Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.
Parkinsonism Relat Disord
; 64: 112-117, 2019 07.
Article
em En
| MEDLINE
| ID: mdl-30935826
INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkinson's disease (PD) and its usefulness for constructing individual dose-response models. METHODS: Twenty-five patients with PD performed a series of tasks throughout a levodopa challenge while wearing sensors. TRIS was used to determine motor changes in pronation-supination tests following a single levodopa dose, and was compared to clinical ratings including the Treatment Response Scale (TRS) and six sub-items of the UPDRS part III. RESULTS: As expected, correlations between TRIS and clinical ratings were lower in the new population than in the initial study. TRIS was still significantly correlated to TRS (rsâ¯=â¯0.23, Pâ¯<â¯0.001) with a root mean square error (RMSE) of 1.33. For the patients (nâ¯=â¯17) with a good levodopa response and clear motor fluctuations, a stronger correlation was found (rsâ¯=â¯0.38, RMSEâ¯=â¯1.29, Pâ¯<â¯0.001). The mean TRIS increased significantly when patients went from the practically defined off to their best on state (Pâ¯=â¯0.024). Individual dose-response models could be fitted for more participants when TRIS was used for modelling than when TRS ratings were used. CONCLUSION: The objective sensor index shows promise for constructing individual dose-response models, but further evaluations and retraining of the TRIS algorithm are desirable to improve its performance and to ensure its clinical effectiveness.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Doença de Parkinson
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Levodopa
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Máquina de Vetores de Suporte
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Dispositivos Eletrônicos Vestíveis
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Atividade Motora
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Antiparkinsonianos
Tipo de estudo:
Prognostic_studies
Limite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article