Human emotion classifications for automotive driver using skin conductance response signal

Khairun Nisa'Minhad, Sawal Hamid Md Ali, Jonathan Ooi Shi Khai, Siti Anom Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Risky driving, speeding, and fatigue are the main causes of traffic accidents in Malaysia. Risky driving is an attitude associated with human states of emotion. Emotions detected using facial and body movements, sounds and physiological changes which required multiple and bulky instruments such as camera, voice recorder and sensors. In this study, skin conductance response (SCR) was investigated to overcome these drawback. The main goal of this study is to recognize human emotions by using a nonintrusive sensor and low-design-complexity protocols. Five emotions, namely, happiness, sadness, disgust, fear, and anger, were identified to have a close relationship with risky driving. The emotions were elicited by using image, video-audio, and video stimulus techniques and 960 Hz raw signal sampling rate was recorded. The video clip stimulus method showed 95.7% efficacy in detecting happiness and anger. The affective assessment classification rate obtained from SCR processing was more than 70% accuracy based on the off-line support vector machine classifier-processing algorithm. Overall results confirmed that the SCR signal should be considered in the future as one of the physiological signals in automated real-time emotions recognition systems.

Original languageEnglish
Title of host publication2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages371-375
Number of pages5
ISBN (Electronic)9781509028894
DOIs
Publication statusPublished - 27 Mar 2017
Event2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016 - Putrajaya, Malaysia
Duration: 14 Nov 201616 Nov 2016

Other

Other2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
CountryMalaysia
CityPutrajaya
Period14/11/1616/11/16

Fingerprint

emotions
Skin
Signal sampling
Highway accidents
Sensors
Processing
stimuli
Support vector machines
Classifiers
Cameras
Acoustic waves
Fatigue of materials
fear
Malaysia
clips
recorders
sensors
accidents
classifiers
traffic

Keywords

  • Electrodermal activity
  • Skin conductance response
  • Support vector machine

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Biomedical Engineering
  • Control and Systems Engineering
  • Hardware and Architecture
  • Computer Networks and Communications
  • Instrumentation

Cite this

Nisa'Minhad, K., Md Ali, S. H., Khai, J. O. S., & Ahmad, S. A. (2017). Human emotion classifications for automotive driver using skin conductance response signal. In 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016 (pp. 371-375). [7888072] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAEES.2016.7888072

Human emotion classifications for automotive driver using skin conductance response signal. / Nisa'Minhad, Khairun; Md Ali, Sawal Hamid; Khai, Jonathan Ooi Shi; Ahmad, Siti Anom.

2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 371-375 7888072.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nisa'Minhad, K, Md Ali, SH, Khai, JOS & Ahmad, SA 2017, Human emotion classifications for automotive driver using skin conductance response signal. in 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016., 7888072, Institute of Electrical and Electronics Engineers Inc., pp. 371-375, 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016, Putrajaya, Malaysia, 14/11/16. https://doi.org/10.1109/ICAEES.2016.7888072
Nisa'Minhad K, Md Ali SH, Khai JOS, Ahmad SA. Human emotion classifications for automotive driver using skin conductance response signal. In 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 371-375. 7888072 https://doi.org/10.1109/ICAEES.2016.7888072
Nisa'Minhad, Khairun ; Md Ali, Sawal Hamid ; Khai, Jonathan Ooi Shi ; Ahmad, Siti Anom. / Human emotion classifications for automotive driver using skin conductance response signal. 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 371-375
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