dc.contributor.authorChakraborty, Debsubhra
dc.contributor.authorYang, Zixu
dc.contributor.authorYasir, Tahir
dc.contributor.authorDauwels, Justin
dc.contributor.authorMagnenat-Thalmann, Nadia
dc.contributor.authorTan, Bhing-Leet
dc.contributor.authorLee, Jimmy
dc.date.accessioned2019-08-20T07:39:19Z
dc.date.available2019-08-20T07:39:19Z
dc.date.issued2018
dc.identifier.citationChakraborty, D., Yang, Z., Yasir, T., Dauwels, J., Magnenat-Thalmann, N., Tan, B.-L., & Lee, J. (2018). Assessment of patients with negative symptoms of schizophrenia from movement, and prosodic and conversational speech signals. Conference of the IEEE Engineering in Medicine and Biology Society.
dc.identifier.urihttp://hdl.handle.net/10220/49700
dc.description.abstractNegative symptoms of schizophrenia are often characterized by speech and motor impairments. Therefore, in this paper we combine audio (prosody and conversation) and video (body movement) signals to distinguish patients (43) from healthy control (23) subjects. First, we used these different modalities individually as features in machine learning algorithms yielding an accuracy of 67-79%. Next, we combined the different modalities as features, improving the accuracy to 85%.en_US
dc.description.sponsorshipNMRC (Natl Medical Research Council, S’pore)en_US
dc.format.extent1 p.en_US
dc.language.isoenen_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.subjectSchizophreniaen_US
dc.subjectConversational Speech Signalsen_US
dc.subjectSocial sciences::Sociologyen_US
dc.titleAssessment of patients with negative symptoms of schizophrenia from movement, and prosodic and conversational speech signalsen_US
dc.typeConference Paper
dc.contributor.conferenceConference of the IEEE Engineering in Medicine and Biology Societyen_US
dc.contributor.schoolInterdisciplinary Graduate School (IGS)en_US
dc.description.versionAccepted versionen_US


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