US 12,433,530 B2
Voice characteristic-based method and device for predicting alzheimer's disease
Jun-Young Lee, Seoul (KR); and Hyunwoong Ko, Seoul (KR)
Assigned to EMOCOG CO., LTD., Seoul (KR)
Appl. No. 18/004,934
Filed by EMOCOG CO., LTD., Seoul (KR)
PCT Filed Jul. 8, 2021, PCT No. PCT/KR2021/008710
§ 371(c)(1), (2) Date Jan. 10, 2023,
PCT Pub. No. WO2022/010282, PCT Pub. Date Jan. 13, 2022.
Claims priority of application No. 10-2020-0085449 (KR), filed on Jul. 10, 2020; and application No. 10-2021-0089014 (KR), filed on Jul. 7, 2021.
Prior Publication US 2023/0233136 A1, Jul. 27, 2023
Int. Cl. A61B 5/00 (2006.01); G10L 25/66 (2013.01)
CPC A61B 5/4088 (2013.01) [A61B 5/7275 (2013.01); G10L 25/66 (2013.01)] 8 Claims
OG exemplary drawing
 
1. A device for predicting Alzheimer's disease, the device comprising:
a voice input unit configured to generate a voice sample by recording a voice of a subject;
a data input unit configured to receive demographic information of the subject;
a voice characteristic extraction unit configured to extract voice characteristics from the generated voice sample; and
a prediction model that is pre-trained to predict presence or absence of Alzheimer's disease in the subject, based on the voice characteristics and the demographic information,
wherein the prediction model comprises a multivariate logistic regression model that comprises at least one term determined by a combination of a plurality of first independent variables representing the voice characteristics, a plurality of second independent variables representing the demographic information, and a plurality of regression coefficients,
wherein the plurality of regression coefficients are trained to determine a decision boundary of the multivariate logistic regression model, and
wherein the multivariate logistic regression model is configured to output a dementia risk. probability value according to the plurality of first independent variables and the plurality of second independent variables using the decision boundary, and output state information that is determined as Alzheimer's disease or normal cognitive function based on the dementia risk probability value.