Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89493
Title: Assessment of patients with negative symptoms of schizophrenia from movement, and prosodic and conversational speech signals
Authors: Tan, Bhing-Leet
Lee, Jimmy
Chakraborty, Debsubhra
Yang, Zixu
Yasir, Tahir
Dauwels, Justin
Magnenat-Thalmann, Nadia
Keywords: Schizophrenia
Conversational Speech Signals
Social sciences::Sociology
Issue Date: 2018
Source: Chakraborty, 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.
Abstract: Negative 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%.
URI: https://hdl.handle.net/10356/89493
http://hdl.handle.net/10220/49700
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.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:IGS Conference Papers

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