Predictive Model for Detection of Depression Based on Uncertainty Analysis Methods

Proceedings

Hernández, Yasmín¹  Benítez, Richard²  Estrada, Hugo³  Martínez, Alicia⁴ 

[1] Author to whom correspondence should be addressed.;INFOTEC Center for Research and Innovation in Information Technology and Communications, Mexico City 14050, Mexico;National Institute of Electricity and Clean Energy, Information Technology Management, Cuernavaca, Morelos 62490, Mexico;National Institute of Technology of Mexico/CENIDET, Cuernavaca, Morelos 62490, Mexico

关键词: depression;    fuzzy rules;    older adults;    predictive model;   

DOI  :  10.3390/proceedings2190551

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

: Currently, advances in technology have permitted increases in the life expectancy of older adults. As a result, a large segment of the world population is 60’s years old, and over. Depression is an important disease in older adults is depression, which seriously affects the moods and behavior of elderly. Novel technologies for smart cities allow us to monitor people and prevent problematic situations related to this mental illness. In this paper, we propose a predictive model to automatically detect depression in older adults. The model is based on machine-learning techniques to analyze the data obtained by a sensor that monitores the daily activities of older adults. Also, the model was evaluated obtaining promising results.

【 授权许可】

CC BY