Heartbeat detection from high-density EMG electrodes on the upper arm at different EMG intensity levels using Zephlet.

ABSTRACT

BACKGROUND AND OBJECTIVES: A significant number of global deaths caused by cardiac arrhythmias can be prevented with accurate and immediate identification. Wearable devices can play a critical role in such identification by continuously monitoring cardiac activity using electrocardiogram (ECG). The existing body of research has focused on extracting cardiac information from the body surface by investigating various electrode locations and algorithm development for ECG interpretation. The present study was designed for heartbeat detection using the signals recorded from the upper arm. METHODS: Firstly, optimal electrode locations on the upper arm were identified for Rest and elbow flexion (EF) conditions. Next, a synthesized ECG was generated using the selected electrodes with generalized weights over subjects and trials, and then zero-phase wavelet (Zephlet) was applied for feature extraction. Heartbeat detection was finally performed using the extracted detail coefficients incorporated with a multiagent detection scheme (MDS). RESULTS: The F1-score for heartbeat detection was 0.94  ±  0.16, 0.86  ±  0.22, 0.79  ±  0.26, and 0.67  ±  0.31 for Rest and EF with three different levels of muscle contraction (C1 to C3), respectively. Changing the acceptable distance between the detected and actual heartbeats from 50 ms to 20 ms, the F1-score changed to 0.81  ±  0.20, 0.66  ±  0.26, 0.57  ±  0.26,  and 0.44  ±  0.26 for Rest and C1 to C3, respectively. CONCLUSION: These findings make several contributions to the current literature, summarized as precise and consistent electrode localization for various muscle contraction levels and accurate heartbeat detection method development for each of these conditions.