Associations Between Depression Symptom Severity and Daily-Life Gait Characteristics Derived From Long-Term Acceleration Signals in Real-World Settings: Retrospective Analysis.
Yuezhou ZhangAmos A FolarinShaoxiong SunNicholas CumminsSrinivasan VairavanLinglong QianYatharth RanjanZulqarnain RashidPauline CondeCallum StewartPetroula LaiouHeet SankesaraFaith MatchamKatie M WhiteCarolin OetzmannAlina IvanFemke LamersSara SiddiSara K SimblettAki RintalaDavid C MohrInez Myin-GermeysTil WykesJosep-Maria HaroBrenda W J H PenninxVaibhav A NarayanPeter AnnasMatthew HotopfRichard James Butler Dobsonnull nullPublished in: JMIR mHealth and uHealth (2022)
This study indicated that the significant links between daily-life walking characteristics and depression symptom severity could be captured by both wearable devices and mobile phones. The daily-life gait patterns could provide additional information for predicting depression symptom severity relative to laboratory walking. These findings may contribute to developing clinical tools to remotely monitor mental health in real-world settings.