Exploring Voice Acoustic Features Associated with Cognitive Status in Korean Speakers: A Preliminary Machine Learning Study

Exploring Voice Acoustic Features Associated with Cognitive Status in Korean Speakers: A Preliminary Machine Learning Study

<b>Objective</b>: To develop a non-invasive cognitive impairment detection system using speech data analysis, addressing the growing global dementia crisis and enabling accessible early screening through daily health monitoring. <b>Methods</b>: Speech data from 223 Korean pat...

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Bibliographic Details
Main Authors: Jiho Lee, Nayeon Kim, Ji-Wan Ha, Kyunghun Kang, Eunhee Park, Janghyeok Yoon, Ki-Su Park
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Diagnostics
Subjects:
cognitive impairment
pre-screening
K-MMSE
speech features
speech tasks
deep learning
Online Access:https://www.mdpi.com/2075-4418/14/24/2837
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