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Sesma-Sánchez L, Ruiz-Castellano M, Romero-Roldán A, Álvarez-García L, Morrás-Gómez M, Tabar-Liberal I, Pulido-Fontes M, Salmón-García B. Continuous Temperature Telemonitoring of Patients with COVID-19 and Other Infectious Diseases Treated in Hospital-at-Home: Viture ® System Validation. SENSORS (BASEL, SWITZERLAND) 2024; 24:5027. [PMID: 39124073 PMCID: PMC11314737 DOI: 10.3390/s24155027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/17/2024] [Accepted: 07/20/2024] [Indexed: 08/12/2024]
Abstract
Body temperature must be monitored in patients receiving Hospital-at-Home (HaH) care for COVID-19 and other infectious diseases. Continuous temperature telemonitoring (CTT) detects fever and patient deterioration early, facilitating decision-making. We performed a validation clinical study assessing the safety, comfort, and impact on healthcare practice of Viture®, a CTT system, compared with a standard digital axillary thermometer in 208 patients with COVID-19 and other infectious diseases treated in HaH at the Navarra University Hospital (HUN). Overall, 3258 pairs of measurements showed a clinical bias of -0.02 °C with limits of agreement of -0.96/+0.92 °C, a 95% acceptance rate, and a mean absolute deviation of 0.36 (SD 0.30) °C. Viture® detected 3 times more febrile episodes and revealed fever in 50% more patients compared with spot measurements. Febrile episodes were detected 7.23 h (mean) earlier and modified the diagnostic and/or therapeutic approach in 43.2% of patients. Viture® was validated for use in a clinical setting and was more effective in detecting febrile episodes than conventional methods.
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Affiliation(s)
| | - María Ruiz-Castellano
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | | | - Laura Álvarez-García
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Marta Morrás-Gómez
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Idoia Tabar-Liberal
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Marta Pulido-Fontes
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Belén Salmón-García
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
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Hayavi-haghighi MH, Gharibzade A, Choobin N, Ansarifard H. Applications and outcomes of implementing telemedicine for hypertension management in COVID-19 pandemic: A systematic review. PLoS One 2024; 19:e0306347. [PMID: 39088489 PMCID: PMC11293715 DOI: 10.1371/journal.pone.0306347] [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: 03/28/2024] [Accepted: 06/13/2024] [Indexed: 08/03/2024] Open
Abstract
INTRODUCTION COVID-19 presented a significant challenge for patients with hypertension in terms of access to care. However, telemedicine offered the healthcare system opportunities that had previously been underutilized. Therefore, this study aims to systematically review the applications and outcomes of telemedicine for hypertension management during the COVID-19 pandemic. METHOD A structured search was conducted in accordance with PRISMA guidelines across multiple databases, including PubMed, Cochrane, Web of Science, and Scopus. The search was limited to studies published from December 2019 until May 2023, resulting in a total of 3727 studies. After quality appraisal using the CASP checklists version 2018, 29 articles were included in the final review. Data analysis was performed using thematic analysis. RESULTS Most of the studies reviewed had used the proprietary platforms (N = 14) and 11 studies had used public platforms such as social messengers or email. Also 9 studies relied on phone calls (N = 9) to record and transmit the clinical data. Some studies had applied two different approaches (proprietary/public platforms and phone). six articles (20.7%) focused only on hypertension control, while 23 articles (79.3%) examined hypertension as a comorbidity with other diseases. Also, the study identified 88 unique concepts, 15 initial themes, and six final themes for outcomes of using telemedicine for hypertension management during the COVID-19 pandemic. These themes include BP control, BP measurement and recording, medication management, mental health, care continuity and use and acceptance. CONCLUSION Telemedicine provides patients with hypertension with the opportunity to engage in medical consultations in a more convenient and comfortable manner, with the same validity as in-person visits. Telemedicine facilitates the creation of a connected network to support patients with high BP at any time and in any location. Limitations and issues may arise due to patients and healthcare staff's unfamiliarity with telemedicine. These issues can be resolved through the ongoing use and continuous feedback.
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Affiliation(s)
- Mohammad Hosein Hayavi-haghighi
- Department of Health Information Technology, School of Allied Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Abdullah Gharibzade
- Department of cardiology, School of medicine, Tobacco and Health Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Niloofar Choobin
- Faculty of Para-medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Haniyeh Ansarifard
- Faculty of Para-medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
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Nunes T, Gaspar L, Faria JN, Portugal D, Lopes T, Fernandes P, Tavakoli M. Deployment and validation of a smart bed architecture for untethered patients with wireless biomonitoring stickers. Med Biol Eng Comput 2024:10.1007/s11517-024-03155-3. [PMID: 39037541 DOI: 10.1007/s11517-024-03155-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 06/10/2024] [Indexed: 07/23/2024]
Abstract
Conventional patient monitoring in healthcare has limitations such as delayed identification of deteriorating conditions, disruptions to patient routines, and discomfort due to extensive wiring for bed-bound patients. To address these, we have recently developed an innovative IoT-based healthcare system for real-time wireless patient monitoring. This system includes a flexible epidermal patch that collects vital signs using low power electronics and transmits the data to IoT nodes in hospital beds. The nodes connect to a smart gateway that aggregates the information and interfaces with the hospital information system (HIS), facilitating the exchange of electronic health records (EHR) and enhancing access to patient vital signs for healthcare professionals. Our study validates the proposed smart bed architecture in a clinical setting, assessing its ability to meet healthcare personnel needs, patient comfort, and data transmission reliability. Technical performance assessment involves analyzing key performance indicators for communication across various interfaces, including the wearable device and the smart box, and the link between the gateway and the HIS. Also, a comparative analysis is conducted on data from our architecture and traditional hospital equipment. Usability evaluation involves questionnaires completed by patients and healthcare professionals. Results demonstrate the robustness of the architecture proposed, exhibiting reliable and efficient information flow, while offering significant improvements in patient monitoring over conventional wired methods, including unrestricted mobility and improved comfort to enhance healthcare delivery.
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Affiliation(s)
- Tânia Nunes
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - Luís Gaspar
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - José N Faria
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - David Portugal
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal.
| | - Telmo Lopes
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - Pedro Fernandes
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
| | - Mahmoud Tavakoli
- Institute of Systems and Robotics, University of Coimbra, Coimbra, Portugal
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Khalili M, GholamHosseini H, Lowe A, Kuo MMY. Motion artifacts in capacitive ECG monitoring systems: a review of existing models and reduction techniques. Med Biol Eng Comput 2024:10.1007/s11517-024-03165-1. [PMID: 39031328 DOI: 10.1007/s11517-024-03165-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 06/27/2024] [Indexed: 07/22/2024]
Abstract
Current research focuses on improving electrocardiogram (ECG) monitoring systems to enable real-time and long-term usage, with a specific focus on facilitating remote monitoring of ECG data. This advancement is crucial for improving cardiovascular health by facilitating early detection and management of cardiovascular disease (CVD). To efficiently meet these demands, user-friendly and comfortable ECG sensors that surpass wet electrodes are essential. This has led to increased interest in ECG capacitive electrodes, which facilitate signal detection without requiring gel preparation or direct conductive contact with the body. This feature makes them suitable for wearables or integrated measurement devices. However, ongoing research is essential as the signals they measure often lack sufficient clinical accuracy due to susceptibility to interferences, particularly Motion Artifacts (MAs). While our primary focus is on studying MAs, we also address other limitations crucial for designing a high Signal-to-Noise Ratio (SNR) circuit and effectively mitigating MAs. The literature on the origins and models of MAs in capacitive electrodes is insufficient, which we aim to address alongside discussing mitigation methods. We bring attention to digital signal processing approaches, especially those using reference signals like Electrode-Tissue Impedance (ETI), as highly promising. Finally, we discuss its challenges, proposed solutions, and offer insights into future research directions.
