Machine Learning and Deep Learning for Physiological Signal Processing

Summary

Physiological signal processing is essential in healthcare and biomedical research, as it enables the extraction of meaningful information from complex biological signals, such as heart rate, brain waves, and muscle activity. By analysing these signals, clinicians and researchers can gain insights into the body's functioning and detect anomalies that may indicate health conditions, support early diagnosis, and guide treatment decisions. This project aims to develop machine learning (ML) and deep learning (DL) techniques algorithms to analyse and interpret complex biomedical signals like ECG, EEG, and EMG.

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