Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning...
Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study
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Switzerland: MDPI AG
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English
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Switzerland: MDPI AG
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Background: Three-dimensional gait analysis, supported by advanced sensor systems, is a crucial component in the rehabilitation assessment of post-stroke hemiplegic patients. However, the sensor data generated from such analyses are often complex and challenging to interpret in clinical practice, requiring significant time and complicated procedure...
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Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study
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TN_cdi_doaj_primary_oai_doaj_org_article_3ee79f1ef8b14e56a0949c5cbba0c61e
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_3ee79f1ef8b14e56a0949c5cbba0c61e
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s24227258
