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Advisor(s)
Abstract(s)
"Background: There is growing interest in having objective assessment of health-related outcomes using
technology-based devices that provide unbiased measurements which can be used in clinical practice and
scientific research. Many studies have investigated the clinical manifestations of Parkinson’s disease using such
devices. However, clinimetric properties and clinical validation vary among the different devices.
Methods: Given such heterogeneity, we sought to perform a systematic review in order to (i) list, (ii) compare
and (iii) classify technological-based devices used to measure motor function in individuals with Parkinson's
disease into three groups, namely wearable, non-wearable and hybrid devices. A systematic literature search of
the PubMed database resulted in the inclusion of 168 studies. These studies were grouped based on the type
of device used. For each device we reviewed availability, use, reliability, validity, and sensitivity to change. The
devices were then classified as (i) ‘recommended’, (ii) ‘suggested’ or (iii) ‘listed’ based on the following criteria:
(1) used in the assessment of Parkinson’s disease (yes/no), (2) used in published studies by people other than
the developers (yes/no), and (3) successful clinimetric testing (yes/no).
Results: Seventy-three devices were identified, 22 were wearable, 38 were non-wearable, and 13 were hybrid
devices. In accordance with our classification method, 9 devices were ‘recommended’, 34 devices were ‘suggested’, and 30 devices were classified as ‘listed’. Within the wearable devices group, the Mobility Lab sensors from Ambulatory Parkinson’s Disease Monitoring (APDM), Physilog®, StepWatch 3, TriTrac RT3 Triaxial accelerometer, McRoberts DynaPort, and Axivity (AX3) were classified as ‘recommended’. Within the non-wearable devices group, the Nintendo Wii Balance Board and GAITRite® gait analysis system were classified as ‘recommended’. Within the hybrid devices group only the Kinesia® system was classified as ‘recommended’."
Description
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Keywords
Outcomes Parkinson’s disease Quantitative assessment Wearable devices Monitoring technologies
Citation
Godinho et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:24 DOI 10.1186/s12984-016-0136-7
Publisher
BioMed Central