Unsupervised Identification of Cardiac Contraction through Ballistocardiography
Our researchers at Dozee --Vibhor Saran, Udit Dhawan, and Gaurav Parchani -- co-authored a publication titled ‘Unsupervised Identification of Cardiac Contraction through Ballistocardiography’. The paper proposed a novel algorithm to detect individual heartbeats from BCG data with a higher detection rate as well as accuracy better than previously proposed techniques.
The proposed algorithm is able to achieve an accuracy of 93.81% for individual heartbeats with a detection rate of 92.59%, and an accuracy of 98.39% for 30-second epochs with a detection rate of 99.46% compared to a standard ECG machine. This is the same algorithm that Dozee uses every night to determine the heart rate.
Published On: 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)
Authors: Vibhor Saran, Gulshan Kumar. Udit Dhawan, Gaurav Parchani