Development of medical device software for the screening and assessment of depression severity using data collected from a wristband-type wearable device: SWIFT study protocol

• Published in: Frontiers in psychiatry Vol. 13; p. 1025517
• Main Authors: Kishimoto, Taishiro, Kinoshita, Shotaro, Kikuchi, Toshiaki, Bun, Shogyoku, Kitazawa, Momoko, Horigome, Toshiro, Tazawa, Yuki, Takamiya, Akihiro, Hirano, Jinichi, Mimura, Masaru, Liang, Kuo-ching, Koga, Norihiro, Ochiai, Yasushi, Ito, Hiromi, Miyamae, Yumiko, Tsujimoto, Yuiko, Sakuma, Kei, Kida, Hisashi, Miura, Gentaro, Kawade, Yuko, Goto, Akiko, Yoshino, Fumihiro
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 21.12.2022
• Subjects: depression; digital health; machine learning; personalized medicine; Psychiatry; wearables; wearables; digital health; depression; machine learning; personalized medicine

Few biomarkers can be used clinically to diagnose and assess the severity of depression. However, a decrease in activity and sleep efficiency can be observed in depressed patients, and recent technological developments have made it possible to measure these changes. In addition, physiological change...