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Arm impairment and walking speed explain real-life activity of the affected Arm and leg after stroke
The Department of Clinical Neuroscience, Rehabilitation Medicine, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; The Department of Occupational Therapy and Physiotherapy, Sahlgrenska University Hospital, Gothenburg, Sweden.
The Department of Clinical Neuroscience, Rehabilitation Medicine, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; The Department of Health and Rehabilitation, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. The RISE, Unit Sensor System, Gothenburg, Sweden.ORCID iD: 0000-0002-3165-6999
The RISE, Unit Sensor System, Gothenburg, Sweden.
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2021 (English)In: Journal of Rehabilitation Medicine, ISSN 1650-1977, E-ISSN 1651-2081, Vol. 53, no 6, article id jrm00210Article in journal (Refereed) Published
Abstract [en]

Objective: To determine to what extent accelerometer-based arm, leg and trunk activity is associated with sensorimotor impairments, walking capacity and other factors in subacute stroke.

Design: Cross-sectional study.

Patients: Twenty-six individuals with stroke (mean age 55.4 years, severe to mild motor impairment).

Methods: Data on daytime activity were collected over a period of 4 days from accelerometers placed on the wrists, ankles and trunk. A forward stepwise linear regression was used to determine associations between free-living activity, clinical and demographic variables.

Results: Arm motor impairment (Fugl-Meyer Assessment) and walking speed explained more than 60% of the variance in daytime activity of the more-affected arm, while walking speed alone explained 60% of the more-affected leg activity. Activity of the less-affected arm and leg was associated with arm motor impairment (R2=0.40) and independence in walking (R2=0.59). Arm activity ratio was associated with arm impairment (R2=0.63) and leg activity ratio with leg impairment (R2=0.38) and walking speed (R2=0.27). Walking-related variables explained approximately 30% of the variance in trunk activity.

Conclusion: Accelerometer-based free-living activity is dependent on motor impairment and walking capacity. The most relevant activity data were obtained from more-affected limbs. Motor impairment and walking speed can provide some information about real-life daytime activity levels.

Place, publisher, year, edition, pages
Foundation for Rehabilitation Information , 2021. Vol. 53, no 6, article id jrm00210
Keywords [en]
Accelerometry, Ambulatory monitoring, Clinical research, Outcome assessment (healthcare), Outcome measures, Rehabilitation, Stroke, Wearable technology
National Category
Physiotherapy
Identifiers
URN: urn:nbn:se:umu:diva-186553DOI: 10.2340/16501977-2838ISI: 000677561500004Scopus ID: 2-s2.0-85111768366OAI: oai:DiVA.org:umu-186553DiVA, id: diva2:1584450
Available from: 2021-08-12 Created: 2021-08-12 Last updated: 2025-02-11Bibliographically approved

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Ohlsson, Fredrik

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