Description

This Master Prompt develops research frameworks for acquiring, processing and interpreting physiological signals in biomedical monitoring, wearable sensing, rehabilitation and human–machine interaction. It addresses electroencephalography, electromyography, electrocardiography, photoplethysmography, arterial pressure and other relevant measurements according to the available evidence. Drawing on the supplied studies of physiological signal cleansing, EEG frequency-band fusion, time-resolved neural decoding, sEMG-based force estimation and radar sensing, it connects signal quality with physiological interpretation and task-specific validation. Particular attention is given to participant characteristics, recording conditions, reference-label quality, artifacts, temporal alignment, individual variability and independent evaluation. The framework distinguishes technical feasibility from clinical usefulness, within-participant prediction from generalization to new users, and reconstructed waveforms from directly observed physiology. It supports transparent reporting of ethical procedures, uncertainty, computational requirements and the limitations of translating experimental performance into practical monitoring or assistive systems.