Alexander, S;
Peryer, G;
Gray, E;
Barkhof, F;
Chataway, J;
(2020)
Wearable technologies to measure clinical outcomes in multiple sclerosis: A scoping review.
Multiple Sclerosis Journal
10.1177/1352458520946005.
(In press).
Preview |
Text
Wearable technologies to measure clinical outcomes in multiple sclerosis -A scoping review.pdf - Published Version Download (485kB) | Preview |
Abstract
Wearable technology refers to any sensor worn on the person, making continuous and remote monitoring available to many people with chronic disease, including multiple sclerosis (MS). Daily monitoring seems an ideal solution either as an outcome measure or as an adjunct to support rater-based monitoring in both clinical and research settings. There has been an increase in solutions that are available, yet there is little consensus on the most appropriate solution to use in either MS research or clinical practice. We completed a scoping review (using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines) to summarise the wearable solutions available in MS, to identify those approaches that could potentially be utilised in clinical trials, by evaluating the following: scalability, cost, patient adaptability and accuracy. We identified 35 unique products that measure gait, cognition, upper limb function, activity, mood and fatigue, with most of these solutions being phone applications.
Type: | Article |
---|---|
Title: | Wearable technologies to measure clinical outcomes in multiple sclerosis: A scoping review |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1177/1352458520946005 |
Publisher version: | https://doi.org/10.1177/1352458520946005 |
Language: | English |
Additional information: | This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | Multiple sclerosis, biosensors, mHealth, mobile applications, remote sensing technology, wearable technology |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Brain Repair and Rehabilitation |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10107071 |
Archive Staff Only
View Item |