Chen Y, Ding X. Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms. SENSORS (BASEL, SWITZERLAND) 2024; 24:2248. [PMID: 38610459 PMCID: PMC11014006 DOI: 10.3390/s24072248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 04/14/2024]
Abstract
Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive signals, specifically integrating photoplethysmogram (PPG) and electrocardiogram (ECG), for enhancing early detection and diagnosis of heart failure. Leveraging a dataset from the MIMIC-III database, encompassing 682 heart failure patients and 954 controls, our approach focuses on continuous, non-invasive monitoring. Key features, including the QRS interval, RR interval, augmentation index, heart rate, systolic pressure, diastolic pressure, and peak-to-peak amplitude, were carefully selected for their clinical relevance and ability to capture cardiovascular dynamics. This feature selection not only highlighted important physiological indicators but also helped reduce computational complexity and the risk of overfitting in machine learning models. The use of these features in training machine learning algorithms led to a model with impressive accuracy (98%), sensitivity (97.60%), specificity (96.90%), and precision (97.20%). Our integrated approach, combining PPG and ECG signals, demonstrates superior performance compared to single-signal strategies, emphasizing its potential in early and precise heart failure diagnosis. The study also highlights the importance of continuous monitoring with wearable technology, suggesting a significant stride forward in non-invasive cardiovascular health assessment. The proposed approach holds promise for implementation in hardware systems to enable continuous monitoring, aiding in early detection and prevention of critical health conditions.
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Affiliation(s)
| | | | - Xiaorong Ding
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (O.A.V.); (Y.C.)
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Ikeda T, Komiyama H, Miyakuni T, Takano M, Asai K. Exploring Possible Links: Thigh Muscle Mass, Apolipoproteins, and Glucose Metabolism in Peripheral Artery Disease-Insights from a Pilot Sub-Study following Endovascular Treatment. Metabolites 2024; 14:192. [PMID: 38668320 PMCID: PMC11052193 DOI: 10.3390/metabo14040192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/24/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024] Open
Abstract
Peripheral artery disease (PAD) compromises walking and physical activity, which results in further loss of skeletal muscle. The cross-sectional area of the thigh muscle has been shown to be correlated with systemic skeletal muscle volume. In our previous pilot study, we observed an increase in thigh muscle mass following endovascular treatment (EVT) in patients with proximal vascular lesions affecting the aortoiliac and femoropopliteal arteries. Considering the potential interactions between skeletal muscle, lipid profile, and glucose metabolism, we aimed to investigate the relationship between thigh muscle mass and apolipoproteins as well as glucose metabolism in PAD patients undergoing EVT. This study is a prespecified sub-study conducted as part of a pilot study. We prospectively enrolled 22 symptomatic patients with peripheral artery disease (PAD) and above-the-knee lesions, specifically involving the blood vessels supplying the thigh muscle. The mid-thigh muscle area was measured with computed tomography before and 6 months after undergoing EVT. Concurrently, we measured levels of apolipoproteins A1 (Apo A1) and B (Apo B), fasting blood glucose, 2 h post-load blood glucose (using a 75 g oral glucose tolerance test), and glycated hemoglobin A1c (HbA1c). Changes in thigh muscle area (delta muscle area: 2.5 ± 8.1 cm2) did not show significant correlations with changes in Apo A1, Apo B, fasting glucose, 2 h post-oral glucose tolerance test blood glucose, HbA1c, or Rutherford classification. However, among patients who experienced an increase in thigh muscle area following EVT (delta muscle area: 8.41 ± 5.93 cm2), there was a significant increase in Apo A1 (pre: 121.8 ± 15.1 mg/dL, 6 months: 136.5 ± 19.5 mg/dL, p < 0.001), while Apo B remained unchanged (pre: 76.4 ± 19.2 mg/dL, 6 months: 80.5 ± 4.9 mg/dL). Additionally, post-oral glucose tolerance test 2 h blood glucose levels showed a decrease (pre: 189.7 ± 67.5 mg/dL, 6 months: 170.6 ± 69.7 mg/dL, p = 0.075). Patients who exhibited an increase in thigh muscle area demonstrated more favorable metabolic changes compared to those with a decrease in thigh muscle area (delta muscle area: -4.67 ± 2.41 cm2). This pilot sub-study provides insights into the effects of EVT on thigh muscle, apolipoproteins, and glucose metabolism in patients with PAD and above-the-knee lesions. Further studies are warranted to validate these findings and establish their clinical significance. The trial was registered on the University Hospital Medical Information Network Clinical Trials Registry (UMIN000047534).
