78 citations · 154 across the 4 of their papers we have counts for
4 papers
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…
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…
Remote smartphone-based speech collection: acceptance and barriers in individuals with major depressive disorder
Judith Dineley, Grace Lavelle, Daniel Leightley +22
The ease of in-the-wild speech recording using smartphones has sparked considerable interest in the combined application of speech, remote measurement technology (RMT) and advanced…