Cardiovascular diseases (CVD) are one of the leading causes of death in rural India. Every year more than 3 million Indian citizens die from CVD [1]. The proposed Wearable Wireless Cardiac Monitoring (WiCard) system, aims to bring home state-of-the-art health care for people living in rural Indian villages, where thousands of death occur each year due to lack of experts and facilities. The architecture involves remote monitoring of the ECG by specialized health professionals via a heterogeneous wireless network. This paper discusses the development of a six lead custom hardware for transmitting data to a Smartphone or a compatible device via a Bluetooth. The data received by the mobile devices will be further processed and transmitted to a central repository located in a specialized hospital. The main disadvantage of wearable cardiac monitoring system is the introduction of Motion Induced Artifacts (MIA), which could mimic a cardiac event. A context aware architecture is proposed here to relate physical activity and physiological signals of the user, with the help of accelerometer sensors. The portion of ECG where the MIA has detected will be tagged and sent to the central repository. Classifications of physical movements are done using statistics based classifiers, which are computationally low cost. The results show that the developed algorithm is capable of classifying the user activity with an accuracy of 94%. The developed hardware achieved a power reduction of 10 %.
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