ArticleSensors (Basel, Switzerland)2021
Emotion Recognition Based on Skin Potential Signals with a Portable Wireless Device.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Affective Response Dataset for Virtual Workspaces: Based on Color Stimuli and Multimodal Physiological Signals.Sensors (Basel, Switzerland) · 2025Article
- Longitudinal observation of psychophysiological data as a novel approach to personalised postural defect rehabilitation.Scientific reports · 2025Article
- An AI recognition method for children's clinical operative pain by skin potential (SP) signal.Heliyon · 2025Article
- Emotional recognition technologies applied to health: review and challenges.Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999) · 2025Review
- Task-state skin potential abnormalities can distinguish major depressive disorder and bipolar depression from healthy controls.Translational psychiatry · 2024Article
- Affective Impressions Recognition under Different Colored Lights Based on Physiological Signals and Subjective Evaluation Method.Sensors (Basel, Switzerland) · 2023Article
- Emotion Detection Based on Pupil Variation.Healthcare (Basel, Switzerland) · 2023Article
- An AI-Inspired Spatio-Temporal Neural Network for EEG-Based Emotional Status.Sensors (Basel, Switzerland) · 2023Article
- Design of Service Robot Based on User Emotion Recognition and Environmental Monitoring.Journal of environmental and public health · 2022Article
- Article
- Affective State during Physiotherapy and Its Analysis Using Machine Learning Methods.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Emotion recognition is of great importance for artificial intelligence, robots, and medicine etc. Although many techniques have been developed for emotion recognition, with certain successes, they rely heavily on complicated and expensive equipment. Skin potential (SP) has been recognized to be correlated with human emotions for a long time, but has been largely ignored due to the lack of systematic research. In this paper, we propose a single SP-signal-based method for emotion recognition. Firstly, we developed a portable wireless device to measure the SP signal between the middle finger and left wrist. Then, a video induction experiment was designed to stimulate four kinds of typical emotion (happiness, sadness, anger, fear) in 26 subjects. Based on the device and video induction, we obtained a dataset consisting of 397 emotion samples. We extracted 29 features from each of the emotion samples and used eight well-established algorithms to classify the four emotions based on these features. Experimental results show that the gradient-boosting decision tree (GBDT), logistic regression (LR) and random forest (RF) algorithms achieved the highest accuracy of 75%. The obtained accuracy is similar to, or even better than, that of other methods using multiple physiological signals. Our research demonstrates the feasibility of the SP signal's integration into existing physiological signals for emotion recognition.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.