Signal Filtering and Peak Analysis of Ballistocardiography for Heartbeat Detection

Ballistocardiography (BCG) signal is an alternative to classical electocardiography (ECG) in several healthcare applications, because his non-contact feature. However, signal weakness and vulnerability to multiple sources of noise due to the high sensibility acquisition is a challenge for it. In order to design and test new algorithms for BCG processing, the ICBHI 2022 held the fourth edition of the Scientific Challenge Competition for biomedical purposes such as non-invasive cardiac monitoring and signal processing of BCG. This research followed the methods based on the Pan-Tompkins algorithm for detection of QRS complexes in ECG signals with a database composed by 4 datasets of healthy volunteers (before and after excersise) and patients with atrial fibrillation (AF). Peak prominence of the signal to find local maxima was selected as the main function for processing data and comparison between BCG and ECG signals of the subjects. Score metrics established by ICBHI to assess the algorithm error showed that initial results for the first and second phase a score of 5686.2 and 3349.1 respectively, thus concluding that the algorithm proposed in the present research project based on the Scientific Challenge proved to have acceptable performance to detect heartbeats based on BCG signal datasets for both volunteers and patients subjects.