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Affiliation(s)
- Takeshi Ikeda
- Cardiovascular Medicine, Nippon Medical School, Tokyo 113-8603, Japan; (T.I.); (K.A.)
| | - Hidenori Komiyama
- Cardiovascular Medicine, Saitama Medical Center, Saitama Medical University, Saitama 350-8550, Japan
| | - Tomoyo Miyakuni
- Cardiovascular Medicine, Nippon Medical School Chiba Hokusoh Hospital, Chiba 270-1613, Japan; (T.M.)
| | - Masamichi Takano
- Cardiovascular Medicine, Nippon Medical School Chiba Hokusoh Hospital, Chiba 270-1613, Japan; (T.M.)
| | - Kuniya Asai
- Cardiovascular Medicine, Nippon Medical School, Tokyo 113-8603, Japan; (T.I.); (K.A.)
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Palermi S, Vecchiato M, Saglietto A, Niederseer D, Oxborough D, Ortega-Martorell S, Olier I, Castelletti S, Baggish A, Maffessanti F, Biffi A, D'Andrea A, Zorzi A, Cavarretta E, D'Ascenzi F. Unlocking the potential of artificial intelligence in sports cardiology: does it have a role in evaluating athlete's heart? Eur J Prev Cardiol 2024; 31:470-482. [PMID: 38198776 DOI: 10.1093/eurjpc/zwae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 01/01/2024] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
The integration of artificial intelligence (AI) technologies is evolving in different fields of cardiology and in particular in sports cardiology. Artificial intelligence offers significant opportunities to enhance risk assessment, diagnosis, treatment planning, and monitoring of athletes. This article explores the application of AI in various aspects of sports cardiology, including imaging techniques, genetic testing, and wearable devices. The use of machine learning and deep neural networks enables improved analysis and interpretation of complex datasets. However, ethical and legal dilemmas must be addressed, including informed consent, algorithmic fairness, data privacy, and intellectual property issues. The integration of AI technologies should complement the expertise of physicians, allowing for a balanced approach that optimizes patient care and outcomes. Ongoing research and collaborations are vital to harness the full potential of AI in sports cardiology and advance our management of cardiovascular health in athletes.
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Affiliation(s)
- Stefano Palermi
- Public Health Department, University of Naples Federico II, via Pansini 5, 80131 Naples, Italy
| | - Marco Vecchiato
- Sports and Exercise Medicine Division, Department of Medicine, University of Padova, 35128 Padova, Italy
| | - Andrea Saglietto
- Division of Cardiology, Cardiovascular and Thoracic Department, 'Citta della Salute e della Scienza' Hospital, 10129 Turin, Italy
- Department of Medical Sciences, University of Turin, 10129 Turin, Italy
| | - David Niederseer
- Department of Cardiology, University Heart Center Zurich, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland
| | - David Oxborough
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UK
| | - Sandra Ortega-Martorell
- Data Science Research Centre, Liverpool John Moores University, Liverpool, UK
- Liverpool Centre for Cardiovascular Science, Liverpool John Moores University, Liverpool, UK
| | - Ivan Olier
- Data Science Research Centre, Liverpool John Moores University, Liverpool, UK
- Liverpool Centre for Cardiovascular Science, Liverpool John Moores University, Liverpool, UK
| | - Silvia Castelletti
- Cardiology Department, Istituto Auxologico Italiano IRCCS, 20149 Milan, Italy
| | - Aaron Baggish
- Cardiovascular Performance Program, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Alessandro Biffi
- Med-Ex, Medicine & Exercise, Medical Partner Scuderia Ferrari, 00187 Rome, Italy
| | - Antonello D'Andrea
- Department of Cardiology, Umberto I Hospital, 84014 Nocera Inferiore, Italy
| | - Alessandro Zorzi
- Department of Cardiac, Thoracic and Vascular Sciences and Public Health, University of Padova, 35128 Padova, Italy
| | - Elena Cavarretta
- Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University of Rome, 04100 Latina, Italy
- Mediterranea Cardiocentro, 80122 Naples, Italy
| | - Flavio D'Ascenzi
- Department of Medical Biotechnologies, Division of Cardiology, University of Siena, 53100 Siena, Italy
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Messinis S, Temenos N, Protonotarios NE, Rallis I, Kalogeras D, Doulamis N. Enhancing Internet of Medical Things security with artificial intelligence: A comprehensive review. Comput Biol Med 2024; 170:108036. [PMID: 38295478 DOI: 10.1016/j.compbiomed.2024.108036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/08/2024] [Accepted: 01/26/2024] [Indexed: 02/02/2024]
Abstract
