**2.3. Physiological modality**

Physiological signals can be used for affect recognition through the detection of biological patterns that are reflective of emotional expressions. These signals are collected through typically noninvasive sensors that are affixed to the body of the subject. However, brain imaging [80] and remote physiological monitoring schemes [81, 82] have been proposed.

There are a multitude of physiological signals that can be analyzed for affect detection. Typical physiological signals used for the assessment of affect are electrocardiography (ECG), electromyography (EMG), electroencephalograph (EEG), skin conductance (also known as galvanic skin response, and electrodermal activity), respiration rate, and skin temperature. ECG records the electrical activity of the heart. Conventionally, 12 electrodes are connected to various parts of the body to conduct this measurement. However, in affective computing, most systems use the Lead I configuration that requires only two electrodes [6]. From the ECG signal, the heart rate (HR) and heart rate variability (HRV) can be extracted. HRV is used in numerous studies that assess mental stress [6, 83–85]. EMG measures muscle activity and is known to reflect negatively valenced emotions [86]. EEG is the electrical activity of the brain measured through electrodes connected to the scalp and possibly forehead. There is little agreement on the number of electrodes to use or features to extract from EEG. EEG features are often used to classify emotional dimensions of arousal [87–90], valence [88–90], and dominance [90, 91]. Skin conductance measures the resistance of the skin by passing a negligible current through the body. The resulting signal is reflective of arousal [86] as it corresponds to the activity of the sweat glands. The latter are controlled by the autonomous nervous system (ANS) that regulates the flight or fight response. Finally, respiration rate tends to reflect arousal [92], while skin temperature carries valence cues [93].
