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Estimating dyskinesia severity in Parkinson’s disease by using a waist-worn sensor: concurrent validity study

Authors :
Albert Samà
Benedetta Giuliani
Daniel Rodríguez-Martín
Roberta Annicchiarico
Hadas Lewy
Berta Mestre
Gabriel Vainstein
Carlos Pérez-López
Dean Sweeney
Paola Quispe
Àngels Bayés
Gearóid Ó Laighin
Timothy J. Counihan
Leo R. Quinlan
Joan Cabestany
J. Manuel Moreno Arostegui
Alberto Costa
Patrick Browne
Alejandro Rodríguez-Molinero
Sheila Alcaine
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
Universitat Politècnica de Catalunya. ISSET - Integrated Smart Sensors and Health Technologies
Source :
Scientific Reports, Vol 9, Iss 1, Pp 1-7 (2019), Scientific Reports, UPCommons. Portal del coneixement obert de la UPC, Universitat Politècnica de Catalunya (UPC)
Publication Year :
2019
Publisher :
Nature Publishing Group, 2019.

Abstract

Our research team previously developed an accelerometry-based device, which can be worn on the waist during daily life activities and detects the occurrence of dyskinesia in patients with Parkinson’s disease. The goal of this study was to analyze the magnitude of correlation between the numeric output of the device algorithm and the results of the Unified Dyskinesia Rating Scale (UDysRS), administered by a physician. In this study, 13 Parkinson’s patients, who were symptomatic with dyskinesias, were monitored with the device at home, for an average period of 30 minutes, while performing normal daily life activities. Each patient’s activity was simultaneously video-recorded. A physician was in charge of reviewing the recorded videos and determining the severity of dyskinesia through the UDysRS for every patient. The sensor device yielded only one value for dyskinesia severity, which was calculated by averaging the recorded device readings. Correlation between the results of physician’s assessment and the sensor output was analyzed with the Spearman’s correlation coefficient. The correlation coefficient between the sensor output and UDysRS result was 0.70 (CI 95%: 0.33–0.88; p = 0.01). Since the sensor was located on the waist, the correlation between the sensor output and the results of the trunk and legs scale sub-items was calculated: 0.91 (CI 95% 0.76–0.97: p

Details

Language :
English
ISSN :
20452322
Volume :
9
Issue :
1
Database :
OpenAIRE
Journal :
Scientific Reports
Accession number :
edsair.doi.dedup.....ba1160fb70da828ba357cdc30b91cc0a
Full Text :
https://doi.org/10.1038/s41598-019-49798-3