Over the past five years, interest in the literature regarding the security of the Internet of Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT devices, their susceptibility to cyber-attacks has proportionally escalated. Motivated by the promising potential of AI-related technologies to improve certain cybersecurity measures, we present a comprehensive review of this emerging field. In this review, we attempt to bridge the corresponding literature gap regarding modern cybersecurity technologies that deploy AI techniques to improve their performance and compensate for security and privacy vulnerabilities. In this direction, we have systematically gathered and classified the extensive research on this topic. Our findings highlight the fact that the integration of machine learning (ML) and deep learning (DL) techniques improves both the performance of cybersecurity measures and their speed, reliability, and effectiveness. This may be proven to be useful for improving the security and privacy of IoMT devices. Furthermore, by considering the numerous advantages of AI technologies as opposed to their core cybersecurity counterparts, including blockchain, anomaly detection, homomorphic encryption, differential privacy, federated learning, and so on, we provide a structured overview of the current scientific trends. We conclude with considerations for future research, emphasizing the promising potential of AI-driven cybersecurity in the IoMT landscape, especially in patient data protection and in data-driven healthcare.
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Affiliation(s)
- Sotirios Messinis
- Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, 15780, Greece.
| | - Nikos Temenos
- School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, Athens, 15780, Greece.
| | | | - Ioannis Rallis
- School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, Athens, 15780, Greece.
| | - Dimitrios Kalogeras
- Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, 15780, Greece.
| | - Nikolaos Doulamis
- School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, Athens, 15780, Greece.
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40
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Lang X, Zhu Z, Qian Y, Artola Arita V, Zeng T. Shortening delays in seeking aid for cardiovascular events: a step beyond. THE LANCET REGIONAL HEALTH. SOUTHEAST ASIA 2024; 22:100369. [PMID: 38450311 PMCID: PMC10915780 DOI: 10.1016/j.lansea.2024.100369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/30/2024] [Accepted: 02/05/2024] [Indexed: 03/08/2024]
Affiliation(s)
- Xi Lang
- Deptartment of Nursing, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Hubei Wuhan, 430030, China
- Nursing School, Tongji Medical College, Huazhong University of Science and Technology, Hubei Wuhan, 430030, China
| | - Zining Zhu
- Deptartment of Nursing, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Hubei Wuhan, 430030, China
- Nursing School, Tongji Medical College, Huazhong University of Science and Technology, Hubei Wuhan, 430030, China
| | - Yinqi Qian
- Nursing School, Tongji Medical College, Huazhong University of Science and Technology, Hubei Wuhan, 430030, China
| | - Vicente Artola Arita
- Department of Global Public Health and Bioethics, Julius Center, University Medical Center (UMC) Utrecht, Utrecht, the Netherlands
| | - Tieying Zeng
- Deptartment of Nursing, Tongji Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Hubei Wuhan, 430030, China
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He T, Cui W, Feng Y, Li X, Yu G. Digital health integration for noncommunicable diseases: Comprehensive process mapping for full-life-cycle management. J Evid Based Med 2024; 17:26-36. [PMID: 38361398 DOI: 10.1111/jebm.12583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 01/05/2024] [Indexed: 02/17/2024]
Abstract
AIM To create a systematic digital health process mapping framework for full-life-cycle noncommunicable disease management grounded in key stakeholder engagement. METHODS A triphasic, qualitative methodology was employed to construct a process mapping framework for digital noncommunicable disease management in Shanghai, China. The first phase involved desk research to examine current guidance and practices. In the second phase, pivotal stakeholders participated in focus group discussions to identify prevalent digital touchpoints across lifetime noncommunicable disease management. In the final phase, the Delphi technique was used to refine the framework based on expert insights and obtain consensus. RESULTS We identified 60 digital touchpoints across five essential stages of full-life-cycle noncommunicable disease management. Most experts acknowledged the rationality and feasibility of these touchpoints. CONCLUSIONS This study led to the creation of a comprehensive digital health process mapping framework that encompasses the entire life cycle of noncommunicable disease management. The insights gained emphasize the importance of a systemic strategic, person-centered approach over a fragmented, purely technocentric approach. We recommend that healthcare professionals use this framework as a linchpin for efficient disease management and seamless technology incorporation in clinical practice.
