A Review of Individual Differences from Transfer Learning

Li, Jingjing; Wang, Qiang

doi:10.1134/s1019331622040189

Cited by 1 publication

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“…They first collected data on brain signals of driving anger when drivers encountered three typical scenarios that could lead to driving anger, and then distinguished normal driving from angry driving according to the self-reported data; finally, a classifier was used to detect angry driving based on the features, and 85.0% detection accuracy was obtained. Li and Wang [43] described the research status of cognitive training and analyzed the reasons for individual cognitive differences. They investigated cognitive neural plasticity for reducing the cognitive differences, explored the merits and drawbacks of the transfer approach in reducing cognitive differences, and put forward future research issues.…”

Section: Type Ofmentioning

confidence: 99%

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Lin

2023

Applied Sciences

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People’s emotions play an important part in our daily life and can not only reflect psychological and physical states, but also play a vital role in people’s communication, cognition and decision-making. Variations in people’s emotions induced by external conditions are accompanied by variations in physiological signals that can be measured and identified. People’s psychological signals are mainly measured with electroencephalograms (EEGs), electrodermal activity (EDA), electrocardiograms (ECGs), electromyography (EMG), pulse waves, etc. EEG signals are a comprehensive embodiment of the operation of numerous neurons in the cerebral cortex and can immediately express brain activity. EDA measures the electrical features of skin through skin conductance response, skin potential, skin conductance level or skin potential response. ECG technology uses an electrocardiograph to record changes in electrical activity in each cardiac cycle of the heart from the body surface. EMG is a technique that uses electronic instruments to evaluate and record the electrical activity of muscles, which is usually referred to as myoelectric activity. EEG, EDA, ECG and EMG have been widely used to recognize and judge people’s emotions in various situations. Different physiological signals have their own characteristics and are suitable for different occasions. Therefore, a review of the research work and application of emotion recognition and judgment based on the four physiological signals mentioned above is offered. The content covers the technologies adopted, the objects of application and the effects achieved. Finally, the application scenarios for different physiological signals are compared, and issues for attention are explored to provide reference and a basis for further investigation.

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Section: Type Ofmentioning

confidence: 99%

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Lin

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

A Review of Individual Differences from Transfer Learning

Cited by 1 publication

References 52 publications

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

Review of Studies on Emotion Recognition and Judgment Based on Physiological Signals

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