Skip to Main Content
This paper aims to present a very-large-scale integration (VLSI) friendly electrocardiogram (ECG) QRS detector for body sensor networks. Baseline wandering and background noise are removed from original ECG signal by a mathematical morphological method. Then the multipixel modulus accumulation is employed to act as a low-pass filter to enhance the QRS complex and improve the signal-to-noise ratio. The performance of the algorithm is evaluated with standard MIT-BIH arrhythmia database and wearable exercise ECG Data. Corresponding power and area efficient VLSI architecture is designed and implemented on a commercial nano-FPGA. High detection rate and high speed demonstrate the effectiveness of the proposed detector.