ADVANCED ELECTRONIC NOISE REDUCTION FOR BIOMEDICAL SIGNALS IN EMERGENCY MEDICAL SYSTEMS
Keywords:
Signals, Noise, Emergency Medicine, Filtering, ElectronicAbstract
Reliable acquisition of biomedical signals in emergency medical systems is often degraded by motion artifacts, power-line interference, baseline wander, and electrode noise, leading to diagnostic uncertainty. This study presents advanced electronics-based noise reduction methods integrating analog front-end optimization with digital adaptive filtering for real-time biomedical signal enhancement. A low-noise instrumentation amplifier (input-referred noise < 1 µVrms, CMRR > 110 dB) is combined with active notch (50/60 Hz attenuation > 40 dB) and high-pass filtering (cutoff 0.5 Hz) to suppress baseline drift. The conditioned signals are further processed using adaptive least mean squares (LMS) and wavelet denoising techniques. Experimental validation was performed on electrocardiogram (ECG) datasets with signal-to-noise ratios (SNR) ranging from −5 dB to 10 dB under simulated emergency conditions. Results demonstrate an average SNR improvement of 18.7 dB, noise reduction of 72%, and QRS detection accuracy increase from 85.3% to 97.6%. The proposed system achieves processing latency below 20 ms, making it suitable for real-time deployment. These findings confirm that integrating advanced electronic design with adaptive algorithms significantly enhances biomedical signal reliability in time-critical emergency medical environments.
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