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dc.contributor.authorPhothisonothai M.
dc.contributor.authorTantisatirapong S.
dc.date.accessioned2021-04-05T03:03:25Z-
dc.date.available2021-04-05T03:03:25Z-
dc.date.issued2019
dc.identifier.other2-s2.0-85065102320
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12437-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85065102320&doi=10.1109%2fKST.2019.8687804&partnerID=40&md5=4f6bf8f3f8f1c153152cadf7869cdbc7
dc.description.abstractHuman-Machine Interaction (HMI) requires a multidisciplinary research study mainly focused on interaction modalities between humans and machines. In this paper, we introduced an integrated HMI system using electrical brainwave signal (or called Electroencephalography: EEG) and eye tracking of pupil movement (or called ET), whose are used as an alternative channel to communicate with others for people with disabilities. In this experiment, the target and non-Target visual stimuli of EEG-based HMI system on the basis of event-related potential (ERP) and steady state visually evoked potential (SSVEP) signals have been performed. For the ET based framework, we proposed the user-friendly virtual keyboard typing for Thai language, i.e., free-form and automatic typing modes. The results showed that the integrated HMI using ERP-SSVEP yielded an average accuracy of 97.4% and reaction time approximately was 724.2 millisecond for control commands. The automatic typing mode performed an average accuracy of 97%, with an average printing time of 6.17 seconds per word for ET based virtual Thai keyboard. © 2019 IEEE.
dc.subjectElectroencephalography
dc.subjectElectrophysiology
dc.subjectEnterprise resource planning
dc.subjectEye movements
dc.subjectHuman computer interaction
dc.subjectHuman reaction time
dc.subjectMan machine systems
dc.subjectEEG signals
dc.subjectEvent-related potentials
dc.subjectHuman machine interaction
dc.subjectHuman machine interaction system
dc.subjectInteractive system
dc.subjectMulti-disciplinary research
dc.subjectSSVEP
dc.subjectSteady state visually evoked potentials
dc.subjectEye tracking
dc.titleIntegrated Human-Machine Interaction System: ERP-SSVEP and Eye Tracking Based Technologies
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitation2019 11th International Conference on Knowledge and Smart Technology, KST 2019. (2019), p.244-248
dc.identifier.doi10.1109/KST.2019.8687804
Appears in Collections:Scopus 1983-2021

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