Rapid detection of mild cognitive impairment using natural language processing
10.3760/cma.j.issn.0254-1424.2023.07.003
- VernacularTitle:基于自然语言处理技术的快速筛查在中国中老年人群轻度认知障碍中的应用
- Author:
Min PENG
1
;
Yaming ZHANG
;
Yongmei FAN
;
Miaoyuan ZHANG
;
Masashi ISHIMARU
;
Canyang LI
;
Lili JIAO
;
Rumi WANG
Author Information
1. 中南大学湘雅二医院康复医学科，长沙 410011
- Keywords:
Alzheimer′s disease;
Dementia;
Speech analysis;
Cognitive impairment;
Natural language processing;
Screening
- From:
Chinese Journal of Physical Medicine and Rehabilitation
2023;45(7):592-597
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To automatically and rapidly detect mild cognitive impairment (MCI) in an objective manner using natural language processing (NLP).Methods:A total of 215 participants (half female) aged 50 to 80 were recruited for the study′s normal cognition and MCI groups. Speech tasks and the mini mental state examination (MMSE-2) were used to collect audio data and quantify cognitive functioning. Altogether 162 acoustic features were extracted including the speaking speed, syllable number, syllable duration, number of pauses, duration of pauses, the standard deviation of formant frequency and sound pressure variation. They were compared between the two groups and genders. Multiple regression analysis was used to formulate a model predicting MCI. The sensitivity, specificity and accuracy of its predictions were used to evaluate its predictive power.Results:There were significant differences between the two groups in 50 acoustic features including their pronunciation rhythm and pronunciation accuracy. Univariate correlation analysis revealed that the pronunciation rhythm was significantly associated with cognitive functioning. The sensitivity, specificity and accuracy of the model were 0.54, 0.80 and 0.69 for males and 0.00, 0.86 and 0.63 for females.Conclusion:MCI greatly affects pronunciation rhythm. Acoustic analysis based on NLP can detect MCI rapidly and objectively.
