Literature DB >> 24080348

Network of movement and proximity sensors for monitoring upper-extremity motor activity after stroke: proof of principle.

Brad Sokal1, Gitendra Uswatte2, Joydip Barman1, Michael Brewer1, Ezekiel Byrom1, Jessica Latten1, Jeethu Joseph1, Camila Serafim1, Touraj Ghaffari3, Nilanjan Sarkar4.   

Abstract

OBJECTIVE: To test the convergent validity of an objective method, Sensor-Enabled Radio-frequency Identification System for Monitoring Arm Activity (SERSMAA), that distinguishes between functional and nonfunctional activity.
DESIGN: Cross-sectional study.
SETTING: Laboratory. PARTICIPANTS: Participants (N=25) were ≥0.2 years poststroke (median, 9) with a wide range of severity of upper-extremity hemiparesis.
INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: After stroke, laboratory tests of the motor capacity of the more-affected arm poorly predict spontaneous use of that arm in daily life. However, available subjective methods for measuring everyday arm use are vulnerable to self-report biases, whereas available objective methods only provide information on the amount of activity without regard to its relation with function. The SERSMAA consists of a proximity-sensor receiver on the more-affected arm and multiple units placed on objects. Functional activity is signaled when the more-affected arm is close to an object that is moved. Participants were videotaped during a laboratory simulation of an everyday activity, that is, setting a table with cups, bowls, and plates instrumented with transmitters. Observers independently coded the videos in 2-second blocks with a validated system for classifying more-affected arm activity.
RESULTS: There was a strong correlation (r=.87, P<.001) between time that the more-affected arm was used for handling objects according to the SERSMAA and functional activity according to the observers.
CONCLUSIONS: The convergent validity of SERSMAA for measuring more-affected arm functional activity after stroke was supported in a simulation of everyday activity.
Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Arm; Outcome and process assessment (health care); Paresis; Rehabilitation; Stroke

Mesh:

Year:  2013        PMID: 24080348     DOI: 10.1016/j.apmr.2013.09.013

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  2 in total

Review 1.  An overview of systematic reviews on upper extremity outcome measures after stroke.

Authors:  Margit Alt Murphy; Carol Resteghini; Peter Feys; Ilse Lamers
Journal:  BMC Neurol       Date:  2015-03-11       Impact factor: 2.474

2.  Recognizing complex upper extremity activities using body worn sensors.

Authors:  Ryanne J M Lemmens; Yvonne J M Janssen-Potten; Annick A A Timmermans; Rob J E M Smeets; Henk A M Seelen
Journal:  PLoS One       Date:  2015-03-03       Impact factor: 3.240

  2 in total

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