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Affiliation(s)
- Tianrui He
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenbin Cui
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Children's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuxuan Feng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xingyi Li
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guangjun Yu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Children's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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42
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Irrera F, Gumiero A, Zampogna A, Boscari F, Avogaro A, Gazzanti Pugliese di Cotrone MA, Patera M, Della Torre L, Picozzi N, Suppa A. Multisensor Integrated Platform Based on MEMS Charge Variation Sensing Technology for Biopotential Acquisition. SENSORS (BASEL, SWITZERLAND) 2024; 24:1554. [PMID: 38475089 DOI: 10.3390/s24051554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/25/2024] [Accepted: 02/26/2024] [Indexed: 03/14/2024]
Abstract
We propose a new methodology for long-term biopotential recording based on an MEMS multisensor integrated platform featuring a commercial electrostatic charge-transfer sensor. This family of sensors was originally intended for presence tracking in the automotive industry, so the existing setup was engineered for the acquisition of electrocardiograms, electroencephalograms, electrooculograms, and electromyography, designing a dedicated front-end and writing proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in a domestic environment will be discussed in detail. The excellent results indicate that this technology can provide a low-power, unexplored solution to biopotential acquisition. The technological breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, it opens up additional possibilities for wearable sensors and strengthens the role of MEMS technology in medical wearables for the long-term synchronous acquisition of a wide range of signals.
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Affiliation(s)
- Fernanda Irrera
- Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, 00185 Rome, Italy
| | | | - Alessandro Zampogna
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | | | - Angelo Avogaro
- Department of Medicine, University of Padua, 35122 Padua, Italy
| | | | - Martina Patera
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | | | | | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- IRCCS Neuromed, 86077 Pozzilli, Italy
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43
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Allinson F, Mejia N, Ariniello L, Quer G, Muse ED. A pilot study exploring novel contexts for out-of-office blood pressure measurement. Front Cardiovasc Med 2024; 11:1351746. [PMID: 38464843 PMCID: PMC10920340 DOI: 10.3389/fcvm.2024.1351746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 02/02/2024] [Indexed: 03/12/2024] Open
Abstract
Introduction Out-of-office blood pressure (BP) monitoring is increasingly valuable in the diagnosis and management of hypertension. With advances in wearable BP technologies, the ability to gain insight into BP outside of traditional centers of care has expanded greatly. Methods Here we explore the usability of a novel, wrist-worn BP cuff monitor for out-of-office data collection with participants following digital cues rather than in-person instruction. Transmitted measurements were used to evaluate BP variation with the time of day and day of week, BP variation with mood, and orthostatic measurements. Results Fifty participants, with a mean age of 44.5 years, were enrolled and received the BP monitor. 82% of the participants transmitted data via the smartphone application, and the median wear time of the device during the 4-week study was 11 days (IQR 8-17). Discussion This prospective digital pilot study illustrates the usability of wearable oscillometric BP technology combined with digital cues via a smartphone application to obtain complex out-of-office BP measurements, including orthostatic vital signs and BP associated with emotion. 25 out of 32 participants who attempted orthostatic vital signs based on in-app instruction were able to do so correctly, while 24 participants transmitted BP readings associated with emotion, with a significant difference in BP noted between calm and stressed emotional states.
