Heartbeat detection from the upper arm using an SWT-based zero-phase filter bank incorporated with a voting Scheme

Electrocardiogram (ECG) signal provides a graphical representation of cardiac activity and is the most commonly adopted clinical tool for cardiac abnormalities detection. Heartbeat detection, as the first step in analyzing ECG signals, is required for an accurate diagnosis. Stationary wavelet transform (SWT) as a commonly used algorithm for heartbeat detection has a disadvantage of phase shift regarding the original signal. This work addresses this issue by presenting a new method that incorporates an SWT-based zero-phase filter bank with a voting scheme. Our results indicated that a superior performance in heartbeat detection was achieved from the upper arm compared to conventional SWT with a more accurate localization. We achieved sensitivity (SE) and positive predictive value (PPV) of 0.98±0.04 and 0.95±0.09 with the most distance of 50 ms from the actual heartbeats. The SE and PPV changed to 0.75±0.15 and 0.73±0.16, respectively for the distance of 20 ms. Clinical Relevance- The proposed method can be later implemented in wearable devices for convenient cardiac activity monitoring from upper arm or other none-conventional sites.