Universiti Teknologi Malaysia Institutional Repository

GSR signals features extraction for emotion recognition

Kipli, Kuryati and Abdul Latip, Aisya Amelia and Lias, Kasumawati and Bateni, Norazlina and Mohamad Yusoff, Salmah and Tajudin, Nurul Mirza Afiqah and Jalil, M. A. and Ray, Kanad and Kaiser, M. Shamim and Mahmud, Mufti (2022) GSR signals features extraction for emotion recognition. In: 1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021, 16 December 2021 - 17 December 2021, Virtual, Online.

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Official URL: http://dx.doi.org/10.1007/978-981-16-8826-3_28


Over the years, the recognition of emotion has become more efficient, diverse, and easily accessible. In general, emotion recognition is conducted in four main steps which are signal acquisition, preprocessing, feature extraction, and classification. Galvanic skin response (GSR) is the autonomic activation of sweat glands in the skin when an individual gets triggered through emotional stimulation. The paper provides an overview of emotion recognition, GSR signals, and how GSR signals are analyzed for emotion recognition. The focus of this research is on the performance of feature extraction of GSR signals. Therefore, related sources were identified using combinations of keywords and terms such as feature extraction, emotion recognition, and galvanic skin response. Existing emotion recognition methods were investigated which focused more on the different feature extraction methods. Research conducted has shown that feature extraction method in time–frequency domain has the best accuracy rate overall compared to time domain and frequency domain. Current GSR-based technology also has the potential to be improved more toward the implementation of a more efficient and reliable emotion recognition system.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:emotion recognition, feature extraction, galvanic skin response
Subjects:Q Science > QC Physics
ID Code:98736
Deposited By: Yanti Mohd Shah
Deposited On:02 Feb 2023 16:06
Last Modified:02 Feb 2023 16:06

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