Investigating the Feasibility of Assessing Depression Severity and Valence-Arousal with Wearable Sensors Using Discrete Wavelet Transforms and Machine Learning

Investigating the Feasibility of Assessing Depression Severity and Valence-Arousal with Wearable Sensors Using Discrete Wavelet Transforms and Machine Learning

Depression is one of the most common mental health disorders, affecting approximately 280 million people worldwide. This condition is defined as emotional dysregulation resulting in persistent feelings of sadness, loss of interest and inability to experience pleasure. Early detection can facilitate...

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Bibliographic Details
Main Authors: Abdullah Ahmed, Jayroop Ramesh, Sandipan Ganguly, Raafat Aburukba, Assim Sagahyroon, Fadi Aloul
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Information
Subjects:
affective
depression screening
digital phenotype
emotion
machine learning
passive sensing
Online Access:https://www.mdpi.com/2078-2489/13/9/406

Internet

https://www.mdpi.com/2078-2489/13/9/406

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