JSAI2023

Presentation information

General Session

General Session » GS-10 AI application

[2E1-GS-10] AI application

Wed. Jun 7, 2023 9:00 AM - 10:40 AM Room E (A2)

座長:上村 健人(富士通) [現地]

10:00 AM - 10:20 AM

[2E1-GS-10-04] Binary Classification Prediction of Cognitive Status Using Sleep Activity Data

〇Shinichi Sugiura1, Kou Murase1, Keita Ando1, Shinichiro Yokoyama2, Ken Inoue2, Shogo Okada1 (1. Japan Advanced Institute of Science and Technology, 2. George and Shaun, Inc)

Keywords:Machine Learning, dementia, sleep, classification

The sleep patterns of patients with dementia have been observed to be affected. This study aims to investigate the feasibility of developing a machine learning model that can classify scores of dementia screening tests based on sleep activity data that can be collected with minimal burden on participants.

Data on sleep activity was collected from 124 elderly patients with varying levels of cognitive ability. The Mini Mental State Estimation (MMSE) cognitive test scores were used to determine the cognitive states of the patients.

To classify the dementia scale and identify individuals with low-MMSE, we employed an efficient sequence model to capture time-series changes in sleep activity. Using LSTM models, a maximum macro F1 score of 0.67 was achieved in the bina

Authentication for paper PDF access

A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.

Password