Abstract
EvolvRehab-Body is a non-immersive virtual rehabilitation system that could provide high-dose, exercise-based upper limb therapy after stroke. This consideration-of-concept study investigated: adherence rate to prescribed repetitions; viability of repeated measures in preparation for a dose-articulation study; and preliminary signal of potential benefit.
Methods
Pre-post and repeated measures with people at least six months after stroke. Twelve-week intervention: exercise-based therapy via EvolvRehab-Body. Pre-post-intervention measures: Wolf Motor Function Test (WMFT); hand grip force. Repeated-during-intervention measures: Motricity Index (MI) and Action Research Arm Test (ARAT). Analysis: adherence rate (%) to set repetitions; percentage of total possible measures collected; pre-to-post-intervention change estimated in relation to published minimally detectable changes of WMFT and hand grip force; and slope of plotted data for MI and ARAT (linear regression).
Results
Eight of twelve participants completed the 12-week intervention phase. Adherence: 88% (1710–9377 repetitions performed). Viability repeated measures: 88 of 96 (92%) ARAT and MI scores collected. Preliminary signal of potential benefit was observed in five participants but not always for the same measures. Three participants improved WMFT-time (−7.9 to −27.2 s/item), four improved WMFT-function (0.2–1.1 points/item), and nobody changed grip force. Slope of plotted data over the 12-week intervention ranged from: − 1.42 (p = 0.26) to 1.36 (p = 0.24) points-per-week for MI and − 0.30 (p = 0.40) to 1.71 (p < 0.001) points-per-week for ARAT.
Conclusion
Findings of good adherence rate in home settings and preliminary signal of benefit for some participants gives support to proceed to a dose-articulation study. These findings cannot inform clinical practice.
| Original language | English |
|---|---|
| Pages (from-to) | 97-107 |
| Number of pages | 11 |
| Journal | Physiotherapy |
| Volume | 116 |
| Early online date | 8 Apr 2022 |
| DOIs | |
| Publication status | Published (in print/issue) - 1 Sept 2022 |
Bibliographical note
Funding Information:We are grateful to Evolv Rehabilitation Technologies for providing part of the funding of the University of East Anglia PhD studentship held by Fiona Ellis, first author of this scientific report. We are also grateful for the support for the last author’s research provided by the National Institute for Health Research (NIHR) Brain Injury MedTech Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.
Funding Information:
Fiona Ellis was funded by a University of East Anglia (UEA) PhD Fellowship. Funding for the PhD Fellowship was provided by the UEA and Evolv Rehabilitation Technologies.
Publisher Copyright:
© 2022 Chartered Society of Physiotherapy
Funding
Funding Information: We are grateful to Evolv Rehabilitation Technologies for providing part of the funding of the University of East Anglia PhD studentship held by Fiona Ellis, first author of this scientific report. We are also grateful for the support for the last author’s research provided by the National Institute for Health Research (NIHR) Brain Injury MedTech Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Funding Information: Fiona Ellis was funded by a University of East Anglia (UEA) PhD Fellowship. Funding for the PhD Fellowship was provided by the UEA and Evolv Rehabilitation Technologies. Publisher Copyright: © 2022 Chartered Society of Physiotherapy
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Virtual Rehabilitation
- Virtual Reality
- User-led design
- Stroke
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