Low-Cost High-Accuracy QRS Detection for Body Area Network Applications
In this study, the low-cost So and Chan (SC) detection method for body area network is combined with the moving average and distance calculation methods for detecting R-waves. The proposed method is compared to existing methods in terms of noise immunity, R-wave detection accuracy, and heartbeat error percent (HBEP). The arrhythmia database provided by the Massachusetts Institute of Technology and Beth Israel Hospital is used. The proposed method effectively reduced HBEP compared to that of the traditional SC method (2.072 vs. 8.518%). R-wave detection verification is conducted using a field-programmable gate array development board, with the obtained R_point data imported into MATLAB for data comparison.