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Fekete M, Liotta EM, Molnar T, Fülöp GA, Lehoczki A. The role of atrial fibrillation in vascular cognitive impairment and dementia: epidemiology, pathophysiology, and preventive strategies. GeroScience 2024:10.1007/s11357-024-01290-1. [PMID: 39138793 DOI: 10.1007/s11357-024-01290-1] [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: 06/12/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024] Open
Abstract
The aging population in Europe faces a substantial burden from dementia, with vascular cognitive impairment and dementia (VCID) being a preventable cause. Atrial fibrillation (AF), a common cardiac arrhythmia, increases the risk of VCID through mechanisms such as thromboembolism, cerebral hypoperfusion, and inflammation. This review explores the epidemiology, pathophysiology, and preventive strategies for AF-related VCID. Epidemiological data indicate that AF prevalence rises with age, affecting up to 12% of individuals over 80. Neuroimaging studies reveal chronic brain changes in AF patients, including strokes, lacunar strokes, white matter hyperintensities (WMHs), and cerebral microbleeds (CMHs), while cognitive assessments show impairments in memory, executive function, and attention. The COVID-19 pandemic has exacerbated the underdiagnosis of AF, leading to an increase in undiagnosed strokes and cognitive impairment. Many elderly individuals did not seek medical care due to fear of exposure, resulting in delayed diagnoses. Additionally, reduced family supervision during the pandemic contributed to missed opportunities for early detection of AF and related complications. Emerging evidence suggests that long COVID may also elevate the risk of AF, further complicating the management of this condition. This review underscores the importance of early detection and comprehensive management of AF to mitigate cognitive decline. Preventive measures, including public awareness campaigns, patient education, and the use of smart devices for early detection, are crucial. Anticoagulation therapy, rate and rhythm control, and addressing comorbid conditions are essential therapeutic strategies. Recognizing and addressing the cardiovascular and cognitive impacts of AF, especially in the context of the COVID-19 pandemic, is essential for advancing public health.
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Affiliation(s)
- Mónika Fekete
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary
| | - Eric M Liotta
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Tihamer Molnar
- Department of Anaesthesiology and Intensive Care, Medical School, University of Pecs, Pecs, Hungary
| | - Gábor A Fülöp
- Heart and Vascular Center, Semmelweis University, Budapest, Hungary
| | - Andrea Lehoczki
- Institute of Preventive Medicine and Public Health, Semmelweis University, Budapest, Hungary.
- Doctoral College, Health Sciences Program, Semmelweis University, Budapest, Hungary.
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Venn RA, Khurshid S, Grayson M, Ashburner JM, Al‐Alusi MA, Chang Y, Foulkes A, Ellinor PT, McManus DD, Singer DE, Atlas SJ, Lubitz SA. Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System. J Am Heart Assoc 2024; 13:e032126. [PMID: 38156452 PMCID: PMC10863832 DOI: 10.1161/jaha.123.032126] [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: 08/10/2023] [Accepted: 11/17/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking. METHODS AND RESULTS WATCH-IT (Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20-question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10-year increase [95% CI, 0.77-0.82]), male sex (OR, 0.87 [95% CI, 0.80-0.95]), and heart failure (OR, 0.75 [95% CI, 0.63-0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1-quartile increase [95% CI, 1.04-1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05-1.30]) were associated with greater odds of device use. CONCLUSIONS Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.