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Affiliation(s)
- Francis Allinson
- Division of Cardiovascular Disease, Scripps Clinic, La Jolla, CA, United States
| | - Nolan Mejia
- Scripps Research Translational Institute, La Jolla, CA, United States
| | - Lauren Ariniello
- Scripps Research Translational Institute, La Jolla, CA, United States
| | - Giorgio Quer
- Scripps Research Translational Institute, La Jolla, CA, United States
| | - Evan D. Muse
- Division of Cardiovascular Disease, Scripps Clinic, La Jolla, CA, United States
- Scripps Research Translational Institute, La Jolla, CA, United States
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44
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Dahiya ES, Kalra AM, Lowe A, Anand G. Wearable Technology for Monitoring Electrocardiograms (ECGs) in Adults: A Scoping Review. SENSORS (BASEL, SWITZERLAND) 2024; 24:1318. [PMID: 38400474 PMCID: PMC10893166 DOI: 10.3390/s24041318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/07/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024]
Abstract
In the rapidly evolving landscape of continuous electrocardiogram (ECG) monitoring systems, there is a heightened demand for non-invasive sensors capable of measuring ECGs and detecting heart rate variability (HRV) in diverse populations, ranging from cardiovascular patients to sports enthusiasts. Challenges like device accuracy, patient privacy, signal noise, and long-term safety impede the use of wearable devices in clinical practice. This scoping review aims to assess the performance and safety of novel multi-channel, sensor-based biopotential wearable devices in adults. A comprehensive search strategy was employed on four databases, resulting in 143 records and the inclusion of 12 relevant studies. Most studies focused on healthy adult subjects (n = 6), with some examining controlled groups with atrial fibrillation (AF) (n = 3), long QT syndrome (n = 1), and sleep apnea (n = 1). The investigated bio-sensor devices included chest-worn belts (n = 2), wrist bands (n = 2), adhesive chest strips (n = 2), and wearable textile smart clothes (n = 4). The primary objective of the included studies was to evaluate device performance in terms of accuracy, signal quality, comparability, and visual assessment of ECGs. Safety findings, reported in five articles, indicated no major side effects for long-term/continuous monitoring, with only minor instances of skin irritation. Looking forward, there are ample opportunities to enhance and test these technologies across various physical activity intensities and clinical conditions.
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Affiliation(s)
| | - Anubha Manju Kalra
- Institute of Biomedical Technologies (IBTec), Auckland University of Technology, Auckland 1010, New Zealand; (E.S.D.); (A.L.); (G.A.)
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Straiton N, Moons P, Verstrael A, Liu M, Winter MM. Beyond Validation: Getting Wearable Activity Trackers into Cardiovascular Care - A Discussion Paper. Eur J Cardiovasc Nurs 2024:zvae019. [PMID: 38345842 DOI: 10.1093/eurjcn/zvae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 02/06/2024] [Accepted: 02/08/2024] [Indexed: 04/24/2024]
Abstract
This paper addresses the challenge of integrating wearable activity trackers into cardiovascular disease care. Despite evidence supporting the use of trackers for monitoring and promoting physical activity, implementation challenges persist in clinical settings. The paper emphasises the lack of systematic, evidence-based implementation approaches for integrating trackers. It underscores the urgent need for stakeholder collaboration between clinicians, patients, implementation scientists, researchers, health and technology partners, and the use of proven implementation science methodologies. This is crucial for bridging the gap and ensuring effective translation of wearable activity trackers into cardiovascular disease care, meeting the increasing demand from patients and clinicians.
