Machine Learning for Healthcare Wearable Devices: The Big Picture
المؤلف | Sabry, Farida |
المؤلف | Eltaras, Tamer |
المؤلف | Labda, Wadha |
المؤلف | Alzoubi, Khawla |
المؤلف | Malluhi, Qutaibah |
تاريخ الإتاحة | 2024-07-17T07:14:42Z |
تاريخ النشر | 2022 |
اسم المنشور | Journal of Healthcare Engineering |
المصدر | Scopus |
المعرّف | http://dx.doi.org/10.1155/2022/4653923 |
الرقم المعياري الدولي للكتاب | 20402295 |
الملخص | Using artificial intelligence and machine learning techniques in healthcare applications has been actively researched over the last few years. It holds promising opportunities as it is used to track human activities and vital signs using wearable devices and assist in diseases' diagnosis, and it can play a great role in elderly care and patient's health monitoring and diagnostics. With the great technological advances in medical sensors and miniaturization of electronic chips in the recent five years, more applications are being researched and developed for wearable devices. Despite the remarkable growth of using smart watches and other wearable devices, a few of these massive research efforts for machine learning applications have found their way to market. In this study, a review of the different areas of the recent machine learning research for healthcare wearable devices is presented. Different challenges facing machine learning applications on wearable devices are discussed. Potential solutions from the literature are presented, and areas open for improvement and further research are highlighted. |
راعي المشروع | This publication was made possible by a grant from the Qatar National Research Fund (QNRF), project number ECRA 01-006-1-001. |
اللغة | en |
الناشر | John Wiley and Sons Inc |
الموضوع | Diagnosis Health care Machine learning Disease diagnosis Elderly care Health care application Human activities Machine learning applications Machine learning techniques Machine-learning Patient health Vital sign Wearable devices Wearable technology applied research artificial intelligence blood volume computer security daily life activity data privacy elderly care emotion falling heart arrhythmia heart rate human hydration interpersonal communication machine learning medical research memory consolidation miniaturization patient monitoring physiological stress plantar pressure rehabilitation remote sensing Review seizure sleep telemonitoring aged artificial intelligence electronic device health care delivery health care facility machine learning Aged Artificial Intelligence Delivery of Health Care Health Facilities Humans Machine Learning Wearable Electronic Devices |
النوع | Article Review |
الصفحات | - |
رقم المجلد | 2022 |
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