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Affiliation(s)
- Rachael A. Venn
- Cardiovascular Research Center, Massachusetts General HospitalBostonMAUSA
- Demoulas Center for Cardiac ArrhythmiasCardiology Division, Massachusetts General HospitalBostonMAUSA
| | - Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General HospitalBostonMAUSA
- Demoulas Center for Cardiac ArrhythmiasCardiology Division, Massachusetts General HospitalBostonMAUSA
| | - Mia Grayson
- Cardiovascular Research Center, Massachusetts General HospitalBostonMAUSA
| | - Jeffrey M. Ashburner
- Division of General Internal MedicineMassachusetts General HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Mostafa A. Al‐Alusi
- Cardiovascular Research Center, Massachusetts General HospitalBostonMAUSA
- Cardiology Division, Massachusetts General HospitalBostonMAUSA
| | - Yuchiao Chang
- Division of General Internal MedicineMassachusetts General HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Andrea Foulkes
- Harvard Medical SchoolBostonMAUSA
- Biostatistics Center, Massachusetts General HospitalBostonMAUSA
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General HospitalBostonMAUSA
- Demoulas Center for Cardiac ArrhythmiasCardiology Division, Massachusetts General HospitalBostonMAUSA
| | - David D. McManus
- Department of MedicineUniversity of Massachusetts T.H. Chan Medical SchoolWorcesterMAUSA
| | - Daniel E. Singer
- Division of General Internal MedicineMassachusetts General HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Steven J. Atlas
- Division of General Internal MedicineMassachusetts General HospitalBostonMAUSA
- Department of MedicineHarvard Medical SchoolBostonMAUSA
| | - Steven A. Lubitz
- Cardiovascular Research Center, Massachusetts General HospitalBostonMAUSA
- Demoulas Center for Cardiac ArrhythmiasCardiology Division, Massachusetts General HospitalBostonMAUSA
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V K, S PR. An effective healthcare monitoring system in an IoMT environment for heart disease detection using the HANN model. Comput Methods Biomech Biomed Engin 2024; 27:67-76. [PMID: 37622486 DOI: 10.1080/10255842.2023.2245521] [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: 05/09/2023] [Revised: 07/14/2023] [Accepted: 08/01/2023] [Indexed: 08/26/2023]
Abstract
The proposed work aims to develop an automated machine learning based network model for heart disease prediction with better accuracy. In the pre-processed data, the most significant features are selected using the White Shark Optimization based Linear Discriminant Analysis (WSO-LDA) technique, reducing computational complexity. Finally, the selected features are fed to the Hybrid Artificial Neural Network (HANN) with a Multi-Objective Spotted Hyena optimization (MOSHO) based classification stage. This stage classifies heart disease with minimized processing time.
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Affiliation(s)
- Karuppuchamy V
- Department of Computer Science and Engineering, PSNA College of Engineering and Technology (Autonomous), Dindigul, Tamil Nadu, India
| | - Palanivel Rajan S
- Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering (Autonomous), Coimbatore, Tamil Nadu, India
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Mensah Otabil E, Dai Q, Anzenberg P, Filippaios A, Ding E, Mehawej J, Mathew JE, Lessard D, Wang Z, Noorishirazi K, Hamel A, Paul T, DiMezza D, Han D, Mohagheghian F, Soni A, Lin H, Barton B, Saczynski J, Chon KH, Tran KV, McManus DD. Technology engagement is associated with higher perceived physical well-being in stroke patients prescribed smartwatches for atrial fibrillation detection. Front Digit Health 2023; 5:1243959. [PMID: 38125757 PMCID: PMC10731012 DOI: 10.3389/fdgth.2023.1243959] [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: 06/21/2023] [Accepted: 11/20/2023] [Indexed: 12/23/2023] Open
Abstract
Background Increasing ownership of smartphones among Americans provides an opportunity to use these technologies to manage medical conditions. We examine the influence of baseline smartwatch ownership on changes in self-reported anxiety, patient engagement, and health-related quality of life when prescribed smartwatch for AF detection. Method We performed a post-hoc secondary analysis of the Pulsewatch study (NCT03761394), a clinical trial in which 120 participants were randomized to receive a smartwatch-smartphone app dyad and ECG patch monitor compared to an ECG patch monitor alone to establish the accuracy of the smartwatch-smartphone app dyad for detection of AF. At baseline, 14 days, and 44 days, participants completed the Generalized Anxiety Disorder-7 survey, the Health Survey SF-12, and the Consumer Health Activation Index. Mixed-effects linear regression models using repeated measures with anxiety, patient activation, physical and mental health status as outcomes were used to examine their association with smartwatch ownership at baseline. Results Ninety-six participants, primarily White with high income and tertiary education, were randomized to receive a study smartwatch-smartphone dyad. Twenty-four (25%) participants previously owned a smartwatch. Compared to those who did not previously own a smartwatch, smartwatch owners reported significant greater increase in their self-reported physical health (β = 5.07, P < 0.05), no differences in anxiety (β = 0.92, P = 0.33), mental health (β = -2.42, P = 0.16), or patient activation (β = 1.86, P = 0.54). Conclusions Participants who own a smartwatch at baseline reported a greater positive change in self-reported physical health, but not in anxiety, patient activation, or self-reported mental health over the study period.