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Affiliation(s)
- Nicola Straiton
- Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne, Australian Catholic University, New South Wales, Australia
| | - Philip Moons
- KU Leuven Department of Public Health and Primary Care, KU Leuven - University of Leuven, Kapucijnenvoer 7 PB7001, 3000 Leuven, Belgium
- Institute of Health and Care Sciences, University of Gothenburg, Arvid Wallgrens backe 1, 413 46 Gothenburg, Sweden
- Department of Paediatrics and Child Health, University of Cape Town, Klipfontein Rd, Rondebosch, 7700 Cape Town, South Africa
| | - Axel Verstrael
- ESC Patient's Platform, European Society of Cardiology, Sophia Antipolis Cedex, France
| | - Mark Liu
- Nursing Research Institute, St Vincent's Health Network Sydney, St Vincent's Hospital Melbourne, Australian Catholic University, New South Wales, Australia
- Faculty of Medicine and Health, University of Sydney
| | - Michiel M Winter
- University of Amsterdam, Heart Center; Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, Meibergdreef 9, Amsterdam, The Netherlands
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Zhan J, Wu X, Fu X, Li C, Deng KQ, Wei Q, Zhang C, Zhao T, Li C, Huang L, Chen K, Wang Q, Li Z, Lu Z. Non-contact assessment of cardiac physiology using FO-MVSS-based ballistocardiography: a promising approach for heart failure evaluation. Sci Rep 2024; 14:3269. [PMID: 38332169 PMCID: PMC10853251 DOI: 10.1038/s41598-024-53464-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 01/31/2024] [Indexed: 02/10/2024] Open
Abstract
Continuous monitoring of cardiac motions has been expected to provide essential cardiac physiology information on cardiovascular functioning. A fiber-optic micro-vibration sensing system (FO-MVSS) makes it promising. This study aimed to explore the correlation between Ballistocardiography (BCG) waveforms, measured using an FO-MVSS, and myocardial valve activity during the systolic and diastolic phases of the cardiac cycle in participants with normal cardiac function and patients with congestive heart failure (CHF). A high-sensitivity FO-MVSS acquired continuous BCG recordings. The simultaneous recordings of BCG and electrocardiogram (ECG) signals were obtained from 101 participants to examine their correlation. BCG, ECG, and intracavitary pressure signals were collected from 6 patients undergoing cardiac catheter intervention to investigate BCG waveforms and cardiac cycle phases. Tissue Doppler imaging (TDI) measured cardiac time intervals in 51 participants correlated with BCG intervals. The BCG recordings were further validated in 61 CHF patients to assess cardiac parameters by BCG. For heart failure evaluation machine learning was used to analyze BCG-derived cardiac parameters. Significant correlations were observed between cardiac physiology parameters and BCG's parameters. Furthermore, a linear relationship was found betwen IJ amplitude and cardiac output (r = 0.923, R2 = 0.926, p < 0.001). Machine learning techniques, including K-Nearest Neighbors (KNN), Decision Tree Classifier (DTC), Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and XGBoost, respectively, demonstrated remarkable performance. They all achieved average accuracy and AUC values exceeding 95% in a five-fold cross-validation approach. We establish an electromagnetic-interference-free and non-contact method for continuous monitoring of the cardiac cycle and myocardial contractility and measure the different phases of the cardiac cycle. It presents a sensitive method for evaluating changes in both cardiac contraction and relaxation in the context of heart failure assessment.
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Affiliation(s)
- Jing Zhan
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Xiaoyan Wu
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
- Institute of Myocardial Injury and Repair, Wuhan University, Wuhan, 430071, Hubei, China
| | - Xuelei Fu
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Chenze Li
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
- Institute of Myocardial Injury and Repair, Wuhan University, Wuhan, 430071, Hubei, China
| | - Ke-Qiong Deng
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
- Institute of Myocardial Injury and Repair, Wuhan University, Wuhan, 430071, Hubei, China
| | - Qin Wei
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Chao Zhang
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
- Institute of Myocardial Injury and Repair, Wuhan University, Wuhan, 430071, Hubei, China
| | - Tao Zhao
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Congcong Li
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Longting Huang
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Kewei Chen
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China
| | - Qiongxin Wang
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
- Institute of Myocardial Injury and Repair, Wuhan University, Wuhan, 430071, Hubei, China
| | - Zhengying Li
- Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, Hubei, China.
