activity
20202025
most citedUsing smartphones and wearable devices to monitor behavioural changes during COVID-19

204 citations · 331 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2025

Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity

Anastasiia Tokareva, Judith Dineley, Zoe Firth +19

Background: Remotely captured spoken language could provide objective, regular indicators of depression symptom severity. However, research to date has largely used non-clinical, c…

cs.CV2025★ 3 cited

An Explainable Anomaly Detection Framework for Monitoring Depression and Anxiety Using Consumer Wearable Devices

Yuezhou Zhang, Amos A. Folarin, Callum Stewart +7

Continuous monitoring of behavior and physiology via wearable devices offers a novel, objective method for the early detection of worsening depression and anxiety. In this study, w…

q-bio.QM2024

Large-scale digital phenotyping: identifying depression and anxiety indicators in a general UK population with over 10,000 participants

Yuezhou Zhang, Callum Stewart, Yatharth Ranjan +6

Digital phenotyping offers a novel and cost-efficient approach for managing depression and anxiety. Previous studies, often limited to small-to-medium or specific populations, may…

stat.AP2024

Deciphering seasonal depression variations and interplays between weather changes, physical activity, and depression severity in real-world settings: Learnings from RADAR-MDD longitudinal mobile health study

Yuezhou Zhang, Amos A. Folarin, Yatharth Ranjan +20

Prior research has shown that changes in seasons and weather can have a significant impact on depression severity. However, findings are inconsistent across populations, and the in…

cs.CL2023★ 1 cited

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model

Yuezhou Zhang, Amos A Folarin, Judith Dineley +25

Language use has been shown to correlate with depression, but large-scale validation is needed. Traditional methods like clinic studies are expensive. So, natural language processi…

stat.AP2020★ 123 cited

The Relationship between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multi-centre Longitudinal Observational Study

Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +19

Research in mental health has implicated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography, is not suitable for long-term, continu…

q-bio.QM2020★ 204 cited

Using smartphones and wearable devices to monitor behavioural changes during COVID-19

Shaoxiong Sun, Amos Folarin, Yatharth Ranjan +23

We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiti…