Details

Autor(en) / Beteiligte

• Yin, Wenyi
• Yu, Chenghao
• Wu, Pianran
• Jiang, Wenxuan
• Liu, Youzhe
• Ren, Tianqi
• Dai, Weihui

Titel

An Intelligent Mobile System for Monitoring Relapse of Depression

Ist Teil von

• Computer Supported Cooperative Work and Social Computing, p.182-193

Ort / Verlag

Singapore: Springer Nature Singapore

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Depression is a common psychological disorder with high relapse rate in modern society. Due to weak self-perception and fear of public bias, most relapse patients fail to receive timely treatment. Aiming to provide a self-monitoring means in home environment and daily life, this paper studied the machine learning and natural language processing technologies for extracting the patient’s acoustic features and semantic features from the designed speech diagnostic test, and proposed an improved CNN-LSTM learning model suitable for the monitoring, which can combine acoustic features, semantic features, weather and environmental information as well as the patient’s personalized features for achieving ideal results. On this basis, an intelligent mobile system is designed for daily monitoring on the relapse of depression.