• Rohan Pardeshi
• Prof. Aditya Mishra

Microcontroller-based vital-sign monitors are cheap, but they struggle once real-time waveform analysis and wireless reporting are required at the same time. This paper examines whether shifting the heaviest part of that workload — QRS detection — into reconfigurable hardware improves the trade-off. A prototype was built on a ZYBO Z7-20 board around a Xilinx Zynq-7000 SoC. The programmable-logic side runs a streaming R-peak detector adapted from the Pan-Tompkins algorithm; the on-chip ARM core reads an NTC thermistor for temperature, packages both readings, and sends them over UART to an ESP8266 Wi-Fi module for display on a web dashboard. Two rounds of testing were carried out — first against simulator-generated ECG traces, then on a live subject. The detector held up well under motion-related noise in both cases, and the complete loop settled into roughly one-second update cycles once deployed, a delay traced mainly to the wireless reporting interval rather than to the FPGA itself. FPGA resource utilization remained well under 5% of available LUTs, and only six DSP48E1 slices were used, confirming that the QRS core was never the system bottleneck. The results suggest that SoC-class FPGAs offer a reasonable middle ground for this kind of monitoring — more capable than a bare microcontroller, and cheaper and smaller than clinical-grade equipment.

FPGA, Zynq SoC, IoT, QRS Detection, Electrocardiogram (ECG), Pan-Tompkins Algorithm, XADC, Health Monitoring, Wireless Data Transmission

"LOW-LATENCY ECG-BASED HEALTH MONITORING USING HARDWARE-ACCELERATED QRS DETECTION ON SOC FPGA WITH IOT REPORTING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 9, page no.b656-b663, September-2026, Available :http://www.jetir.org/papers/JETIR2609172.pdf

"LOW-LATENCY ECG-BASED HEALTH MONITORING USING HARDWARE-ACCELERATED QRS DETECTION ON SOC FPGA WITH IOT REPORTING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 9, page no. ppb656-b663, September-2026, Available at : http://www.jetir.org/papers/JETIR2609172.pdf