Abstract
Cardiovascular diseases are the leading cause of death worldwide. Due to advancements facilitating the integration of electric and adhesive technologies, long-term patch electrocardiogram (ECG) monitors (PEMs) are currently used to conduct daily continuous cardiac function assessments. This paper presents an ECG encoding scheme for joint lossless data compression and heartbeat detection to minimize the circuit footprint size and power consumption of a PEM. The proposed encoding scheme supports two operation modes: fixed-block mode and dynamic-block mode. Both modes compress ECG data losslessly, but only dynamic-block mode supports the heartbeat detection feature. The whole encoding scheme was implemented on a C-platform and tested with ECG data from MIT/BIH arrhythmia databases. A compression ratio of 2.1 could be achieved with a normal heartbeat. Dynamic-block mode provides heartbeat detection accuracy at a rate higher than 98%. Fixed-block mode was also implemented on the field-programmable gate array, and could be used as a chip for using analog-to-digital convertor-ready signals as an operation clock.
Highlights
According to the World Health Organization, cardiovascular diseases (CVD) are the leading cause of death worldwide [1]
2011, 37% of these deaths were caused by CVD, and 82% of them lived in low and middle-income countries, where people often do not have access to integrated primary health care programs for the early detection and treatment of such illnesses
The cost of CVD treatment escalates quickly with the rapidly increasing requirements for supervision and medical management, and traditional health care infrastructures are overwhelmed by the demands of effective late-stage treatment
Summary
According to the World Health Organization, cardiovascular diseases (CVD) are the leading cause of death worldwide [1]. An estimated 17.7 million people died from CVD in 2015, representing 31% of all global deaths. The cost of CVD treatment escalates quickly with the rapidly increasing requirements for supervision and medical management, and traditional health care infrastructures are overwhelmed by the demands of effective late-stage treatment. Such costs can potentially be reduced by using systems that monitor individuals in the course of their daily activities, which would reduce the need for inpatient care or visits to the primary physician
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