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Affiliation(s)
- Matin Khalili
- Institute of Biomedical Technologies, Auckland University of Technology, 6 St Paul St, Auckland, 1010, New Zealand.
- Department of Electrical and Electronic Engineering, Auckland University of Technology, 6 St Paul St, Auckland, 1010, New Zealand.
| | - Hamid GholamHosseini
- Institute of Biomedical Technologies, Auckland University of Technology, 6 St Paul St, Auckland, 1010, New Zealand
- Department of Electrical and Electronic Engineering, Auckland University of Technology, 6 St Paul St, Auckland, 1010, New Zealand
| | - Andrew Lowe
- Institute of Biomedical Technologies, Auckland University of Technology, 6 St Paul St, Auckland, 1010, New Zealand
| | - Matthew M Y Kuo
- Department of Computer Science and Software Engineering, Auckland University of Technology, 6 St Paul St, Auckland, 1010, New Zealand
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Leoncini S, Boasiako L, Di Lucia S, Beker A, Scandurra V, Vignoli A, Canevini MP, Prato G, Nobili L, Nicotera AG, Di Rosa G, Chiarini MBT, Cutrera R, Grosso S, Lazzeri G, Tongiorgi E, Morano P, Botteghi M, Barducci A, De Felice C. 24-h continuous non-invasive multiparameter home monitoring of vitals in patients with Rett syndrome by an innovative wearable technology: evidence of an overlooked chronic fatigue status. Front Neurol 2024; 15:1388506. [PMID: 38952469 PMCID: PMC11215834 DOI: 10.3389/fneur.2024.1388506] [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: 02/19/2024] [Accepted: 05/13/2024] [Indexed: 07/03/2024] Open
Abstract
Background Sleep is disturbed in Rett syndrome (RTT), a rare and progressive neurodevelopmental disorder primarily affecting female patients (prevalence 7.1/100,000 female patients) linked to pathogenic variations in the X-linked methyl-CpG-binding protein 2 (MECP2) gene. Autonomic nervous system dysfunction with a predominance of the sympathetic nervous system (SNS) over the parasympathetic nervous system (PSNS) is reported in RTT, along with exercise fatigue and increased sudden death risk. The aim of the present study was to test the feasibility of a continuous 24 h non-invasive home monitoring of the biological vitals (biovitals) by an innovative wearable sensor device in pediatric and adolescent/adult RTT patients. Methods A total of 10 female patients (mean age 18.3 ± 9.4 years, range 4.7-35.5 years) with typical RTT and MECP2 pathogenic variations were enrolled. Clinical severity was assessed by validated scales. Heart rate (HR), respiratory rate (RR), and skin temperature (SkT) were monitored by the YouCare Wearable Medical Device (Accyourate Group SpA, L'Aquila, Italy). The average percentage of maximum HR (HRmax%) was calculated. Heart rate variability (HRV) was expressed by consolidated time-domain and frequency-domain parameters. The HR/LF (low frequency) ratio, indicating SNS activation under dynamic exercise, was calculated. Simultaneous continuous measurement of indoor air quality variables was performed and the patients' contributions to the surrounding water vapor partial pressure [PH2O (pt)] and carbon dioxide [PCO2 (pt)] were indirectly estimated. Results Of the 6,559.79 h of biovital recordings, 5051.03 h (77%) were valid for data interpretation. Sleep and wake hours were 9.0 ± 1.1 h and 14.9 ± 1.1 h, respectively. HRmax % [median: 71.86% (interquartile range 61.03-82%)] and HR/LF [median: 3.75 (interquartile range 3.19-5.05)] were elevated, independent from the wake-sleep cycle. The majority of HRV time- and frequency-domain parameters were significantly higher in the pediatric patients (p ≤ 0.031). The HRV HR/LF ratio was associated with phenotype severity, disease progression, clinical sleep disorder, subclinical hypoxia, and electroencephalographic observations of multifocal epileptic activity and general background slowing. Conclusion Our findings indicate the feasibility of a continuous 24-h non-invasive home monitoring of biovital parameters in RTT. Moreover, for the first time, HRmax% and the HR/LF ratio were identified as potential objective markers of fatigue, illness severity, and disease progression.
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Affiliation(s)
- Silvia Leoncini
- Rett Syndrome Trial Center, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
- Neonatal Intensive Care Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
- U.O.S.A. Programmazione e Ricerca Clinica, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Lidia Boasiako
- Rett Syndrome Trial Center, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
- Neonatal Intensive Care Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Sofia Di Lucia
- Neonatal Intensive Care Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | | | - Valeria Scandurra
- Child Neuropsychiatry Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Aglaia Vignoli
- Childhood and Adolescence Neurology and Psychiatry Unit, ASST GOM Niguarda, Milan, Italy
| | - Maria Paola Canevini
- Epilepsy Center – Sleep Medicine Center, Childhood and Adolescence Neuropsychiatry Unit, ASST Santi Paolo e Carlo, San Paolo Hospital, Milan, Italy
| | - Giulia Prato
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, Genova, Italy
| | - Lino Nobili
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health (DINOGMI), University of Genova, Genova, Italy
| | | | - Gabriella Di Rosa
- Child Neuropsychiatry Unit, University Hospital “G. Martino”, Messina, Italy
- Department of Biomedical and Dental Sciences and of Morphological and Functional Imaging (BIOMORF), University of Messina, Messina, Italy
| | - Maria Beatrice Testa Chiarini
- Pneumology and Cystic Fibrosis Unit, Academic Department of Pediatrics, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Renato Cutrera
- Pneumology and Cystic Fibrosis Unit, Academic Department of Pediatrics, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Salvatore Grosso
- Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy
- Pediatrics Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Giacomo Lazzeri
- U.O.S.A. Programmazione e Ricerca Clinica, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
- Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy
| | - Enrico Tongiorgi
- Department of Life Sciences, University of Trieste, Trieste, Italy
| | | | - Matteo Botteghi
- Department of Clinical and Molecular Sciences – Experimental Pathology Research Group, Università Politecnica delle Marche, Ancona, Italy
- Medical Physics Activities Coordination Centre – Alma Mater Studiorum – University of Bologna, Bologna, Italy
| | | | - Claudio De Felice
- Rett Syndrome Trial Center, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
- Neonatal Intensive Care Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
- Pediatrics Unit, University Hospital Azienda Ospedaliera Universitaria Senese, Siena, Italy
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Chand K, Chandra S, Dutt V. A comprehensive evaluation of linear and non-linear HRV parameters between paced breathing and stressful mental state. Heliyon 2024; 10:e32195. [PMID: 38873683 PMCID: PMC11170182 DOI: 10.1016/j.heliyon.2024.e32195] [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: 01/09/2024] [Revised: 05/22/2024] [Accepted: 05/29/2024] [Indexed: 06/15/2024] Open
Abstract
Background Heart rate variability (HRV) is a crucial metric that provides valuable insight into the balance between relaxation and stress. Previous research has shown that most HRV parameters improve during periods of mental relaxation, while decreasing during tasks involving cognitive workload. Although a comprehensive analysis of both linear and non-linear HRV parameters has been carried out in existing literature, there still exists a need for further research in this area. Additionally, limited knowledge exists regarding how specific interventions may influence the interpretation of these parameters and how the different parameters correlate under different interventions. This study aims to address these gaps by conducting a thorough comparison of different linear and non-linear HRV parameters under mentally relaxed versus stressful states. Methodology Participants were randomly and equally divided among two between-subjects groups: relaxed-stress (RS) (N = 22) and stress-relaxed (SR) (N = 22). In the RS group, a paced breathing task was given for 5 min to create relaxation, and was followed by a 5-min time-based mental calculation task to create stress. In the SR group, the order of the stress and relaxed tasks was reversed. There was a washout period of 15 min after the first task in both groups. Results Of the 37 HRV parameters, 33 differed significantly between the two interventions. The majority of the parameters exhibited an improving and degrading tendency of HRV parameters in the relaxed and stressed states, respectively. The correlation of the majority of HRV parameters decreases during stress, while prominent time domain and geometric domain parameters stand out in the correlation. Conclusion Overall, HRV parameters can be reliably used to assess a person's relaxed and stressed mental states during paced breathing and mental arithmetic task respectively. Furthermore, non-linear HRV parameters provide accurate estimators of the mental state, in addition to the commonly used linear parameters.