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Affiliation(s)
- Edith Mensah Otabil
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Qiying Dai
- Division of Cardiovascular Medicine, Department of Medicine, Saint Vincent Hospital, Worcester, MA, United States
| | - Paula Anzenberg
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Andreas Filippaios
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Eric Ding
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Jordy Mehawej
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Joanne E. Mathew
- Department of Internal Medicine, Central Michigan University, Mount Pleasant, MI, United States
| | - Darleen Lessard
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Ziyue Wang
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Kamran Noorishirazi
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Alexander Hamel
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Tenes Paul
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Danielle DiMezza
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Dong Han
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, United States
| | - Fahimeh Mohagheghian
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, United States
| | - Apurv Soni
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Honghuang Lin
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Bruce Barton
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - Jane Saczynski
- Department of Pharmacy and Health Systems Sciences, School of Pharmacy, Northeastern University, Boston, MA, United States
| | - Ki H. Chon
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, United States
| | - Khanh-Van Tran
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
| | - David D. McManus
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States
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Simonson JK, Anderson M, Polacek C, Klump E, Haque SN. Characterizing Real-World Implementation of Consumer Wearables for the Detection of Undiagnosed Atrial Fibrillation in Clinical Practice: Targeted Literature Review. JMIR Cardio 2023; 7:e47292. [PMID: 37921865 PMCID: PMC10656655 DOI: 10.2196/47292] [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: 03/14/2023] [Revised: 09/25/2023] [Accepted: 09/27/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Atrial fibrillation (AF), the most common cardiac arrhythmia, is often undiagnosed because of lack of awareness and frequent asymptomatic presentation. As AF is associated with increased risk of stroke, early detection is clinically relevant. Several consumer wearable devices (CWDs) have been cleared by the US Food and Drug Administration for irregular heart rhythm detection suggestive of AF. However, recommendations for the use of CWDs for AF detection in clinical practice, especially with regard to pathways for workflows and clinical decisions, remain lacking. OBJECTIVE We conducted a targeted literature review to identify articles on CWDs characterizing the current state of wearable technology for AF detection, identifying approaches to implementing CWDs into the clinical workflow, and characterizing provider and patient perspectives on CWDs for patients at risk of AF. METHODS PubMed, ClinicalTrials.gov, UpToDate Clinical Reference, and DynaMed were searched for articles in English published between January 2016 and July 2023. The searches used predefined Medical Subject Headings (MeSH) terms, keywords, and search strings. Articles of interest were specifically on CWDs; articles on ambulatory monitoring tools, tools available by prescription, or handheld devices were excluded. Search results were reviewed for relevancy and discussed among the authors for inclusion. A qualitative analysis was conducted and themes relevant to our study objectives were identified. RESULTS A total of 31 articles met inclusion criteria: 7 (23%) medical society reports or guidelines, 4 (13%) general reviews, 5 (16%) systematic reviews, 5 (16%) health care provider surveys, 7 (23%) consumer or patient surveys or interviews, and 3 (10%) analytical reports. Despite recognition of CWDs by medical societies, detailed guidelines regarding CWDs for AF detection were limited, as was the availability of clinical tools. A main theme was the lack of pragmatic studies assessing real-world implementation of CWDs for AF detection. Clinicians expressed concerns about data overload; potential for false positives; reimbursement issues; and the need for clinical tools such as care pathways and guidelines, preferably developed or endorsed by professional organizations. Patient-facing challenges included device costs and variability in digital literacy or technology acceptance. CONCLUSIONS This targeted literature review highlights the lack of a comprehensive body of literature guiding real-world implementation of CWDs for AF detection and provides insights for informing additional research and developing appropriate tools and resources for incorporating these devices into clinical practice. The results should also provide an impetus for the active involvement of medical societies and other health care stakeholders in developing appropriate tools and resources for guiding the real-world use of CWDs for AF detection. These resources should target clinicians, patients, and health care systems with the goal of facilitating clinician or patient engagement and using an evidence-based approach for establishing guidelines or frameworks for administrative workflows and patient care pathways.
