The adoption of wireless health monitoring is encouraging to boost the quality of lifespan for chronic sick patients and the old people, as well as healthy one –. With the growth in the proportions of the adult and elderly population, as well as the emergence of chronic diseases and syndromes because of the ups and downs in lifestyle, there has been a necessity to monitor and analyze the health status of individuals in their daily living to avoid fatal conditions. The strategy of physiological measurement systems has been a mounting research attention in the last decade, due to the possible applications in medicine, sports, and security. The cardiac auscultation monitoring system may provide a way for heart disease self-management. Preprocessing, segmentation and clustering technique were performed for significant health information interpretation. Subsequence segmentation algorithm based on double-threshold has been developed to extract physiological parameters. The Hilbert-Huang transform is used to eliminate interference signals and to help to extract the heart sound signal features. #HEART MONITOR SOUND BLUETOOTH#Bluetooth protocol is used to offer power efficiency and moderate data transmission rate. Cardiac auscultation sensing unit has been designed to monitor cardiovascular health of an individual. An integrated system for heart sound acquisition, storage, asynchronous analysis has been developed, from scratch to information uploading through IoT and signal analysis. In this paper, a novel wireless sensing system to monitor and analyze cardiac condition is proposed, which sends the information to the caregiver as well as a medical practitioner with an application of the Internet of Things (IoT). #HEART MONITOR SOUND MANUAL#Wireless cardiac auscultation offers continuous cardiac monitoring of an individual without 24*7 manual healthcare care services. Heart sounds deliver vital physiological and pathological evidence about health. Preprocessing, segmentation, and clustering technique were performed for significant health information interpretation. The Hilbert–Huang transform is used to eliminate interference signals and to help to extract the heart sound signal features. An integrated system for heart sound acquisition, storage, and asynchronous analysis has been developed, from scratch to information uploading through IoT and signal analysis.
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