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Affiliation(s)
- Kulbhushan Chand
- IIT Mandi iHub and HCi Foundation, Indian Institute of Technology Mandi, Kamand, HP, India , 175005
| | - Shilpa Chandra
- Indian Institute of Technology Mandi, Kamand, HP, India , 175005
| | - Varun Dutt
- Indian Institute of Technology Mandi, Kamand, HP, India , 175005
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El-Tallawy SN, Pergolizzi JV, Vasiliu-Feltes I, Ahmed RS, LeQuang JK, El-Tallawy HN, Varrassi G, Nagiub MS. Incorporation of "Artificial Intelligence" for Objective Pain Assessment: A Comprehensive Review. Pain Ther 2024; 13:293-317. [PMID: 38430433 PMCID: PMC11111436 DOI: 10.1007/s40122-024-00584-8] [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: 01/05/2024] [Accepted: 02/08/2024] [Indexed: 03/03/2024] Open
Abstract
Pain is a significant health issue, and pain assessment is essential for proper diagnosis, follow-up, and effective management of pain. The conventional methods of pain assessment often suffer from subjectivity and variability. The main issue is to understand better how people experience pain. In recent years, artificial intelligence (AI) has been playing a growing role in improving clinical diagnosis and decision-making. The application of AI offers promising opportunities to improve the accuracy and efficiency of pain assessment. This review article provides an overview of the current state of AI in pain assessment and explores its potential for improving accuracy, efficiency, and personalized care. By examining the existing literature, research gaps, and future directions, this article aims to guide further advancements in the field of pain management. An online database search was conducted via multiple websites to identify the relevant articles. The inclusion criteria were English articles published between January 2014 and January 2024). Articles that were available as full text clinical trials, observational studies, review articles, systemic reviews, and meta-analyses were included in this review. The exclusion criteria were articles that were not in the English language, not available as free full text, those involving pediatric patients, case reports, and editorials. A total of (47) articles were included in this review. In conclusion, the application of AI in pain management could present promising solutions for pain assessment. AI can potentially increase the accuracy, precision, and efficiency of objective pain assessment.
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Affiliation(s)
- Salah N El-Tallawy
- Anesthesia and Pain Department, College of Medicine, King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia.
- Anesthesia and Pain Department, Faculty of Medicine, Minia University & NCI, Cairo University, Giza, Egypt.
| | | | - Ingrid Vasiliu-Feltes
- Science, Entrepreneurship and Investments Institute, University of Miami, Miami, USA
| | - Rania S Ahmed
- College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
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Ren L, Dong J, Zhang L, Laili Y, Wang X, Qi Y, Li BH, Wang L, Yang LT, Deen MJ. Industrial Metaverse for Smart Manufacturing: Model, Architecture, and Applications. IEEE TRANSACTIONS ON CYBERNETICS 2024; 54:2683-2695. [PMID: 38512748 DOI: 10.1109/tcyb.2024.3372591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Smart manufacturing has been transforming toward industrial digitalization integrated with various advanced technologies. Metaverse has been evolving as a next-generation paradigm of a digital space extended and augmented by reality. In the metaverse, users are interconnected for various virtual activities. In consideration of advanced possibilities that may be brought by the metaverse, it is envisioned that industrial metaverse should be integrated into smart manufacturing to upgrade industry for more visible, intelligent and efficient production in the future. Therefore, a conceptual model, named IMverse Model, and novel characteristics of the industrial metaverse for smart manufacturing are proposed in this article. Besides, an industrial metaverse architecture, named IMverse Architecture, is proposed involving several key enabling technologies. Typical innovative applications of the industrial metaverse throughout the whole product life cycle for smart manufacturing are presented with insights. Nonetheless, in prospect of future, the industrial metaverse still faces limitations and is far from implementation. Thus, challenges and open issues of the industrial metaverse for smart manufacturing are discussed, then outlook is provided for further research and application.
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Li AY, Li WX, Li J. Emerging trends in management of long COVID with a focus on pulmonary rehabilitation: A review. THE CLINICAL RESPIRATORY JOURNAL 2024; 18:e13777. [PMID: 38775379 PMCID: PMC11110486 DOI: 10.1111/crj.13777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 03/10/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024]
Abstract
Long COVID, or post-acute sequelae of COVID-19 (PASC), represents a complex condition with persistent symptoms following SARS-Cov-2 infection. The symptoms include fatigue, dyspnoea, cognitive impairment, decreased quality of life in variable levels of severity. Potential mechanisms behind long COVID include vascular damage, immune dysregulation and viral persistence. Diagnosing long COVID involves medical evaluation by multidisciplinary team and assessment of persistent symptoms with scoring systems in development. Treatment strategies are symptom-focused, encompassing multidisciplinary care, rehabilitation and tailored exercise programmes. Pulmonary rehabilitation, an effective and critical component of long COVID management, has shown promise, particularly for patients with respiratory symptoms such as dyspnoea. These programmes, which combine exercise, breathing techniques, education and psychological support, improve symptoms, quality of life and overall recovery. Innovative technologies, such as telemedicine, wearable devices, telerehabilitation, are transforming long COVID management. Telemedicine facilitates consultations and interventions, eliminating healthcare access barriers. Wearable devices enable remote and continuous monitoring of patients during their rehabilitation activities. Telerehabilitation has proven to be safe and feasible and to have high potential for COVID-19 recovery. This review provides a concise overview of long COVID, encompassing its definition, prevalence, mechanisms, clinical manifestations, diagnosis and management approaches. It emphasizes the significance of multidisciplinary approach in diagnosis and treatment of long COVID, with focus on pulmonary rehabilitation and innovative technology advances to effectively address the management of long COVID.
