Physiological signal processing sits at the heart of nearly every modern medical device — from ICU ECG monitors and wrist pulse oximeters to FDA-cleared atrial-fibrillation detection in wearables. Turning a signal-processing technique into a verified, validated, regulator-ready algorithm takes a specific discipline.

This instructor-led online course walks through the canonical methods of biomedical signal processing — time, frequency, time-frequency and wavelet analysis; FIR and IIR filter design; adaptive filtering; Pan-Tompkins QRS detection; EEG and EMG feature extraction; and machine learning for physiological-signal classification. Each method is implemented in MATLAB or Python and validated against public reference datasets, alongside the regulatory framework for software as a medical device: IEC 62304, ISO 14971, and current FDA SaMD and AI/ML guidance.