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CVD tops the list of public health concern compared to other diseases and has almost become the primary cause of human deaths, as per a survey of the World Health Organization (WHO).The main causes include changings trend in lifestyle, unhealthy eating habits, tobacco usage, low fruit and vegetable intake and lack of physical activity and lot of stress.These factors necessitate developing a personalised CVD monitoring device powered by battery backup and with a very low form factor to achieve unobtrusiveness that works under the emerging cyber-physical system setup."CVD is one of the deadliest disease and irrespective of the economy of the country people are getting affected by it. It is manifested in different forms necessitating the early diagnosis, therapy and prognosis. Hence the proposed work on the classification is going to be of immense help for the society," said Amit Acharyya, Associate Professor, Department of Electrical Engineering, IIT Hyderabad.In addition, they also worked on developing different classification techniques and integrating them to make a generic algorithm.A novel System-On-Chip (SoC) architecture is developed in a low complex way by resource sharing concept for the CVD automation.Thus the whole system can cover various ECG abnormalities and finally come up with the prototype board which looks similar to as a smartphone at the patient end."There is an exponential increment in human mortality rate, due to the delayed diagnosis, lack of proper distribution of health care facilities and prognosis centers in the vicinity. There is a need of a robust automated device for the early detection of the vital abnormal ECG signals in chronic CVD patients," said Vemishetty Naresh from IIT Hyderabad.This medical science and technological needs impose many challenges on such device development such as low power consuming system design tradeoff between the on-board processing and RF (Radio Frequency) communication, low complexity analog front-end circuit design and energy harvesting or self-power mechanism to prolong battery life.With the present advancement in technology, there is a great scope for developing robust medical ECG devices in analysing the ECG signals and classify the patient condition.This method will predict the departure from the healthy condition to unhealthy condition corresponding to the CVDs.( With inputs from IANS )

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