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Affiliation(s)
- Allison Y. Li
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
- College of EngineeringUniversity of California Santa BarbaraSanta BarbaraCaliforniaUSA
| | - Willis X. Li
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Jinghong Li
- Department of MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
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Thomassin K, McVey Neufeld S, Ansari N, Vogel N. Feasibility, Acceptability, and Usability of Physiology and Emotion Monitoring in Adults and Children Using the Novel Time2Feel Smartphone Application. SENSORS (BASEL, SWITZERLAND) 2023; 23:9470. [PMID: 38067844 PMCID: PMC10708754 DOI: 10.3390/s23239470] [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: 10/24/2023] [Revised: 11/15/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023]
Abstract
The present study tests the feasibility, acceptability, and utility of the novel smartphone application-Time2Feel-to monitor family members' emotional experiences, at the experiential and physiological level, and their context. To our knowledge, Time2Feel is the first of its kind, having the capability to monitor multiple members' emotional experiences simultaneously and survey users' emotional experiences when experiencing an increase in physiological arousal. In this study, a total of 44 parents and children used Time2Feel along with the Empatica E4 wrist-wearable device for 10 days. Engagement rates were within the acceptable range and consistent with previous work using experience sampling methods. Perceived ease of use and satisfaction fell mostly in the moderate range, with users reporting challenges with connectivity. We further discuss how addressing connectivity would increase acceptability. Finally, Time2Feel was successful at identifying physiological deviations in electrodermal activity for parents and children alike, and even though responses to those deviation-generated surveys were largely consistent with random survey responses, some differences were noted for mothers and fathers. We discuss the implications of using Time2Feel for understanding families' emotional and stressful experiences day-to-day.
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Affiliation(s)
- Kristel Thomassin
- Department of Psychology, University of Guelph, Guelph, ON N1G 2W1, Canada; (S.M.N.); (N.A.); (N.V.)
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Chatterjee A, Prinz A, Riegler MA, Das J. A systematic review and knowledge mapping on ICT-based remote and automatic COVID-19 patient monitoring and care. BMC Health Serv Res 2023; 23:1047. [PMID: 37777722 PMCID: PMC10543863 DOI: 10.1186/s12913-023-10047-z] [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: 02/25/2023] [Accepted: 09/20/2023] [Indexed: 10/02/2023] Open
Abstract
BACKGROUND e-Health has played a crucial role during the COVID-19 pandemic in primary health care. e-Health is the cost-effective and secure use of Information and Communication Technologies (ICTs) to support health and health-related fields. Various stakeholders worldwide use ICTs, including individuals, non-profit organizations, health practitioners, and governments. As a result of the COVID-19 pandemic, ICT has improved the quality of healthcare, the exchange of information, training of healthcare professionals and patients, and facilitated the relationship between patients and healthcare providers. This study systematically reviews the literature on ICT-based automatic and remote monitoring methods, as well as different ICT techniques used in the care of COVID-19-infected patients. OBJECTIVE The purpose of this systematic literature review is to identify the e-Health methods, associated ICTs, method implementation strategies, information collection techniques, advantages, and disadvantages of remote and automatic patient monitoring and care in COVID-19 pandemic. METHODS The search included primary studies that were published between January 2020 and June 2022 in scientific and electronic databases, such as EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MEDLINE, Google Scholar, JMIR, Web of Science, Science Direct, and PubMed. In this review, the findings from the included publications are presented and elaborated according to the identified research questions. Evidence-based systematic reviews and meta-analyses were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Additionally, we improved the review process using the Rayyan tool and the Scale for the Assessment of Narrative Review Articles (SANRA). Among the eligibility criteria were methodological rigor, conceptual clarity, and useful implementation of ICTs in e-Health for remote and automatic monitoring of COVID-19 patients. RESULTS Our initial search identified 664 potential studies; 102 were assessed for eligibility in the pre-final stage and 65 articles were used in the final review with the inclusion and exclusion criteria. The review identified the following eHealth methods-Telemedicine, Mobile Health (mHealth), and Telehealth. The associated ICTs are Wearable Body Sensors, Artificial Intelligence (AI) algorithms, Internet-of-Things, or Internet-of-Medical-Things (IoT or IoMT), Biometric Monitoring Technologies (BioMeTs), and Bluetooth-enabled (BLE) home health monitoring devices. Spatial or positional data, personal and individual health, and wellness data, including vital signs, symptoms, biomedical images and signals, and lifestyle data are examples of information that is managed by ICTs. Different AI and IoT methods have opened new possibilities for automatic and remote patient monitoring with associated advantages and weaknesses. Our findings were represented in a structured manner using a semantic knowledge graph (e.g., ontology model). CONCLUSIONS Various e-Health methods, related remote monitoring technologies, different approaches, information categories, the adoption of ICT tools for an automatic remote patient monitoring (RPM), advantages and limitations of RMTs in the COVID-19 case are discussed in this review. The use of e-Health during the COVID-19 pandemic illustrates the constraints and possibilities of using ICTs. ICTs are not merely an external tool to achieve definite remote and automatic health monitoring goals; instead, they are embedded in contexts. Therefore, the importance of the mutual design process between ICT and society during the global health crisis has been observed from a social informatics perspective. A global health crisis can be observed as an information crisis (e.g., insufficient information, unreliable information, and inaccessible information); however, this review shows the influence of ICTs on COVID-19 patients' health monitoring and related information collection techniques.
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Affiliation(s)
- Ayan Chatterjee
- Department of Information and Communication Technology, Centre for e-Health, University of Agder, Grimstad, Norway.
- Department of Holistic Systems, Simula Metropolitan Center for Digital Engineering, Oslo, Norway.
| | - Andreas Prinz
- Department of Information and Communication Technology, Centre for e-Health, University of Agder, Grimstad, Norway
| | - Michael A Riegler
- Department of Holistic Systems, Simula Metropolitan Center for Digital Engineering, Oslo, Norway
| | - Jishnu Das
- Department of Information Systems, Centre for e-Health, University of Agder, Kristiansand, Norway
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12
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Hasasneh A, Hijazi H, Talib MA, Afadar Y, Nassif AB, Nasir Q. Wearable Devices and Explainable Unsupervised Learning for COVID-19 Detection and Monitoring. Diagnostics (Basel) 2023; 13:3071. [PMID: 37835814 PMCID: PMC10572947 DOI: 10.3390/diagnostics13193071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/20/2023] [Accepted: 09/22/2023] [Indexed: 10/15/2023] Open
Abstract
Despite the declining COVID-19 cases, global healthcare systems still face significant challenges due to ongoing infections, especially among fully vaccinated individuals, including adolescents and young adults (AYA). To tackle this issue, cost-effective alternatives utilizing technologies like Artificial Intelligence (AI) and wearable devices have emerged for disease screening, diagnosis, and monitoring. However, many AI solutions in this context heavily rely on supervised learning techniques, which pose challenges such as human labeling reliability and time-consuming data annotation. In this study, we propose an innovative unsupervised framework that leverages smartwatch data to detect and monitor COVID-19 infections. We utilize longitudinal data, including heart rate (HR), heart rate variability (HRV), and physical activity measured via step count, collected through the continuous monitoring of volunteers. Our goal is to offer effective and affordable solutions for COVID-19 detection and monitoring. Our unsupervised framework employs interpretable clusters of normal and abnormal measures, facilitating disease progression detection. Additionally, we enhance result interpretation by leveraging the language model Davinci GPT-3 to gain deeper insights into the underlying data patterns and relationships. Our results demonstrate the effectiveness of unsupervised learning, achieving a Silhouette score of 0.55. Furthermore, validation using supervised learning techniques yields high accuracy (0.884 ± 0.005), precision (0.80 ± 0.112), and recall (0.817 ± 0.037). These promising findings indicate the potential of unsupervised techniques for identifying inflammatory markers, contributing to the development of efficient and reliable COVID-19 detection and monitoring methods. Our study shows the capabilities of AI and wearables, reflecting the pursuit of low-cost, accessible solutions for addressing health challenges related to inflammatory diseases, thereby opening new avenues for scalable and widely applicable health monitoring solutions.
