C. Stewart

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.

Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study

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

Presentation of long COVID and associated risk factors in a mobile health study

A. Folarin, Y. Ranjan, Z. Rashid, 2022, medRxiv.

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

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

Fitbeat: COVID-19 estimation based on wristband heart rate using a contrastive convolutional auto-encoder

Florian B. Pokorny, M. Hotopf, R. Dobson, 2021, Pattern Recognition.

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.

RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices

Richard Dobson, Mark Begale, Amos Folarin, 2019, JMIR mHealth and uHealth.

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.

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..

Personalized acute stress classification from physiological signals with neural processes

Richard Dobson, Callum L. Stewart, Amos Folarin, 2020, 2002.04176.

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

Amos Folarin, Richard Dobson, Callum Stewart, 2021, JMIR research protocols.

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

Marwa Al Arab, K. Bhaskaran, L. Smeeth, 2023, EClinicalMedicine.

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 .