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The continuous monitoring of cardiac patients requires an ambulatory system that can automatically detect heart diseases. This study presents a new field programmable gate array (FPGA)-based hardware implementation of the QRS complex detection. The proposed detection system is mainly based on the Pan and Tompkins algorithm, but applying a new, simple, and efficient technique in the detection stage. The new method is based on the centred derivative and the intermediate value theorem, to locate the QRS peaks. The proposed architecture has been implemented on FPGA using the Xilinx System Generator for digital signal processor and the Nexys-4 FPGA evaluation kit. To evaluate the effectiveness of the proposed system, a comparative study has been performed between the resulting performances and those obtained with existing QRS detection systems, in terms of reliability, execution time, and FPGA resources estimation. The proposed architecture has been validated using the 48 half-hours of records obtained from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. It has also been validated in real time via the analogue discovery device.

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Due to the rising number of cardiovascular diseases death, the monitoring of cardiac patients has become a primary objective in the world. In this context, a fully FPGA-based system, for ECG signal monitoring and cardiac arrhythmia detection, has been proposed. The proposed QRS detection method is inspired by the Pan and Tompkins algorithm. It is optimized to be implemented in FPGA board Spartan 3 E (Nexys 2) using the VHDL language on the Xilinx ISE 14.2. In order to evaluate the effectiveness and reliability of our system, three comparative studies have been performed. The first comparison targeted the different results obtained with a floating-point representation under Matlab on one hand, and a fixed point representation under Xilinx ISE on the other hand, both using the MIT-BIH arrhythmia database records. The second comparison concerns the results obtained from the records of eight preselected subjects, with a commercialized electronic armband device ROMED BP-WR20 in a real-time test. The third is a comparison between the performance of our proposed method with the recent works in terms of reducing the FPGA resources list. The full embedded system has been realized completely from the signal acquisition to the display using the analog discovery device. The designed architecture has been validated using records obtained from the Massachusetts Institute of Technology — Beth Israel Hospital (MIT-BIH) arrhythmia database. It has also been validated in real-time via the analog discovery device. The overall accuracy and sensitivity are obtained as 97.6% and 97.3%, respectively.

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