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Affiliation(s)
- Ahmad Hasasneh
- Department of Natural, Engineering, and Technology Sciences, Faculty of Graduate Studies, Arab American University, Ramallah P-600-699, Palestine;
| | - Haytham Hijazi
- Department of Informatics Engineering, CISUC-Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, 3030-790 Coimbra, Portugal
- Intelligent Systems Department, Palestine Ahliya University, Bethlehem P-150-199, Palestine
| | - Manar Abu Talib
- College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates; (M.A.T.); (Y.A.); (A.B.N.); (Q.N.)
| | - Yaman Afadar
- College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates; (M.A.T.); (Y.A.); (A.B.N.); (Q.N.)
| | - Ali Bou Nassif
- College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates; (M.A.T.); (Y.A.); (A.B.N.); (Q.N.)
| | - Qassim Nasir
- College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates; (M.A.T.); (Y.A.); (A.B.N.); (Q.N.)
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13
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Quesada-Caballero M, Carmona-García A, Chami-Peña S, Caballero-Mateos AM, Fernández-Martín O, Cañadas-De la Fuente GA, Romero-Bejar JL. Telemedicine in Elderly Hypertensive and Patients with Chronic Diseases during the COVID-19 Pandemic: A Systematic Review and Meta-Analysis. J Clin Med 2023; 12:6160. [PMID: 37834803 PMCID: PMC10574013 DOI: 10.3390/jcm12196160] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 09/21/2023] [Accepted: 09/22/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND One aspect of the distancing measures imposed in response to the COVID-19 pandemic is that telemedicine consultations have increased exponentially. Among these consultations, the assessment and follow-up of patients with chronic diseases in a non-presential setting has been strengthened considerably. Nevertheless, some controversy remains about the most suitable means of patient follow-up. OBJECTIVE To analyze the impact of the telemedicine measures implemented during the COVID-19 period on chronic patients. MATERIAL AND METHODS A systematic review was carried out using the following databases: PubMed, Pro-Quest, and Scopus. The systematic review followed the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search equation utilized descriptors sourced from the Medical Subject Headings (MeSH) thesaurus. The search equation was: "hypertension AND older AND primary care AND (COVID-19 OR coronavirus)" and its Spanish equivalent. RESULTS The following data were obtained: 14 articles provided data on 6,109,628 patients and another 4 articles focused on a study population of 9684 physicians. Telemedicine was less likely to be used by elderly patients (OR 0.85; 95% C.I. 0.83-0.88; p = 0.05), those of Asian race (OR 0.69; 95% C.I. 0.66-0.73; p = 0.05), and those whose native language was not English (OR 0.89; 95% C.I. 0.78-0.9; p = 0.05). In primary care, lower use of telemedicine was associated with residents of rural areas (OR 0.81; p = 0.05), patients of African American race (OR 0.65, p = 0.05), and others (OR 0.64; p = 0.05). A high proportion (40%) of physicians had no prior training in telemedicine techniques. The highest quality in terms of telephone consultation was significantly associated with physicians who did not increase their prescription of antibiotherapy during the pandemic (OR = 0.30, p = 0.05) or prescribe more tests (OR 0.06 p = 0.05), i.e., who maintained their former clinical criteria despite COVID-19. CONCLUSIONS Telemedicine is of proven value and has been especially useful in the COVID-19 pandemic. A mixed remote-presential model is most efficient. Appropriate training in this area for physicians and patients, together with correct provision, is essential to prevent errors in implementation and use.
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Affiliation(s)
- Miguel Quesada-Caballero
- Centro de Salud Albayda La Cruz, Distrito Sanitario Granada-Metropolitano, Servicio Andaluz de Salud, Calle Virgen de la Consolación 12, 18015 Granada, Spain;
| | - Ana Carmona-García
- Critical Care and Emergency Unit (UCCU), Distrito Sanitario Granada-Metropolitano, Servicio Andaluz de Salud, Calle Virgen de la Consolación 12, 18015 Granada, Spain
| | - Sara Chami-Peña
- Hospital de la Serranía de Ronda, Servicio Andaluz de Salud, Carretera San Pedro Km 2, 29400 Ronda, Spain
| | - Antonio M. Caballero-Mateos
- Gastroenterology and Hepatology Department, San Cecilio University Hospital, Av. del Conocimiento s/n, 18016 Granada, Spain
| | - Oscar Fernández-Martín
- Centro de Salud Guadix, Área de Gestión Sanitaria Nordeste Granada, Servicio Andaluz de Salud, Ctra. de Murcia s/n, 18800 Baza, Spain
| | - Guillermo A. Cañadas-De la Fuente
- Faculty of Health Sciences, University of Granada, Avda. Ilustración 60, 18016 Granada, Spain;
- Brain, Mind and Behaviour Research Center (CIMCYC), University of Granada, 18071 Granada, Spain
| | - José Luis Romero-Bejar
- Statistics and Operational Research Department, University of Granada, Avda. Fuentenueva s/n, 18071 Granada, Spain;
- Institute of Mathematics, University of Granada (IMAG), Ventanilla 11, 18001 Granada, Spain
- Instituto de Investigación Biosanitaria (ibs.GRANADA), 18012 Granada, Spain
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14
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Kromołowska K, Kluza K, Kańtoch E, Sulikowski P. Open-Source Strain Gauge System for Monitoring Pressure Distribution of Runner's Feet. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23042323. [PMID: 36850921 PMCID: PMC9959378 DOI: 10.3390/s23042323] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/10/2023] [Accepted: 02/16/2023] [Indexed: 06/12/2023]
Abstract
The objective of the research presented in this paper was to provide a novel open-source strain gauge system that shall enable the measurement of the pressure of a runner's feet on the ground and the presentation of the results of that measurement to the user. The system based on electronic shoe inserts with 16 built-in pressure sensors laminated in a transparent film was created, consisting of two parts: a mobile application and a wearable device. The developed system provides a number of advantages in comparison with existing solutions, including no need for calibration, an accurate and frequent measurement of pressure distribution, placement of electronics on the outside of a shoe, low cost, and an open-source approach to encourage enhancements and open collaboration.
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Affiliation(s)
- Klaudia Kromołowska
- AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
- Faculty of Computer Science and Telecommunications, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland
| | - Krzysztof Kluza
- AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
| | - Eliasz Kańtoch
- AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
| | - Piotr Sulikowski
- Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, ul. Żołnierska 49, 71-210 Szczecin, Poland
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15
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Escobar-Linero E, Muñoz-Saavedra L, Luna-Perejón F, Sevillano JL, Domínguez-Morales M. Wearable Health Devices for Diagnosis Support: Evolution and Future Tendencies. SENSORS (BASEL, SWITZERLAND) 2023; 23:1678. [PMID: 36772718 PMCID: PMC9920884 DOI: 10.3390/s23031678] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/18/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
The use of wearable devices has increased substantially in recent years. This, together with the rise of telemedicine, has led to the use of these types of devices in the healthcare field. In this work, we carried out a detailed study on the use of these devices (regarding the general trends); we analyzed the research works and devices marketed in the last 10 years. This analysis extracted relevant information on the general trend of use, as well as more specific aspects, such as the use of sensors, communication technologies, and diseases. A comparison was made between the commercial and research aspects linked to wearables in the healthcare field, and upcoming trends were analyzed.
