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Data · dataset · 2015

Reducing Compensatory Motions in Motion-Based Video Games for Stroke Rehabilitation

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Stroke survivors’ unsupervised therapeutic exercise motions are often accompanied by harmful compensatory motions that prevent proper motor recovery and introduce additional health issues.

Description

These compensatory motions are often performed unconsciously and are difficult to prevent. Motion-based games show promise for motivating patients to perform stroke rehabilitation exercises at home by themselves.

Currently, exercises with these games are likely to contain undesired compensatory motions. In this article, we provide the design and empirical evaluation of a motion-based game system that addresses the issue of compensation in therapeutic games. We introduce a technique to identify and measure compensation, develop a game that meaningfully uses exercise and compensation as inputs, and use incentives and disincentives to reduce compensation.

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We show that this technique outperforms existing approaches by significantly reducing compensatory motions during therapeutic exercise. This has important implications for therapeutic games, which can use our findings to improve the quality of motions to be closer to therapist-supervised motions. Our techniques can increase the effectiveness of therapeutic games and reduce the possibility that they may cause harm in long-term use.

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Stated by source
Biological sciences · Sociology
Inferred from text
Video 75%
Provenance · 1 source records, 15 field assertions
SourceKeyLast seenRaw
DataCite10.6084/m9.figshare.125776512 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[disease].local:disease:cancermapping · DataCitevocabulary-mapper@1.0.0keywords['Cancer']
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concepts[field].fos:sociologysource · DataCiteconnector:datacite@1.0.0
concepts[field].local:field:life-sciencesmapping · DataCitevocabulary-mapper@1.0.0keywords['Biological Sciences']
concepts[field].local:field:medicine-healthmapping · DataCitevocabulary-mapper@1.0.0keywords['Medicine']
concepts[field].local:field:social-sciencemapping · DataCitevocabulary-mapper@1.0.0keywords['Sociology']
concepts[modality].local:modality:videoenrichment · DataCitekeyword-concept-rules@1.0.0title+description (75%)
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