Constructing Bodily Emotion Maps Based on High-Density Body Surface Potentials for Psychophysiological Computing.

Emotion is a complex physiological and psychological activity, accompanied by subjective physiological sensations and objective physiological changes. The body sensation map describes the changes in body sensation associated with emotion in a topographic manner, but it relies on subjective evaluations from participants. Physiological signals are a more reliable measure of emotion, but most research focuses on the central nervous system, neglecting the importance of the peripheral nervous system.

A novel physiological feature selection method for emotional stress assessment based on emotional state transition.

The connection between emotional states and physical health has attracted widespread attention. The emotional stress assessment can help healthcare professionals figure out the patient's engagement toward the diagnostic plan and optimize the rehabilitation program as feedback. It is of great significance to study the changes of physiological features in the process of emotional change and find out subset of one or several physiological features that can best represent the changes of psychological state in a statistical sense.

EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review.

Epileptic seizure is one of the most chronic neurological diseases that instantaneously disrupts the lifestyle of affected individuals. Toward developing novel and efficient technology for epileptic seizure management, recent diagnostic approaches have focused on developing machine/deep learning model (ML/DL)-based electroencephalogram (EEG) methods. Importantly, EEG's noninvasiveness and ability to offer repeated patterns of epileptic-related electrophysiological information have motivated the development of varied ML/DL algorithms for epileptic seizure diagnosis in the recent years.

A Pilot Study on Long-term Physiological Signal Monitoring using Anhydrous Viscoplastic Electrodes.

Electrocardiography (ECG) and Electromyogram (EMG) are widely used to help physicians to diagnose various diseases. Besides, long-term physiological signals monitoring is of great significance for circumstances where certain diseases may not be observed in short-term monitoring. At present, wet electrodes are widely used in the clinic and are considered as a standard method to acquire physiological signals in high fidelity.

Spectrum power and brain functional connectivity of different EEG frequency bands in attention network tests.

There have been many previous studies on brain electrical activity and attention function, but the research on observing the cognitive function of attention from frequency brain electrical indicators remains insufficient. This study proposed an attentional network test (ANT) of Chinese version and used frequency analysis methods to observe the power spectrum activity and functional connectivity of delta (δ), theta (θ), alpha (α) bands of EEG signals to further understand their relationship with attention networks. The attentional network test was composed of alerting network, orienting network and execute conflict network, and these networks were compared with the resting state in different frequency bands.