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Sensors 2016, 16(6), 930; doi:10.3390/s16060930

Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson’s Disease

1
Institute of Medical Engineering and Mechatronics, Ulm University of Applied Sciences, Albert-Einstein-Allee 55, Ulm D-89081, Germany
2
Faculty of Physics, Ludwig-Maximilians-Universität München, Geschwister-Scholl-Platz 1, Munich D-80539, Germany
3
Department of Neurology, University of Ulm, Oberer Eselsberg 45, Ulm D-89081, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Panicos Kyriacou
Received: 30 March 2016 / Revised: 4 June 2016 / Accepted: 16 June 2016 / Published: 21 June 2016
(This article belongs to the Collection Sensors for Globalized Healthy Living and Wellbeing)
View Full-Text   |   Download PDF [3346 KB, uploaded 21 June 2016]   |  

Abstract

Remote monitoring of Parkinson’s Disease (PD) patients with inertia sensors is a relevant method for a better assessment of symptoms. We present a new approach for symptom quantification based on motion data: the automatic Unified Parkinson Disease Rating Scale (UPDRS) classification in combination with an animated 3D avatar giving the neurologist the impression of having the patient live in front of him. In this study we compared the UPDRS ratings of the pronation-supination task derived from: (a) an examination based on video recordings as a clinical reference; (b) an automatically classified UPDRS; and (c) a UPDRS rating from the assessment of the animated 3D avatar. Data were recorded using Magnetic, Angular Rate, Gravity (MARG) sensors with 15 subjects performing a pronation-supination movement of the hand. After preprocessing, the data were classified with a J48 classifier and animated as a 3D avatar. Video recording of the movements, as well as the 3D avatar, were examined by movement disorder specialists and rated by UPDRS. The mean agreement between the ratings based on video and (b) the automatically classified UPDRS is 0.48 and with (c) the 3D avatar it is 0.47. The 3D avatar is similarly suitable for assessing the UPDRS as video recordings for the examined task and will be further developed by the research team. View Full-Text
Keywords: MARG sensors; inertia sensors; IMU; motion data; Parkinson’s Disease; UPDRS; symptom quantification; animated 3D avatar; telemonitoring; remote monitoring; pronation-supination; diadochokinesis MARG sensors; inertia sensors; IMU; motion data; Parkinson’s Disease; UPDRS; symptom quantification; animated 3D avatar; telemonitoring; remote monitoring; pronation-supination; diadochokinesis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

  • Externally hosted supplementary file 1
    Doi: 10.5281/zenodo.48539
    Link: https://zenodo.org/record/48539
    Description: In this ZIP-file you find supplementary data to the manuscript "Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson's Disease". 26 subjects (13 PD patients and 13 controls) performed Item 3.6 "Pronation-Supination Movements of Hands" of the MDS-UPDRS [1]. The ZIP-file contains anonymized subject data, 51 data features for each record, results of the different UPDRS ratings from all neurologists and the MARG sensor raw data of the pronation-supination phase in single data files (csv).

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MDPI and ACS Style

Piro, N.E.; Piro, L.K.; Kassubek, J.; Blechschmidt-Trapp, R.A. Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson’s Disease. Sensors 2016, 16, 930.

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