Evidence map›Paper›PMID 28582260›Full record

ArticleJMIR rehabilitation and assistive technologies2016

A Personalized Self-Management Rehabilitation System for Stroke Survivors: A Quantitative Gait Analysis Using a Smart Insole.

Richard John Davies, Jack Parker, Paul McCullagh, Huiru Zheng, Chris Nugent, Norman David Black, Susan Mawson

Abstract read
In one paragraph

Article in JMIR rehabilitation and assistive technologies, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Home-Based Gait Interventions for Adults with Stroke: A Scoping Review.Archives of rehabilitation research and clinical translation · 2025
    Review
  4. Article
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Richard John DaviesComputer Science Research Institute, Faculty of Computing and Engineering, Ulster University, Belfast, United Kingdom.ORCID http://orcid.org/0000-0002-2663-3979
Jack ParkerSchool of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.ORCID http://orcid.org/0000-0003-4684-7330
Paul McCullaghComputer Science Research Institute, Faculty of Computing and Engineering, Ulster University, Belfast, United Kingdom.ORCID http://orcid.org/0000-0002-9060-6262
Huiru ZhengComputer Science Research Institute, Faculty of Computing and Engineering, Ulster University, Belfast, United Kingdom.ORCID http://orcid.org/0000-0001-7648-8709
Chris NugentComputer Science Research Institute, Faculty of Computing and Engineering, Ulster University, Belfast, United Kingdom.ORCID http://orcid.org/0000-0003-0882-7902
Norman David BlackComputer Science Research Institute, Faculty of Computing and Engineering, Ulster University, Belfast, United Kingdom.ORCID http://orcid.org/0000-0002-7699-8626
Susan MawsonSchool of Health and Related Research, University of Sheffield, Sheffield, United Kingdom.ORCID http://orcid.org/0000-0003-2795-8983

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the United Kingdom, stroke is the single largest cause of adult disability and results in a cost to the economy of £8.9 billion per annum. Service needs are currently not being met; therefore, initiatives that focus on patient-centered care that promote long-term self-management for chronic conditions should be at the forefront of service redesign. The use of innovative technologies and the ability to apply these effectively to promote behavior change are paramount in meeting the current challenges.

objectiveOur objective was to gain a deeper insight into the impact of innovative technologies in support of home-based, self-managed rehabilitation for stroke survivors. An intervention of daily walks can assist with improving lower limb motor function, and this can be measured by using technology. This paper focuses on assessing the usage of self-management technologies on poststroke survivors while undergoing rehabilitation at home.

methodsA realist evaluation of a personalized self-management rehabilitation system was undertaken in the homes of stroke survivors (N=5) over a period of approximately two months. Context, mechanisms, and outcomes were developed and explored using theories relating to motor recovery. Participants were encouraged to self-manage their daily walking activity; this was achieved through goal setting and motivational feedback. Gait data were collected and analyzed to produce metrics such as speed, heel strikes, and symmetry. This was achieved using a "smart insole" to facilitate measurement of walking activities in a free-living, nonrestrictive environment.

resultsInitial findings indicated that 4 out of 5 participants performed better during the second half of the evaluation. Performance increase was evident through improved heel strikes on participants' affected limb. Additionally, increase in performance in relation to speed was also evident for all 5 participants. A common strategy emerged across all but one participant as symmetry performance was sacrificed in favor of improved heel strikes. This paper evaluates compliance and intensity of use.

conclusionOur findings suggested that 4 out of the 5 participants improved their ability to heel strike on their affected limb. All participants showed improvements in their speed of gait measured in steps per minute with an average increase of 9.8% during the rehabilitation program. Performance in relation to symmetry showed an 8.5% average decline across participants, although 1 participant improved by 4%. Context, mechanism, and outcomes indicated that dual motor learning and compensatory strategies were deployed by the participants.

Indexed as

ambulatory monitoringgaitrehabilitationself-managementsmart insolestroke

Identifiers

PMID28582260
PMCPMC5454559

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.