Please use this identifier to cite or link to this item:
Title: Automated socio-cognitive assessment of patients with schizophrenia and depression
Authors: Xu, Shihao
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Xu, S. (2022). Automated socio-cognitive assessment of patients with schizophrenia and depression. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: This thesis analyzed the speech, facial expressions, and body movement recordings of schizophrenia and depression patients in two separate studies. The first study was conducted from 2014 to 2016, which included the recruitment of the cohort. The study was conducted with 58 patients with schizophrenia and 29 healthy controls over three sessions: at week 0, week 2, and week 12. The second study was conducted between 2017 and 2019 involving 50 patients with depression, 50 patients with schizophrenia, and 50 healthy control subjects, where only one session was conducted for each participant. In both studies, all subjects spoke English and were matched in age, gender, educational background, and ethnicity. Patients were then selected for persistent and predominantly negative symptoms with minimal positive symptoms. The baseline session of the first study was combined with the second study for model training and leave-one-out cross-validation, resulting in a total of 228 participants (103 patients with schizophrenia, 50 patients with depression, and 75 healthy controls), where 5 schizophrenia patients and 4 controls were excluded due to equipment malfunction or error in the consent form.
Schools: School of Electrical and Electronic Engineering 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
Thesis_NTU_Shihao_Final.pdf12.75 MBAdobe PDFThumbnail

Page view(s)

Updated on Mar 1, 2024


Updated on Mar 1, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.