204 citations · 480 across the 17 of their papers we have counts for
17 papers
Longitudinal wearable monitoring and polygenic risk for incident major depressive disorder in the All of Us Research Program
Yuezhou Zhang, Amos A. Folarin, Rongrong Zhong +4
Major depressive disorder (MDD) risk reflects both stable inherited liability and dynamic behavioral patterns, yet these dimensions are rarely examined together using long-term obj…
Preoperative Decline and Postoperative Recovery of Wearable-Derived Physical Activity Over a Four-Year Perioperative Period in Total Knee and Hip Arthroplasty: Evidence from the All of Us Research Program
Yuezhou Zhang, Amos Folarin, Callum Stewart +4
Total knee arthroplasty (TKA) and total hip arthroplasty (THA) improve symptoms in end-stage osteoarthritis, yet long-term objective characterization of perioperative physical acti…
Physical Activity Trajectories Preceding Incident Major Depressive Disorder Diagnosis Using Consumer Wearable Devices in the All of Us Research Program: Case-Control Study
Yuezhou Zhang, Amos Folarin, Hugh Logan Ellis +7
Low physical activity is a known risk factor for major depressive disorder (MDD), but changes in activity before a first clinical diagnosis remain unclear, especially using long-te…
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…
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…
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…
Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +24
Objective: This study aimed to explore the associations between depression severity and wearable-measured circadian rhythms, accounting for seasonal impacts and quantifying seasona…
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…
Disease Insight through Digital Biomarkers Developed by Remotely Collected Wearables and Smartphone Data
Zulqarnain Rashid, Amos A Folarin, Yatharth Ranjan +7
Digital Biomarkers and remote patient monitoring can provide valuable and timely insights into how a patient is coping with their condition (disease progression, treatment response…
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis
Shaoxiong Sun, Amos A. Folarin, Yuezhou Zhang +28
A number of challenges exist for the analysis of mHealth data: maintaining participant engagement over extended time periods and therefore understanding what constitutes an accepta…
Associations between depression symptom severity and daily-life gait characteristics derived from long-term acceleration signals in real-world settings
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +27
Gait is an essential manifestation of depression. Laboratory gait characteristics have been found to be closely associated with depression. However, the gait characteristics of dai…
The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions
Shaoxiong Sun, Amos A Folarin, Yuezhou Zhang +25
Multiple sclerosis (MS) is a progressive inflammatory and neurodegenerative disease of the central nervous system affecting over 2.5 million people globally. In-clinic six-minute w…
Predicting Depressive Symptom Severity through Individuals' Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal Study
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +21
The Bluetooth sensor embedded in mobile phones provides an unobtrusive, continuous, and cost-efficient means to capture individuals' proximity information, such as the nearby Bluet…
Fitbeat: COVID-19 Estimation based on Wristband Heart Rate
Shuo Liu, Jing Han, Estela Laporta Puyal +26
This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilise…
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…
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…
Personalized acute stress classification from physiological signals with neural processes
Callum L. Stewart, Amos Folarin, Richard Dobson
Objective: A person's affective state has known relationships to physiological processes which can be measured by wearable sensors. However, while there are general trends those re…