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Affiliation(s)
- Elena Escobar-Linero
- Architecture and Computer Technology Department, ETSII-EPS, University of Seville, 41004 Sevilla, Spain
- Robotics and Technology of Computers Laboratory, University of Seville, 41004 Sevilla, Spain
| | - Luis Muñoz-Saavedra
- Architecture and Computer Technology Department, ETSII-EPS, University of Seville, 41004 Sevilla, Spain
- Robotics and Technology of Computers Laboratory, University of Seville, 41004 Sevilla, Spain
| | - Francisco Luna-Perejón
- Architecture and Computer Technology Department, ETSII-EPS, University of Seville, 41004 Sevilla, Spain
- Robotics and Technology of Computers Laboratory, University of Seville, 41004 Sevilla, Spain
| | - José Luis Sevillano
- Architecture and Computer Technology Department, ETSII-EPS, University of Seville, 41004 Sevilla, Spain
- Robotics and Technology of Computers Laboratory, University of Seville, 41004 Sevilla, Spain
- Research Institute of Computer Engineering (I3US), University of Seville, 41004 Sevilla, Spain
| | - Manuel Domínguez-Morales
- Architecture and Computer Technology Department, ETSII-EPS, University of Seville, 41004 Sevilla, Spain
- Robotics and Technology of Computers Laboratory, University of Seville, 41004 Sevilla, Spain
- Research Institute of Computer Engineering (I3US), University of Seville, 41004 Sevilla, Spain
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16
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Manchanda A, Lee K, Poznanski GD, Hassani A. Automated Adjustment of PPE Masks Using IoT Sensor Fusion. SENSORS (BASEL, SWITZERLAND) 2023; 23:1711. [PMID: 36772747 PMCID: PMC9921841 DOI: 10.3390/s23031711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/13/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
The COVID-19 pandemic has led to a dramatic increase in the use of PPE by the general public as well as health professionals. Scientists and health organizations have developed measures to protect people and minimize the catastrophic outcomes of COVID, including social distancing, frequent and periodic sanitizing, vaccinations, protective coverings, and face masks. During this time, the usage of protective face masks has increased dramatically. A mask only provides full safety to the user if it is a proper fit on their face. The aim of this paper is to automatically analyze and improve the fit of a face mask using IoT sensors. This paper describes the creation of a 3D-printed smart face mask that uses sensors to determine the current mask fit and then automatically tightens mask straps. This is evaluated using adjustment response time and the quality of fit achieved using the automatic adjustment approach with a range of sensor types.
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Affiliation(s)
- Ashish Manchanda
- School of Information Technology, Deakin University, Geelong, VIC 3220, Australia
| | - Kevin Lee
- School of Information Technology, Deakin University, Geelong, VIC 3220, Australia
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17
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Sinha K, Uddin Z, Kawsar H, Islam S, Deen M, Howlader M. Analyzing chronic disease biomarkers using electrochemical sensors and artificial neural networks. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2022.116861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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18
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Shen J, Ghatti S, Levkov NR, Shen H, Sen T, Rheuban K, Enfield K, Facteau NR, Engel G, Dowdell K. A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine. Front Artif Intell 2022; 5:1034732. [PMID: 36530356 PMCID: PMC9755752 DOI: 10.3389/frai.2022.1034732] [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: 09/02/2022] [Accepted: 11/02/2022] [Indexed: 09/19/2023] Open
Abstract
Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.
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Affiliation(s)
- John Shen
- Department of Computer Science, University of Virginia, Charlottesville, VA, United States
| | - Siddharth Ghatti
- Department of Computer Science, University of Virginia, Charlottesville, VA, United States
| | - Nate Ryan Levkov
- Department of Computer Science, University of Virginia, Charlottesville, VA, United States
| | - Haiying Shen
- Department of Computer Science, University of Virginia, Charlottesville, VA, United States
| | - Tanmoy Sen
- Department of Computer Science, University of Virginia, Charlottesville, VA, United States
| | - Karen Rheuban
- School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Kyle Enfield
- School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Nikki Reyer Facteau
- University of Virginia (UVA) Health System, University of Virginia, Charlottesville, VA, United States
| | - Gina Engel
- School of Medicine, University of Virginia, Charlottesville, VA, United States
| | - Kim Dowdell
- School of Medicine, University of Virginia, Charlottesville, VA, United States
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19
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Zhang M, Sykes DL, Brindle K, Sadofsky LR, Morice AH. Chronic cough-the limitation and advances in assessment techniques. J Thorac Dis 2022; 14:5097-5119. [PMID: 36647459 PMCID: PMC9840016 DOI: 10.21037/jtd-22-874] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 11/04/2022] [Indexed: 11/23/2022]
Abstract
Accurate and consistent assessments of cough are essential to advance the understanding of the mechanisms of cough and individualised the management of patients. Considerable progress has been made in this work. Here we reviewed the currently available tools for subjectively and objectively measuring both cough sensitivity and severity. We also provided some opinions on the new techniques and future directions. The simple and practical Visual Analogue Scale (VAS), the Leicester Cough Questionnaire (LCQ), and the Cough Specific Quality of Life Questionnaire (CQLQ) are the most widely used self-reported questionnaires for evaluating and quantifying cough severity. The Hull Airway Reflux Questionnaire (HARQ) is a tool to elucidate the constellation of symptoms underlying the diagnosis of chronic cough. Chemical excitation tests are widely used to explore the pathophysiological mechanisms of the cough reflex, such as capsaicin, citric acid and adenosine triphosphate (ATP) challenge test. Cough frequency is an ideal primary endpoint for clinical research, but the application of cough counters has been limited in clinical practice by the high cost and reliance on aural validation. The ongoing development of cough detection technology for smartphone apps and wearable devices will hopefully simplify cough counting, thus transitioning it from niche research to a widely available clinical application.
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Affiliation(s)
- Mengru Zhang
- Centre for Clinical Science, Respiratory Medicine, Hull York Medical School, University of Hull, Castle Hill Hospital, Cottingham, East Yorkshire, UK;,Department of Pulmonary and Critical Care Medicine, Tongji Hospital, Tongji University School of Medicine, Shanghai, China
| | - Dominic L. Sykes
- Centre for Clinical Science, Respiratory Medicine, Hull York Medical School, University of Hull, Castle Hill Hospital, Cottingham, East Yorkshire, UK
| | - Kayleigh Brindle
- Centre for Clinical Science, Respiratory Medicine, Hull York Medical School, University of Hull, Castle Hill Hospital, Cottingham, East Yorkshire, UK
| | - Laura R. Sadofsky
- Centre for Clinical Science, Respiratory Medicine, Hull York Medical School, University of Hull, Castle Hill Hospital, Cottingham, East Yorkshire, UK
| | - Alyn H. Morice
- Centre for Clinical Science, Respiratory Medicine, Hull York Medical School, University of Hull, Castle Hill Hospital, Cottingham, East Yorkshire, UK
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20
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Adiono T, Ahmadi N, Saraswati C, Aditya Y, Yudhanto YP, Aziz A, Wulandari L, Maranatha D, Khusnurrokhman G, Riadi ARW, Sudjud RW. Respinos: A Portable Device for Remote Vital Signs Monitoring of COVID-19 Patients. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2022; 16:947-961. [PMID: 36067112 PMCID: PMC9906646 DOI: 10.1109/tbcas.2022.3204632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/28/2022] [Accepted: 08/24/2022] [Indexed: 06/15/2023]
Abstract
The rapidly increasing number of COVID-19 patients has posed a massive burden on many healthcare systems worldwide. Moreover, the limited availability of diagnostic and treatment equipment makes it difficult to treat patients in the hospital. To reduce the burden and maintain the quality of care, asymptomatic patients or patients with mild symptoms are advised to self-isolate at home. However, self-isolated patients need to be continuously monitored as their health can turn into critical condition within a short time. Therefore, a portable device that can remotely monitor the condition and progression of the health of these patients is urgently needed. Here we present a portable device, called Respinos, that can monitor multiparameter vital signs including respiratory rate, heart rate, body temperature, and SpO2. It can also operate as a spirometer that measures forced vital capacity (FVC), forced expiratory volume (FEV), FEV in the first second (FEV1), and peak expiratory flow Rate (PEFR) parameters which are useful for detecting pulmonary diseases. The spirometer is designed in the form of a tube that can be ergonomically inflated by the patient, and is equipped with an accurate and disposable turbine based air flow sensor to evaluate the patient's respiratory condition. Respinos uses rechargeable batteries and wirelessly connects to a mobile application whereby the patient's condition can be monitored in real-time and consulted with doctors via chat. Extensive comparison against medical-grade reference devices showed good performance of Respinos. Overall results demonstrate the potential of Respinos for remote patient monitoring during and post pandemic.
