An Optimized Field Programmable Gate Array Based Noise Reduction Techniques for Fetal Electrocardiogram Signal Processing

Analyzing fetal electrocardiogram (FECG) signals is essential for identifying fetal cardiac disorders early on, although noise interference is still a problem. Conventional signal processing techniques can produce conflicting findings. With an emphasis on three important noise reduction methods the Kalman Filter, Discrete wavelet transform, and Finite impulse response this study evaluates the performance of the PYNQZ2 and NEXYS A 7 Field Programmable Gate Array (FPGA) boards in real-time FECG signal monitoring. With a mean squared error of 0.58% and a signal-to-noise ratio of 31.1 dB, the Kalman Filter fared better than the other filters, especially when it came to lowering dynamic noise in real-time applications. Furthermore, the PYNQ Z2 was outperformed by the NEXYS A7 board at processing FECG signals efficiently. effectively. By providing insights into the best noise reduction strategies and improving the accuracy of FECG monitoring in biomedical applications, this comparative analysis advances FPGA-based signal processing systems.