Regular and appropriate exercising facilitates rehabilitation from chronic diseases such as cardiovascular disease (CVD). Adherence to community-based exercise and rehabilitation programme is extremely low. It is known that less than 10% people with CVD adhere to such rehabilitation programmes due to lack of motivation, personal supervision or poor self-esteem to perform in a group. Use of wearables in the identification of the correctness in exercise performing and in providing feedback may solve adherence issues and encourage patients to take up home-based exercising for rehabilitation.
Ghanashyama Prabhu is with personal sensing team and working on human activity recognition such as exercise detection with machine learning algorithms using accurate data from smart, miniaturized, wearable sensors. Wearable sensors with 3D accelerometer and gyroscope can provide accurate translational and rotational data.