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Affiliation(s)
- Trio Adiono
- School of Electrical Engineering and InformaticsBandung Institute of TechnologyBandung40132Indonesia
| | - Nur Ahmadi
- Center for Artificial Intelligence (U-CoE AI-VLB), School of Electrical Engineering and InformaticsBandung Institute of TechnologyBandung40132Indonesia
| | | | | | | | | | - Laksmi Wulandari
- Department of Pulmonology and Respiratory Medicine and Faculty of MedicineUniversitas Airlangga-RSUD dr. SoetomoSurabaya60115Indonesia
| | - Daniel Maranatha
- Department of Pulmonology and Respiratory Medicine and Faculty of MedicineUniversitas Airlangga-RSUD dr. SoetomoSurabaya60115Indonesia
| | - Gemilang Khusnurrokhman
- Department of Pulmonology and Respiratory Medicine and Faculty of MedicineUniversitas Airlangga-RSUD dr. SoetomoSurabaya60115Indonesia
| | - Agustinus Rizki Wirawan Riadi
- Department of Pulmonology and Respiratory Medicine and Faculty of MedicineUniversitas Airlangga-RSUD dr. SoetomoSurabaya60115Indonesia
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21
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Affiliation(s)
- Baoying Dai
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Jiangsu Key Laboratory for Biosensors Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM) Nanjing University of Posts and Telecommunications Nanjing China
| | - Chenchen Gao
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Jiangsu Key Laboratory for Biosensors Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM) Nanjing University of Posts and Telecommunications Nanjing China
| | - Yannan Xie
- State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Jiangsu Key Laboratory for Biosensors Jiangsu National Synergetic Innovation Center for Advanced Materials (SICAM) Nanjing University of Posts and Telecommunications Nanjing China
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22
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Subramaniam S, Faisal AI, Deen MJ. Wearable Sensor Systems for Fall Risk Assessment: A Review. Front Digit Health 2022; 4:921506. [PMID: 35911615 PMCID: PMC9329588 DOI: 10.3389/fdgth.2022.921506] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 06/22/2022] [Indexed: 01/14/2023] Open
Abstract
Fall risk assessment and fall detection are crucial for the prevention of adverse and long-term health outcomes. Wearable sensor systems have been used to assess fall risk and detect falls while providing additional meaningful information regarding gait characteristics. Commonly used wearable systems for this purpose are inertial measurement units (IMUs), which acquire data from accelerometers and gyroscopes. IMUs can be placed at various locations on the body to acquire motion data that can be further analyzed and interpreted. Insole-based devices are wearable systems that were also developed for fall risk assessment and fall detection. Insole-based systems are placed beneath the sole of the foot and typically obtain plantar pressure distribution data. Fall-related parameters have been investigated using inertial sensor-based and insole-based devices include, but are not limited to, center of pressure trajectory, postural stability, plantar pressure distribution and gait characteristics such as cadence, step length, single/double support ratio and stance/swing phase duration. The acquired data from inertial and insole-based systems can undergo various analysis techniques to provide meaningful information regarding an individual's fall risk or fall status. By assessing the merits and limitations of existing systems, future wearable sensors can be improved to allow for more accurate and convenient fall risk assessment. This article reviews inertial sensor-based and insole-based wearable devices that were developed for applications related to falls. This review identifies key points including spatiotemporal parameters, biomechanical gait parameters, physical activities and data analysis methods pertaining to recently developed systems, current challenges, and future perspectives.
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Affiliation(s)
| | - Abu Ilius Faisal
- Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - M. Jamal Deen
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
- Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
- *Correspondence: M. Jamal Deen
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Design of a Physiological Monitoring Device for Holistic Telemedicine Applications. MAPAN 2022. [PMCID: PMC9258458 DOI: 10.1007/s12647-022-00577-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Telemedicine is a word that the world has been hearing about since the early days of the telephonic technology used to exchange information for delivering medical care. Medical practitioners need the holistic information of the patients to treat them effectively. Telemedicine is relatively limited compared to direct appointments; hence a prototype is needed to create an environment that is identical to the direct appointments where the practitioners can see the patient and their physiological data. A novel prototype with state-of-the-art software and hardware is developed for establishing a holistic telemedicine environment in this work. The designed system measures the skin temperature, SpO2, pulse rate, heart rate, breath rate, and Non-invasive Blood Pressure (NIBP). The SpO2 of the system is measured with Beer-Lambert’s law, and the NIBP is measured using a single synchronous ECG and PPG sensor. Quality video conferencing is provided between the patient and the practitioners.
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Sinaki FY, Ward R, Abbott D, Allen J, Fletcher RR, Menon C, Elgendi M. Ethnic disparities in publicly-available pulse oximetry databases. COMMUNICATIONS MEDICINE 2022; 2:59. [PMID: 35637660 PMCID: PMC9142514 DOI: 10.1038/s43856-022-00121-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 05/03/2022] [Indexed: 11/25/2022] Open
Abstract
Sinaki et al. highlight ethnic disparities in the populations of 12 publicly-available pulse oximetry databases. The authors outline the potential consequences of such disparities on pulse oximetry device and algorithm development.
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Subramaniam S, Majumder S, Faisal AI, Deen MJ. Insole-Based Systems for Health Monitoring: Current Solutions and Research Challenges. SENSORS (BASEL, SWITZERLAND) 2022; 22:438. [PMID: 35062398 PMCID: PMC8780030 DOI: 10.3390/s22020438] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 01/01/2022] [Accepted: 01/03/2022] [Indexed: 02/04/2023]
Abstract
Wearable health monitoring devices allow for measuring physiological parameters without restricting individuals' daily activities, providing information that is reflective of an individual's health and well-being. However, these systems need to be accurate, power-efficient, unobtrusive and simple to use to enable a reliable, convenient, automatic and ubiquitous means of long-term health monitoring. One such system can be embedded in an insole to obtain physiological data from the plantar aspect of the foot that can be analyzed to gain insight into an individual's health. This manuscript provides a comprehensive review of insole-based sensor systems that measure a variety of parameters useful for overall health monitoring, with a focus on insole-based PPD measurement systems developed in recent years. Existing solutions are reviewed, and several open issues are presented and discussed. The concept of a fully integrated insole-based health monitoring system and considerations for future work are described. By developing a system that is capable of measuring parameters such as PPD, gait characteristics, foot temperature and heart rate, a holistic understanding of an individual's health and well-being can be obtained without interrupting day-to-day activities. The proposed device can have a multitude of applications, such as for pathology detection, tracking medical conditions and analyzing gait characteristics.