- National Engineering Research Center of Optical Fiber Sensing Technology and Networks, Wuhan University of Technology, Wuhan, 430070, Hubei, China.
- State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan, 430070, Hubei, China.
- State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, 430070, Hubei, China.
| | - Zhibing Lu
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China.
- Institute of Myocardial Injury and Repair, Wuhan University, Wuhan, 430071, Hubei, China.
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Ichihara YK, Kohsaka S, Kisanuki M, Sandhu ATS, Kawana M. Implementation of evidence-based heart failure management: Regional variations between Japan and the USA. J Cardiol 2024; 83:74-83. [PMID: 37543194 DOI: 10.1016/j.jjcc.2023.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/26/2023] [Accepted: 07/28/2023] [Indexed: 08/07/2023]
Abstract
The implementation of optimal medical therapy is a crucial step in the management of heart failure with reduced ejection fraction (HFrEF). Over the prior three decades, there have been substantial advancements in this field. Early and accurate detection and diagnosis of the disease allow for the appropriate initiation of optimal therapies. The initiation and uptitration of optimal medical therapy including renin-angiotensin system inhibitor, beta-blocker, mineralocorticoid receptor antagonist, and sodium-glucose cotransporter 2 inhibitor in the early stage would prevent the progression and morbidity of HF. Concurrently, individualized surveillance to recognize and treat signs of disease progression is critical given the progressive nature of HF, even among stable patients on optimal therapy. However, there remains a wide variation in regional practice regarding the initiation, titration, and long-term monitoring of this therapy. To cover the differences in approaches toward HFrEF management and the implementation of guideline-based medical therapy, we discuss the current evidence in this arena, differences in present guideline recommendations, and compare practice patterns in Japan and the USA using a case of new-onset HF as an example. We will discuss pros and cons of the way HF is managed in each region, and highlight potential areas for improvement in care.
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Affiliation(s)
| | - Shun Kohsaka
- Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
| | - Megumi Kisanuki
- Department of Medicine and Biosystemic Sciences, Kyushu University Graduate School of Medicine, Fukuoka, Japan
| | | | - Masataka Kawana
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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Babu M, Lautman Z, Lin X, Sobota MHB, Snyder MP. Wearable Devices: Implications for Precision Medicine and the Future of Health Care. Annu Rev Med 2024; 75:401-415. [PMID: 37983384 DOI: 10.1146/annurev-med-052422-020437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Wearable devices are integrated analytical units equipped with sensitive physical, chemical, and biological sensors capable of noninvasive and continuous monitoring of vital physiological parameters. Recent advances in disciplines including electronics, computation, and material science have resulted in affordable and highly sensitive wearable devices that are routinely used for tracking and managing health and well-being. Combined with longitudinal monitoring of physiological parameters, wearables are poised to transform the early detection, diagnosis, and treatment/management of a range of clinical conditions. Smartwatches are the most commonly used wearable devices and have already demonstrated valuable biomedical potential in detecting clinical conditions such as arrhythmias, Lyme disease, inflammation, and, more recently, COVID-19 infection. Despite significant clinical promise shown in research settings, there remain major hurdles in translating the medical uses of wearables to the clinic. There is a clear need for more effective collaboration among stakeholders, including users, data scientists, clinicians, payers, and governments, to improve device security, user privacy, data standardization, regulatory approval, and clinical validity. This review examines the potential of wearables to offer affordable and reliable measures of physiological status that are on par with FDA-approved specialized medical devices. We briefly examine studies where wearables proved critical for the early detection of acute and chronic clinical conditions with a particular focus on cardiovascular disease, viral infections, and mental health. Finally, we discuss current obstacles to the clinical implementation of wearables and provide perspectives on their potential to deliver increasingly personalized proactive health care across a wide variety of conditions.
