Early Detection of Dementia by Advancing Speech Analysis and Bayesian-Based Data Mining

2015 Fiscal Year Final Research Report

• Project/Area Number: 25540146
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Web informatics, Service informatics
• Research Institution: Nagoya Institute of Technology
• Principal Investigator: Kato Shohei 名古屋工業大学, 工学(系)研究科(研究院), 教授 (70311032)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 認知症スクリーニング / 医療・福祉サービス / 発話音声解析 / 加齢工学

Outline of Final Research Achievements

In this research, we have developed a novel data-mining approach for detection of cognitive impairment, SPCIR (Speech Prosody-Based Cognitive Impairment Rating), which can discriminate between mild cognitive impairment and mild Alzheimer’s disease from elderly using prosodic sign extracted from elderly speech during questionnaire test. This study proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection using receiver operating characteristic (ROC) curve analysis, and confirmed acceptable discriminative performance of the sensitivity and specificity of SPCIR for diagnosis (control; mild cognitive impairment/mild Alzheimer’s disease).

Free Research Field

人工知能、知能感性ロボティクス、医工連携情報処理