Early Detection of Dementia by Advancing Speech Analysis and Bayesian-Based Data Mining
| Project/Area Number |
25540146
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Web informatics, Service informatics
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| Research Institution | Nagoya Institute of Technology |
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Principal Investigator |
Kato Shohei 名古屋工業大学, 工学(系)研究科(研究院), 教授 (70311032)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2015: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2014: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2013: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| 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 / 発話音韻解析 / 多重ロジスティック回帰分析 / ROC解析 |
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| 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).
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Report
(4 results)
Research Products
(48 results)
