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Longitudinal assessment of falls in patients with Parkinson’s disease using inertial sensors and the Timed Up and Go test
OBJECTIVE: To examine the predictive validity of a TUG test for falls risk, quantified using body-worn sensors (QTUG) in people with Parkinson's Disease (PD). We also sought to examine the inter-session reliability of QTUG sensor measures and their association with the Unified Parkinson’s Disea...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6453040/ https://www.ncbi.nlm.nih.gov/pubmed/31191922 http://dx.doi.org/10.1177/2055668317750811 |
Sumario: | OBJECTIVE: To examine the predictive validity of a TUG test for falls risk, quantified using body-worn sensors (QTUG) in people with Parkinson's Disease (PD). We also sought to examine the inter-session reliability of QTUG sensor measures and their association with the Unified Parkinson’s Disease Rating Scale (UPDRS) motor score. APPROACH: A six-month longitudinal study of 15 patients with Parkinson’s disease. Participants were asked to complete a weekly diary recording any falls activity for six months following baseline assessment. Participants were assessed monthly, using a Timed Up and Go test, quantified using body-worn sensors, placed on each leg below the knee. MAIN RESULTS: The results suggest that the QTUG falls risk estimate recorded at baseline is 73.33% (44.90, 92.21) accurate in predicting falls within 90 days, while the Timed Up and Go time at baseline was 46.67% (21.27, 73.41) accurate. The Timed Up and Go time and QTUG falls risk estimate were strongly correlated with UPDRS motor score. Fifty-two of 59 inertial sensor parameters exhibited excellent inter-session reliability, five exhibited moderate reliability, while two parameters exhibited poor reliability. SIGNIFICANCE: The results suggest that QTUG is a reliable tool for the assessment of gait and mobility in Parkinson’s disease and, furthermore, that it may have utility in predicting falls in patients with Parkinson’s disease. |
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