Psychophysiological Recording: Signals, Uses and Configurations

Electrocardiography (ECG) records the electrical activity of the heart. Timing differences between successive cardiac cycles can be used to derive heart rate and heart-rate variability (HRV), which describes variation in the time interval between successive heartbeats.

HRV interpretation depends on recording duration, signal quality, respiration, posture, physical activity and the chosen time- or frequency-domain measures. Contemporary reporting guidance therefore emphasizes detailed documentation of acquisition conditions and analysis steps. [1]

Electrodermal activity (EDA) reflects changes in skin conductance that are driven mainly by sympathetic control of sweat glands. The term galvanic skin response (GSR) is also widely used in this area. [2]

EDA is commonly decomposed into slower tonic activity, meaning the background skin-conductance level, and faster phasic responses, meaning shorter event-related changes. These signals are sensitive to general physiological arousal, while inference about a specific emotion or psychological state requires experimental context and complementary measures.

Psychophysiological recording is useful when a study needs objective measures of autonomic, cardiac, respiratory or muscular change alongside behaviour or self-report.

Respiratory dynamics can be measured using chest or abdominal belts, airflow sensors, pressure systems or gas analysis. Respiratory rate and depth are especially important when interpreting HRV and autonomic physiology. [3]

Electromyography (EMG) records electrical activity from muscle. Surface electromyography (surface EMG), in which electrodes on the skin measure electrical activity generated by underlying muscle, is widely used in movement science, rehabilitation, biomechanics and facial psychophysiology. Electrode placement, cross-talk, movement artefacts and normalization require standardized methodology. [4,5]

Synchronized acquisition makes it possible to align EEG, ECG, EDA, respiration, EMG, behavioural responses and experimental events on the same timeline. This can show how multiple systems change during the same task or stimulus.

The quality of a multimodal experiment depends not only on individual sensors but also on shared timing, signal-quality control and a prespecified analysis strategy.

A psychophysiology setup can be built around one signal or around a synchronized sensor suite. The configuration should follow the scientific question and required mobility.