TY  - JOUR
AU  - Ding, Huitong
AU  - Mandapati, Amiya
AU  - Karjadi, Cody
AU  - Ang, Ting Fang Alvin
AU  - Lu, Sophia
AU  - Miao, Xiao
AU  - Glass, James
AU  - Au, Rhoda
AU  - Lin, Honghuang
PY  - 2022
DA  - 2022/12/22
TI  - Association Between Acoustic Features and Neuropsychological Test Performance in the Framingham Heart Study: Observational Study
JO  - J Med Internet Res
SP  - e42886
VL  - 24
IS  - 12
KW  - mild cognitive impairment
KW  - digital voice
KW  - neuropsychological test
KW  - association
KW  - prediction
AB  - Background: Human voice has increasingly been recognized as an effective indicator for the detection of cognitive disorders. However, the association of acoustic features with specific cognitive functions and mild cognitive impairment (MCI) has yet to be evaluated in a large community-based population. Objective: This study aimed to investigate the association between acoustic features and neuropsychological (NP) tests across multiple cognitive domains and evaluate the added predictive power of acoustic composite scores for the classification of MCI. Methods: This study included participants without dementia from the Framingham Heart Study, a large community-based cohort with longitudinal surveillance for incident dementia. For each participant, 65 low-level acoustic descriptors were derived from voice recordings of NP test administration. The associations between individual acoustic descriptors and 18 NP tests were assessed with linear mixed-effect models adjusted for age, sex, and education. Acoustic composite scores were then built by combining acoustic features significantly associated with NP tests. The added prediction power of acoustic composite scores for prevalent and incident MCI was also evaluated. Results: The study included 7874 voice recordings from 4950 participants (age: mean 62, SD 14 years; 4336/7874, 55.07% women), of whom 453 were diagnosed with MCI. In all, 8 NP tests were associated with more than 15 acoustic features after adjusting for multiple testing. Additionally, 4 of the acoustic composite scores were significantly associated with prevalent MCI and 7 were associated with incident MCI. The acoustic composite scores can increase the area under the curve of the baseline model for MCI prediction from 0.712 to 0.755. Conclusions: Multiple acoustic features are significantly associated with NP test performance and MCI, which can potentially be used as digital biomarkers for early cognitive impairment monitoring. 
SN  - 1438-8871
UR  - https://www.jmir.org/2022/12/e42886
UR  - https://doi.org/10.2196/42886
UR  - http://www.ncbi.nlm.nih.gov/pubmed/36548029
DO  - 10.2196/42886
ID  - info:doi/10.2196/42886
ER  -