[2F3-OS-4b] [Organized Session] OS-4

[2F3-OS-4b-04] A study on Detection of Symptoms of Dementia Based on Peak Latency of P300.

〇Koki Miwa¹, Tomohiro Yoshikawa¹, Takeshi Furuhashi¹, Minoru Hoshiyama², Taeko Makino³, Madoka Yanagawa⁴, Yusuke Suzuki⁵, Hiroyuki Umegaki⁶, Masahumi Kuzuya⁷ (1. Dept. of Information and Communication Eng., Graduate School of Eng., Nagoya University, 2. Brain & Mind Research Ceneter, Nagoya University, 3. School of Rehabilitation and Care, Seijo University, 4. Dept. of Geriatrics, Nagoya University Hospital, 5. Center for Community Liaison and Patient Consultations, Nagoya University Hospital, 6. Dept. of Community Healthcare and Geriatrics, Graduate School of Medicine, Nagoya University, 7. Institute of Innovation for Future Society / Dept. of Community Healthcare and Geriatrics, Graduate School of Medicine, Nagoya University)

Keywords:ERP (Event-related potential), P300, Dementia, Multiple Regression Analysis, MMSE (Mini Mental State Examination)

P300 is an enhanced positive component in EEG(Electroencephalogram) observed around 300ms after an Oddball stimulus is presented to a subject. It has been reported that the peak latency of P300 is dependent on the degree of task difficulty, age, educational background, and MMSE (Mini-Mental State Examination) score. The authors measured the peak latency of dementia patients attending the Geriatrics of Nagoya University hospital and identified a multiple regression equation with MMSE score as the objective variable. The 95% confidence interval of estimated MMSE was ±3.42. In this paper, a method to eliminate outliers of EEG data is employed. The 95% confidence interval was ±3.14, and the obtained model has a better ROC curve than that of a regression model without the outlier elimination.