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Affiliation(s)
- Mohan Babu
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
| | - Ziv Lautman
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
- Department of Bioengineering, Stanford University School of Medicine, Stanford, California, USA
| | - Xiangping Lin
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
| | - Milan H B Sobota
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA;
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49
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Spatz ES, Ginsburg GS, Rumsfeld JS, Turakhia MP. Wearable Digital Health Technologies for Monitoring in Cardiovascular Medicine. N Engl J Med 2024; 390:346-356. [PMID: 38265646 DOI: 10.1056/nejmra2301903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Affiliation(s)
- Erica S Spatz
- From the Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT (E.S.S.); the National Institutes of Health, Bethesda, MD (G.S.G.); the University of Colorado School of Medicine, Aurora (J.S.R.); and Meta Platforms, Menlo Park (J.S.R.), the Stanford Center for Digital Health, Stanford University School of Medicine, Stanford (M.P.T.), and iRhythm Technologies, San Francisco (M.P.T.) - all in California
| | - Geoffrey S Ginsburg
- From the Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT (E.S.S.); the National Institutes of Health, Bethesda, MD (G.S.G.); the University of Colorado School of Medicine, Aurora (J.S.R.); and Meta Platforms, Menlo Park (J.S.R.), the Stanford Center for Digital Health, Stanford University School of Medicine, Stanford (M.P.T.), and iRhythm Technologies, San Francisco (M.P.T.) - all in California
| | - John S Rumsfeld
- From the Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT (E.S.S.); the National Institutes of Health, Bethesda, MD (G.S.G.); the University of Colorado School of Medicine, Aurora (J.S.R.); and Meta Platforms, Menlo Park (J.S.R.), the Stanford Center for Digital Health, Stanford University School of Medicine, Stanford (M.P.T.), and iRhythm Technologies, San Francisco (M.P.T.) - all in California
| | - Mintu P Turakhia
- From the Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT (E.S.S.); the National Institutes of Health, Bethesda, MD (G.S.G.); the University of Colorado School of Medicine, Aurora (J.S.R.); and Meta Platforms, Menlo Park (J.S.R.), the Stanford Center for Digital Health, Stanford University School of Medicine, Stanford (M.P.T.), and iRhythm Technologies, San Francisco (M.P.T.) - all in California
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Kim H, Lee J, Heo U, Jayashankar DK, Agno KC, Kim Y, Kim CY, Oh Y, Byun SH, Choi B, Jeong H, Yeo WH, Li Z, Park S, Xiao J, Kim J, Jeong JW. Skin preparation-free, stretchable microneedle adhesive patches for reliable electrophysiological sensing and exoskeleton robot control. SCIENCE ADVANCES 2024; 10:eadk5260. [PMID: 38232166 DOI: 10.1126/sciadv.adk5260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/18/2023] [Indexed: 01/19/2024]
Abstract
High-fidelity and comfortable recording of electrophysiological (EP) signals with on-the-fly setup is essential for health care and human-machine interfaces (HMIs). Microneedle electrodes allow direct access to the epidermis and eliminate time-consuming skin preparation. However, existing microneedle electrodes lack elasticity and reliability required for robust skin interfacing, thereby making long-term, high-quality EP sensing challenging during body movement. Here, we introduce a stretchable microneedle adhesive patch (SNAP) providing excellent skin penetrability and a robust electromechanical skin interface for prolonged and reliable EP monitoring under varying skin conditions. Results demonstrate that the SNAP can substantially reduce skin contact impedance under skin contamination and enhance wearing comfort during motion, outperforming gel and flexible microneedle electrodes. Our wireless SNAP demonstration for exoskeleton robot control shows its potential for highly reliable HMIs, even under time-dynamic skin conditions. We envision that the SNAP will open new opportunities for wearable EP sensing and its real-world applications in HMIs.
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Affiliation(s)
- Heesoo Kim
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Juhyun Lee
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Ung Heo
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | | | - Karen-Christian Agno
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Yeji Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Choong Yeon Kim
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Youngjun Oh
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Sang-Hyuk Byun
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Bohyung Choi
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Hwayeong Jeong
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Woon-Hong Yeo
- IEN Center for Wearable Intelligent Systems and Healthcare at the Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, GA 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Institute for Materials, Neural Engineering Center, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Zhuo Li
- Department of Material Science, Fudan University, Shanghai 200433, China
| | - Seongjun Park
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Jianliang Xiao
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Jung Kim
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Jae-Woong Jeong
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon 34141, Republic of Korea
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