Yuezhou Zhang

发表

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

M. Hotopf, R. Dobson, B. Penninx, 2020, 2009.12983.

A VISUALIZATION ANALYSIS OF HOTSPOTS AND TRENDS OF INTERNATIONAL ENTREPRENEURSHIP RESEARCH

Yuezhou Zhang, Rui Yi, Qiu Huang, 2021, 2021 INTERNATIONAL CONFERENCE ON ADVANCED EDUCATION AND INFORMATION MANAGEMENT (AEIM 2021).

Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon

Wanguo Xue, Leo Anthony Celi, Desen Cao, 2017, JMIR medical informatics.

Temporal Evolution of Multiday, Epileptic Functional Networks Prior to Seizure Occurrence

A. Schulze-Bonhage, J. Winston, M. Richardson, 2022, medRxiv.

Challenges in the analysis of mobile health data from smartphones and wearable devices to predict depression symptom severity

M. Hotopf, B. Penninx, V. Narayan, 2022, 2212.10540.

Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study

M. Hotopf, D. Mohr, B. Penninx, 2021, JMIR mental health.

The Longitudinal relationships between depressive symptom severity and phone-measured mobility: an application of dynamic structural equation modeling (Preprint)

M. Hotopf, D. Mohr, B. Penninx, 2021 .

Long-term participant retention and engagement patterns in an app and wearable-based multinational remote digital depression study

M. Hotopf, D. Mohr, B. Penninx, 2023, npj Digital Medicine.

The Feasibility of Implementing Remote Measurement Technologies in Psychological Treatment for Depression: Mixed Methods Study on Engagement

M. Hotopf, F. Matcham, A. Folarin, 2022, JMIR mental health.

Predicting Depressive Symptom Severity Through Individuals’ Nearby Bluetooth Device Count Data Collected by Mobile Phones: Preliminary Longitudinal Study

M. Hotopf, D. Mohr, R. Dobson, 2021, JMIR mHealth and uHealth.

Predicting Depressive Symptom Severity through Individuals’ Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal study (Preprint)

M. Hotopf, D. Mohr, R. Dobson, 2021 .

The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions

M. Hotopf, L. Leocani, R. Bailón, 2021, Comput. Methods Programs Biomed..

Sleep Stage Classification Using Bidirectional LSTM in Wearable Multi-sensor Systems

Xiaoli Liu, Jianli Pan, Zhicheng Yang, 2019, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

The Association Between Home Stay and Symptom Severity in Major Depressive Disorder: Preliminary Findings From a Multicenter Observational Study Using Geolocation Data From Smartphones

M. Hotopf, B. Penninx, V. Narayan, 2022, JMIR mHealth and uHealth.

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

M. Hotopf, Björn Schuller, V. Narayan, 2023, Journal of affective disorders.

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

M. Hotopf, Björn Schuller, B. Penninx, 2023 .

Associations Between Depression Symptom Severity and Daily-Life Gait Characteristics Derived From Long-Term Acceleration Signals in Real-World Settings: Retrospective Analysis

M. Hotopf, D. Mohr, B. Penninx, 2022, JMIR mHealth and uHealth.

Disease Insight through Digital Biomarkers Developed by Remotely Collected Wearables and Smartphone Data

A. Folarin, R. Dobson, Yuezhou Zhang, 2023, ArXiv.

Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis

M. Hotopf, V. Narayan, J. Haro, 2022, Journal of medical Internet research.

Breathing Disorder Detection Using Wearable Electrocardiogram And Oxygen Saturation

Xiaoli Liu, Qian Yuan, Jiewen Zheng, 2018, SenSys.

Automated Sleep Period Estimation in Wearable Multi-sensor Systems

Xiaoli Liu, Jiewen Zheng, Desen Cao, 2018, SenSys.

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

V. Narayan, F. Matcham, S. Simblett, 2024, 2404.11212.