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Venn RA, Khurshid S, Grayson M, Ashburner JM, Al-Alusi MA, Chang Y, Foulkes A, Ellinor PT, McManus DD, Singer DE, Atlas SJ, Lubitz SA. Characteristics and Attitudes of Wearable Device Users and Non-Users in a Large Healthcare System. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.10.23293960. [PMID: 37609134 PMCID: PMC10441501 DOI: 10.1101/2023.08.10.23293960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Introduction Consumer wearable devices with health and wellness features are increasingly common and may enhance prevention and management of cardiovascular disease. However, the characteristics and attitudes of wearable device users versus non-users are poorly understood. Methods Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology (WATCH-IT) was a prospective study of adults aged ≥18 years receiving longitudinal primary or ambulatory cardiovascular care at one of eleven hospitals within the Mass General Brigham multi-institutional healthcare system between January 2010-July 2021. We invited patients, including wearable users and non-users, to participate via an electronic patient portal. Participants were asked to complete a 20-question survey regarding perceptions and use of consumer wearable devices. Responses were linked to electronic health record data. Multivariable logistic regression was used to identify factors associated with device use. Results Among 280,834 individuals receiving longitudinal primary or cardiovascular care, 65,842 did not have an active electronic portal or opted out of research contact. Of the 214,992 individuals sent a survey link, 11,121 responded (5.2%), comprising the WATCH-IT patient sample. Most respondents (55.8%) reported current use of a wearable device, and most non-users (95.3%) reported they would use a wearable device if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, the majority believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR] 0.80 per 10-year increase, 95% CI 0.77-0.82), male sex (0.87, 95% CI 0.80-0.95), and heart failure (0.75, 95% CI 0.63-0.89) were associated with lower odds of wearable device use, whereas higher median zip code income (1.08 per 1-quartile increase, 95% CI 1.04-1.12) and care in a cardiovascular medicine clinic (1.17, 95% CI 1.05-1.30) were associated with greater odds of device use. Nearly all respondents (98%) stated they would share device data with researchers studying health outcomes. Conclusions Within an electronically assembled cohort of patients in primary and cardiovascular medicine clinics with linkage to detailed health records, wearable device use is common. Most users perceive value in wearable data. Our platform may enable future study of the relationships between wearable technology and resource utilization, clinical outcomes, and health disparities.
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Affiliation(s)
- Rachael A. Venn
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Shaan Khurshid
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mia Grayson
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jeffrey M. Ashburner
- Division of General Internal Medicine, Massachusetts General Hospital, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Mostafa A. Al-Alusi
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Yuchiao Chang
- Division of General Internal Medicine, Massachusetts General Hospital, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Andrea Foulkes
- Harvard Medical School, Boston, Massachusetts, United States of America
- Biostatistics Center, Massachusetts General Hospital, Boston, MA
| | - Patrick T. Ellinor
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - David D. McManus
- Department of Medicine, University of Massachusetts T.H. Chan Medical School, Worcester, Massachusetts, USA
| | - Daniel E. Singer
- Division of General Internal Medicine, Massachusetts General Hospital, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Steven J. Atlas
- Division of General Internal Medicine, Massachusetts General Hospital, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Steven A. Lubitz
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA
- Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
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Faro JM, Yue KL, Singh A, Soni A, Ding EY, Shi Q, McManus DD. Wearable device use and technology preferences in cancer survivors with or at risk for atrial fibrillation. CARDIOVASCULAR DIGITAL HEALTH JOURNAL 2022; 3:S23-S27. [PMID: 36589761 PMCID: PMC9795259 DOI: 10.1016/j.cvdhj.2022.08.002] [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: 01/04/2023] Open
Abstract
Background Cancer survivors face increased risk of heart disease, including atrial fibrillation (AF). Certain types of technology, such as consumer wearable devices, can be useful to monitor for AF, but little is known about wearables and AF monitoring in cancer survivor populations. Objective The purpose of this study was to understand technology usage and preferences in cancer survivors with or at risk for AF, and to describe demographic factors associated with wearable device ownership in this population. Methods Eligible patients completed a remote survey assessment regarding use of commercial wearable devices. The survey contained questions designed to assess commercial wearable device use, electronic health communications, and perceptions regarding the participant's cardiac health. Results A total of 424 cancer survivors (mean age 74.2 years; 53.1% female; 98.8% white) were studied. Although most participants owned a smartphone (85.9%), only 31.8% owned a wearable device. Over half (53.5%) of cancer survivors were worried about their heart health. Overall, patients believed arrhythmias (79.7%) were the most important heart condition for a wearable to detect. Survivors reported being most willing to share blood pressure (95.6%) and heart rate (95.3%) data with their providers and were least willing to share information about their diet, weight, and physical activity using these devices. Conclusion Understanding factors such as device ownership, usage, and heart health concerns in cancer survivors can play an important role in improving cardiovascular monitoring and its accessibility. Long-term patient outcomes may be improved by incorporating wearable devices into routine care of cancer survivors.
