Reliable, Real-Time, Low Cost Cardiac Health Monitoring System for Affordable Patient Care

Abstract

It is increasingly being made aware by various organizations including the WHO (World Health Organization) that Cardiovascular Disease (CVD) is the 'Silent Killer' and is the perhaps the most important cause for death globally in the present times. The prime reason being the fact that CVD often goes unnoticed at the early stages and clinical intervention is soughted only during emergency. A thorough understanding of the nature of the disease reveals the association of physiological abnormalities and subdued physiological disorders that might have raised due to stress, lifestyle related disorders, pathological conditions etc. Studies have revealed that all these problems if addressed to at an early stage can be controlled and the potential risks and hazards lessened to a considerable extent. Early detection is possible in developed countries with expensive and advanced machineries, which can keep the data recorded in a user-friendly device affordable by the patient. But in a developing country like ours a low cost affordable device is yet to be available to the rural population especially addressing the problem. The aim of this study is to design an affordable and reliable Cardiac Health Monitoring platform for identification, data storage and availability to the physician even after a considerable time interval for diagnosis of the condition and post diagnosis continued therapy. The Cardiac Health Monitoring Systems (CHMS) was developed to capture and pre-process physiological parameters (ECG, Heart Sound, Heart Rate in Normal, Stressed and Physiologically abnormal conditions) in real-time and transmit the same using wired as well as wireless communication technology. The CHMS has been so designed is designed to capture the patient's/user's physiological parameters in electrical form e.g. the ECG signal, apply preliminary adaptive filtering to shape the requisite signals and forward the processed data. This data is acquired by Smart hand held mobile device, and the excess processing power of the device is utilized for further processing as well as storage of medical records and transmission of data to the hospital management system or for isolated diagnosis and assessment. Critical readings crossing the set threshold (per WHO standards) would set off an alarm [locally as well as over the mobile network] and thus alert any imminent life-threatening situation.

An Insight on Machine Learning Algorithms for Predicting Heart Diseases

“…Dutta, Dutta, Sikdar, Dutta, Sharma and Sharma [10] designed a Cardiac Health Monitoring System (CHMS) to identify cardiac abnormalities in less computational cost targeting low and middle masses. The input for CHMS was audio signal obtained through a digital stethoscope.…”