This paper is in the following e-collection/theme issue:

Methods and New Tools in Mental Health Research (396) Mobile Health (mhealth) (2359) JMIR Theme Issue: COVID-19 Special Issue (2276) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (359) Outbreak and Pandemic Preparedness and Management (1556) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1403) Digital Biomarkers and Digital Phenotyping (155) Machine Learning (1189) Fitness Trackers and Smart Pedometers/Accelerometers (513) Wearable Devices and Sensors (733) mHealth for Wellness, Behavior Change and Prevention (2523) Neurology and Neurosciences (127)

Published on in Vol 9, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38495, first published .
Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping

Authors of this article:

Prerna Chikersal 1 Author Orcid Image ;   Shruthi Venkatesh 2 Author Orcid Image ;   Karman Masown 2 Author Orcid Image ;   Elizabeth Walker 2 Author Orcid Image ;   Danyal Quraishi 2 Author Orcid Image ;   Anind Dey 3 Author Orcid Image ;   Mayank Goel 1 Author Orcid Image ;   Zongqi Xia 2 Author Orcid Image
Article Authors Cited by (5) Tweetations (5) Metrics

Journals

  1. Moura I, Teles A, Viana D, Marques J, Coutinho L, Silva F. Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review. Journal of Biomedical Informatics 2023;138:104278 View
  2. Triantafyllidis A, Segkouli S, Zygouris S, Michailidou C, Avgerinakis K, Fappa E, Vassiliades S, Bougea A, Papagiannakis N, Katakis I, Mathioudis E, Sorici A, Bajenaru L, Tageo V, Camonita F, Magga-Nteve C, Vrochidis S, Pedullà L, Brichetto G, Tsakanikas P, Votis K, Tzovaras D. Mobile App Interventions for Parkinson’s Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review. Sensors 2023;23(7):3396 View
  3. Voigt I, Inojosa H, Wenk J, Akgün K, Ziemssen T. Building a monitoring matrix for the management of multiple sclerosis. Autoimmunity Reviews 2023;22(8):103358 View
  4. Woelfle T, Bourguignon L, Lorscheider J, Kappos L, Naegelin Y, Jutzeler C. Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective. Journal of Medical Internet Research 2023;25:e44428 View
  5. Pinarello C, Elmers J, Inojosa H, Beste C, Ziemssen T. Management of multiple sclerosis fatigue in the digital age: from assessment to treatment. Frontiers in Neuroscience 2023;17 View