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Affiliation(s)
- Jamie M. Faro
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts,Address reprint requests and correspondence: Dr Jamie Faro, Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation St, Worcester, MA 01605.
| | - Kai-Lou Yue
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Aditi Singh
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Apurv Soni
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Eric Y. Ding
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
| | - Qiming Shi
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts
| | - David D. McManus
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
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Prieto-Avalos G, Cruz-Ramos NA, Alor-Hernández G, Sánchez-Cervantes JL, Rodríguez-Mazahua L, Guarneros-Nolasco LR. Wearable Devices for Physical Monitoring of Heart: A Review. BIOSENSORS 2022; 12:292. [PMID: 35624593 PMCID: PMC9138373 DOI: 10.3390/bios12050292] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 04/27/2022] [Accepted: 04/29/2022] [Indexed: 12/19/2022]
Abstract
Cardiovascular diseases (CVDs) are the leading cause of death globally. An effective strategy to mitigate the burden of CVDs has been to monitor patients' biomedical variables during daily activities with wearable technology. Nowadays, technological advance has contributed to wearables technology by reducing the size of the devices, improving the accuracy of sensing biomedical variables to be devices with relatively low energy consumption that can manage security and privacy of the patient's medical information, have adaptability to any data storage system, and have reasonable costs with regard to the traditional scheme where the patient must go to a hospital for an electrocardiogram, thus contributing a serious option in diagnosis and treatment of CVDs. In this work, we review commercial and noncommercial wearable devices used to monitor CVD biomedical variables. Our main findings revealed that commercial wearables usually include smart wristbands, patches, and smartwatches, and they generally monitor variables such as heart rate, blood oxygen saturation, and electrocardiogram data. Noncommercial wearables focus on monitoring electrocardiogram and photoplethysmography data, and they mostly include accelerometers and smartwatches for detecting atrial fibrillation and heart failure. However, using wearable devices without healthy personal habits will cause disappointing results in the patient's health.
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Affiliation(s)
- Guillermo Prieto-Avalos
- Tecnológico Nacional de México/I.T. Orizaba, Av. Oriente 9 No. 852 Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico; (G.P.-A.); (N.A.C.-R.); (L.R.-M.); (L.R.G.-N.)
| | - Nancy Aracely Cruz-Ramos
- Tecnológico Nacional de México/I.T. Orizaba, Av. Oriente 9 No. 852 Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico; (G.P.-A.); (N.A.C.-R.); (L.R.-M.); (L.R.G.-N.)
| | - Giner Alor-Hernández
- Tecnológico Nacional de México/I.T. Orizaba, Av. Oriente 9 No. 852 Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico; (G.P.-A.); (N.A.C.-R.); (L.R.-M.); (L.R.G.-N.)
| | - José Luis Sánchez-Cervantes
- CONACYT-Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852 Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico;
| | - Lisbeth Rodríguez-Mazahua
- Tecnológico Nacional de México/I.T. Orizaba, Av. Oriente 9 No. 852 Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico; (G.P.-A.); (N.A.C.-R.); (L.R.-M.); (L.R.G.-N.)
| | - Luis Rolando Guarneros-Nolasco
- Tecnológico Nacional de México/I.T. Orizaba, Av. Oriente 9 No. 852 Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico; (G.P.-A.); (N.A.C.-R.); (L.R.-M.); (L.R.G.-N.)
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