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Affiliation(s)
- Sophini Subramaniam
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada;
| | - Sumit Majumder
- Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada; (S.M.); (A.I.F.)
- Department of Biomedical Engineering, Chittagong University of Engineering and Technology, Chattogram 4349, Bangladesh
| | - Abu Ilius Faisal
- Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada; (S.M.); (A.I.F.)
| | - M. Jamal Deen
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada;
- Electrical and Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada; (S.M.); (A.I.F.)
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Photoplethysmography Analysis with Duffing–Holmes Self-Synchronization Dynamic Errors and 1D CNN-Based Classifier for Upper Extremity Vascular Disease Screening. Processes (Basel) 2021. [DOI: 10.3390/pr9112093] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Common upper limb peripheral artery diseases (PADs) are atherosclerosis, embolic diseases, and systemic diseases, which are often asymptomatic, and the narrowed arteries (stenosis) will gradually reduce blood flow in the right or left upper limbs. Upper extremity vascular disease (UEVD) and atherosclerosis are high-risk PADs for patients with Type 2 diabetes or with both diabetes and end-stage renal disease. For early UEVD detection, a fingertip-based, toe-based, or wrist-based photoplethysmography (PPG) tool is a simple and noninvasive measurement system for vital sign monitoring and healthcare applications. Based on time-domain PPG analysis, a Duffing–Holmes system with a master system and a slave system is used to extract self-synchronization dynamic errors, which can track the differences in PPG morphology (in amplitudes (systolic peak) and time delay (systolic peak to diastolic peak)) between healthy subjects and PAD patients. In the preliminary analysis, the self-synchronization dynamic errors can be used to evaluate risk levels based on the reflection index (RI), which includes normal condition, lower PAD, and higher PAD. Then, a one-dimensional convolutional neural network is established as a multilayer classifier for automatic UEVD screening. The experimental results indicated that the self-synchronization dynamic errors have a positive correlation with the RI (R2 = 0.6694). The K-fold cross-validation is used to verify the performance of the proposed classifier with recall (%), precision (%), accuracy (%), and F1 score.
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Barizien N, Le Guen M, Russel S, Touche P, Huang F, Vallée A. Clinical characterization of dysautonomia in long COVID-19 patients. Sci Rep 2021; 11:14042. [PMID: 34234251 DOI: 10.1038/s41598-021-93546-5.pdf] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 06/28/2021] [Indexed: 05/22/2023] Open
Abstract
Increasing numbers of COVID-19 patients, continue to experience symptoms months after recovering from mild cases of COVID-19. Amongst these symptoms, several are related to neurological manifestations, including fatigue, anosmia, hypogeusia, headaches and hypoxia. However, the involvement of the autonomic nervous system, expressed by a dysautonomia, which can aggregate all these neurological symptoms has not been prominently reported. Here, we hypothesize that dysautonomia, could occur in secondary COVID-19 infection, also referred to as "long COVID" infection. 39 participants were included from December 2020 to January 2021 for assessment by the Department of physical medicine to enhance their physical capabilities: 12 participants with COVID-19 diagnosis and fatigue, 15 participants with COVID-19 diagnosis without fatigue and 12 control participants without COVID-19 diagnosis and without fatigue. Heart rate variability (HRV) during a change in position is commonly measured to diagnose autonomic dysregulation. In this cohort, to reflect HRV, parasympathetic/sympathetic balance was estimated using the NOL index, a multiparameter artificial intelligence-driven index calculated from extracted physiological signals by the PMD-200 pain monitoring system. Repeated-measures mixed-models testing group effect were performed to analyze NOL index changes over time between groups. A significant NOL index dissociation over time between long COVID-19 participants with fatigue and control participants was observed (p = 0.046). A trend towards significant NOL index dissociation over time was observed between long COVID-19 participants without fatigue and control participants (p = 0.109). No difference over time was observed between the two groups of long COVID-19 participants (p = 0.904). Long COVID-19 participants with fatigue may exhibit a dysautonomia characterized by dysregulation of the HRV, that is reflected by the NOL index measurements, compared to control participants. Dysautonomia may explain the persistent symptoms observed in long COVID-19 patients, such as fatigue and hypoxia. Trial registration: The study was approved by the Foch IRB: IRB00012437 (Approval Number: 20-12-02) on December 16, 2020.
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Affiliation(s)
- Nicolas Barizien
- Department of Physical Medicine and Rehabilitation, Foch Hospital, Suresnes, France
| | - Morgan Le Guen
- Department of Anesthesiology, Foch Hospital, Suresnes, France
| | | | - Pauline Touche
- Department of Clinical Research and Innovation, Foch Hospital, 40 rue Worth, 92150, Suresnes, France
| | - Florent Huang
- Department of Cardiology, Foch Hospital, Suresnes, France
| | - Alexandre Vallée
- Department of Clinical Research and Innovation, Foch Hospital, 40 rue Worth, 92150, Suresnes, France.
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28
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Clinical characterization of dysautonomia in long COVID-19 patients. Sci Rep 2021; 11:14042. [PMID: 34234251 PMCID: PMC8263555 DOI: 10.1038/s41598-021-93546-5] [Citation(s) in RCA: 105] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 06/28/2021] [Indexed: 01/07/2023] Open
Abstract
Increasing numbers of COVID-19 patients, continue to experience symptoms months after recovering from mild cases of COVID-19. Amongst these symptoms, several are related to neurological manifestations, including fatigue, anosmia, hypogeusia, headaches and hypoxia. However, the involvement of the autonomic nervous system, expressed by a dysautonomia, which can aggregate all these neurological symptoms has not been prominently reported. Here, we hypothesize that dysautonomia, could occur in secondary COVID-19 infection, also referred to as “long COVID” infection. 39 participants were included from December 2020 to January 2021 for assessment by the Department of physical medicine to enhance their physical capabilities: 12 participants with COVID-19 diagnosis and fatigue, 15 participants with COVID-19 diagnosis without fatigue and 12 control participants without COVID-19 diagnosis and without fatigue. Heart rate variability (HRV) during a change in position is commonly measured to diagnose autonomic dysregulation. In this cohort, to reflect HRV, parasympathetic/sympathetic balance was estimated using the NOL index, a multiparameter artificial intelligence-driven index calculated from extracted physiological signals by the PMD-200 pain monitoring system. Repeated-measures mixed-models testing group effect were performed to analyze NOL index changes over time between groups. A significant NOL index dissociation over time between long COVID-19 participants with fatigue and control participants was observed (p = 0.046). A trend towards significant NOL index dissociation over time was observed between long COVID-19 participants without fatigue and control participants (p = 0.109). No difference over time was observed between the two groups of long COVID-19 participants (p = 0.904). Long COVID-19 participants with fatigue may exhibit a dysautonomia characterized by dysregulation of the HRV, that is reflected by the NOL index measurements, compared to control participants. Dysautonomia may explain the persistent symptoms observed in long COVID-19 patients, such as fatigue and hypoxia.
Trial registration: The study was approved by the Foch IRB: IRB00012437 (Approval Number: 20-12-02) on December 16, 2020.
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