Low Cost Wearable Sensor for Human Emotion Recognition Using Skin Conductance Response

Khairun Nisa' MINHAD; Jonathan Shi Khai OOI; Sawal Hamid MD ALI; Mamun IBNE REAZ; Siti Anom AHMAD

doi:10.1587/transinf.2017EDP7067

Low Cost Wearable Sensor for Human Emotion Recognition Using Skin Conductance Response

Khairun Nisa' MINHAD, Jonathan Shi Khai OOI, Sawal Hamid MD ALI, Mamun IBNE REAZ, Siti Anom AHMAD

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Malaysia is one of the countries with the highest car crash fatality rates in Asia. The high implementation cost of in-vehicle driver behavior warning system and autonomous driving remains a significant challenge. Motivated by the large number of simple yet effective inventions that benefitted many developing countries, this study presents the findings of emotion recognition based on skin conductance response using a low-cost wearable sensor. Emotions were evoked by presenting the proposed display stimulus and driving stimulator. Meaningful power spectral density was extracted from the filtered signal. Experimental protocols and frameworks were established to reduce the complexity of the emotion elicitation process. The proof of concept in this work demonstrated the high accuracy of two-class and multiclass emotion classification results. Significant differences of features were identified using statistical analysis. This work is one of the most easy-to-use protocols and frameworks, but has high potential to be used as biomarker in intelligent automobile, which helps prevent accidents and saves lives through its simplicity.

Publication: IEICE TRANSACTIONS on Information Vol.E100-D No.12 pp.3010-3017

Publication Date: 2017/12/01

Publicized: 2017/08/23

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2017EDP7067

Type of Manuscript: PAPER

Category: Biological Engineering

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Khairun Nisa' MINHAD, Jonathan Shi Khai OOI, Sawal Hamid MD ALI, Mamun IBNE REAZ, Siti Anom AHMAD, "Low Cost Wearable Sensor for Human Emotion Recognition Using Skin Conductance Response" in IEICE TRANSACTIONS on Information, vol. E100-D, no. 12, pp. 3010-3017, December 2017, doi: 10.1587/transinf.2017EDP7067.
Abstract: Malaysia is one of the countries with the highest car crash fatality rates in Asia. The high implementation cost of in-vehicle driver behavior warning system and autonomous driving remains a significant challenge. Motivated by the large number of simple yet effective inventions that benefitted many developing countries, this study presents the findings of emotion recognition based on skin conductance response using a low-cost wearable sensor. Emotions were evoked by presenting the proposed display stimulus and driving stimulator. Meaningful power spectral density was extracted from the filtered signal. Experimental protocols and frameworks were established to reduce the complexity of the emotion elicitation process. The proof of concept in this work demonstrated the high accuracy of two-class and multiclass emotion classification results. Significant differences of features were identified using statistical analysis. This work is one of the most easy-to-use protocols and frameworks, but has high potential to be used as biomarker in intelligent automobile, which helps prevent accidents and saves lives through its simplicity.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017EDP7067/_p

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@ARTICLE{e100-d_12_3010,
author={Khairun Nisa' MINHAD, Jonathan Shi Khai OOI, Sawal Hamid MD ALI, Mamun IBNE REAZ, Siti Anom AHMAD, },
journal={IEICE TRANSACTIONS on Information},
title={Low Cost Wearable Sensor for Human Emotion Recognition Using Skin Conductance Response},
year={2017},
volume={E100-D},
number={12},
pages={3010-3017},
abstract={Malaysia is one of the countries with the highest car crash fatality rates in Asia. The high implementation cost of in-vehicle driver behavior warning system and autonomous driving remains a significant challenge. Motivated by the large number of simple yet effective inventions that benefitted many developing countries, this study presents the findings of emotion recognition based on skin conductance response using a low-cost wearable sensor. Emotions were evoked by presenting the proposed display stimulus and driving stimulator. Meaningful power spectral density was extracted from the filtered signal. Experimental protocols and frameworks were established to reduce the complexity of the emotion elicitation process. The proof of concept in this work demonstrated the high accuracy of two-class and multiclass emotion classification results. Significant differences of features were identified using statistical analysis. This work is one of the most easy-to-use protocols and frameworks, but has high potential to be used as biomarker in intelligent automobile, which helps prevent accidents and saves lives through its simplicity.},
keywords={},
doi={10.1587/transinf.2017EDP7067},
ISSN={1745-1361},
month={December},}

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TY - JOUR
TI - Low Cost Wearable Sensor for Human Emotion Recognition Using Skin Conductance Response
T2 - IEICE TRANSACTIONS on Information
SP - 3010
EP - 3017
AU - Khairun Nisa' MINHAD
AU - Jonathan Shi Khai OOI
AU - Sawal Hamid MD ALI
AU - Mamun IBNE REAZ
AU - Siti Anom AHMAD
PY - 2017
DO - 10.1587/transinf.2017EDP7067
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2017
AB - Malaysia is one of the countries with the highest car crash fatality rates in Asia. The high implementation cost of in-vehicle driver behavior warning system and autonomous driving remains a significant challenge. Motivated by the large number of simple yet effective inventions that benefitted many developing countries, this study presents the findings of emotion recognition based on skin conductance response using a low-cost wearable sensor. Emotions were evoked by presenting the proposed display stimulus and driving stimulator. Meaningful power spectral density was extracted from the filtered signal. Experimental protocols and frameworks were established to reduce the complexity of the emotion elicitation process. The proof of concept in this work demonstrated the high accuracy of two-class and multiclass emotion classification results. Significant differences of features were identified using statistical analysis. This work is one of the most easy-to-use protocols and frameworks, but has high potential to be used as biomarker in intelligent automobile, which helps prevent accidents and saves lives through its simplicity.
ER -