Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/12468
ชื่อเรื่อง: Stress classification system for intelligent wheelchair
ผู้แต่ง: Sueaseenak D.
Apichontivong P.
Sripitak P.
Sukplang S.
Keywords: Disabled persons
Heart
Physiological models
Stresses
Support vector machines
Wheelchairs
Heart rates
Intelligent wheelchair
Physiological signals
Stress classifications
Stress detection
Video game
Signal detection
วันที่เผยแพร่: 2019
บทคัดย่อ: This research has developed a stress detection system for the disabled person who uses a wheelchair based on physiological signals. Physiological signals that we used to detect stress are galvanic skins response (GSR) and heart rate (HR), these parameters were collected from BIOPAC. The GSR was detected by 2 sensors on fingertips at the left forefinger and middle finger. Heart rate was detected by 3 sensors one on the left wrist and two on the ankles. The video game was selected to stimulate stress from 7 subjects during 19-21 years old. The proposed method consists of several parts which are (i) the feature extraction by MAV, (ii) Classification by Support Vector Machine (SVM). The experiment results of our proposed method show that the system has stress detection rate 97.1 percent and non-stress detection rate 100 percent. The result is very promising. © 2019 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/12468
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074876588&doi=10.1109%2fLifeTech.2019.8883963&partnerID=40&md5=e8deb0326d42d69f08c1ba08bdc1bdca
Appears in Collections:Scopus 1983-2021

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