期刊
JOURNAL OF SUPERCOMPUTING
卷 78, 期 11, 页码 13680-13709出版社
SPRINGER
DOI: 10.1007/s11227-022-04387-6
关键词
Heart rate variability; Smoothed pseudo Wigner-Ville Distribution; Support Vector Machine; Mutual information; Feature selection; Adaptive structure learning; Transport layer security
类别
资金
- Directorate General of Scientific Research and Technological Development (Direction Generale de la Recherche Scientifique et du Developpement Technologique, DGRSDT)
Heart rate variability signal is a valuable tool for cardiovascular system diagnostics, used to detect arrhythmia and abnormalities in the autonomic nervous system. Quadratic time-frequency analysis of the signal can help detect various cardiovascular pathologies. A client-server telemedical platform was developed for real-time remote monitoring of cardiovascular function in arrhythmia patients, allowing immediate interaction in case of alarms.
The heart rate variability signal is a valuable tool for cardiovascular system diagnostics. Processing this signal detects arrhythmia during long-term cardiac monitoring. It is also analyzed to recognize abnormalities within the autonomic nervous system. Processing this signal helps in detecting various pathologies, such as atrial fibrillation (AF), supraventricular tachycardia (SVT), and congestive heart failure (CHF). As a beneficial alternative to the commonly used HRV spectrum analysis, quadratic time-frequency analysis of HRV signals could be helpful in heart pathology detection. Indeed, in this study, we have created a client-server paradigm deployed as a telemedical platform for real-time remote monitoring of the cardiovascular function in patients suffering from arrhythmia. This platform detects arrhythmia in real-time by deploying time-frequency analysis, feature extraction, feature selection, and classification of Heart Rate Variability (HRV) signals. We gathered all these functionalities in a Graphical User Interface (GUI) in addition to data acquisition. As a client, a Raspberry Pi Zero ensures data acquisition and connects to a server over TCP/IP that involves a 4G/3G connection encrypted through the transport layer security (TLS). This telemedical tool continuously monitors the heart rate variability. In the case of an alarm, medical professionals may immediately interact with their patients in the hospital or at home.
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