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Medical & Biological Engineering & Computing

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13-09-2018 | Original Article

Computer model for leg agility quantification and assessment for Parkinson’s disease patients

Authors: Christopher Ornelas-Vences, Luis Pastor Sánchez-Fernández, Luis Alejandro Sánchez-Pérez, Juan Manuel Martínez-Hernández

Published in: Medical & Biological Engineering & Computing | Issue 2/2019

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Abstract

Parkinson’s disease (PD) is a progressive disorder that affects motor regulation. The Unified Parkinson’s Disease Rating Scale sponsored by the Movement Disorder Society (MDS-UPDRS) quantifies the illness progression based on clinical observations. The leg agility is an item in this scale, yet only a visual detection of the features is used, leading to subjectivity. Overall, 50 patients (85 measurements) with varying motor impairment severity were asked to perform the leg agility item while wearing inertial sensor units on each ankle. We quantified features based on the MDS-UPDRS and designed a fuzzy inference model to capture clinical knowledge for assessment. The model proposed is capable of capturing all details regardless of the task speed, reducing the inherent uncertainty of the examiner observations obtaining a 92.35% of coincidence with at least one expert. In addition, the continuous scale implemented in this work prevents the inherent “floor/ceil” effect of discrete scales. This model proves the feasibility of quantification and assessment of the leg agility through inertial signals. Moreover, it allows a better follow-up of the PD patient state, due to the repeatability of our computer model and the continuous output, which are not objectively achievable through visual examination.

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Title: Computer model for leg agility quantification and assessment for Parkinson’s disease patients
Authors: Christopher Ornelas-Vences
Luis Pastor Sánchez-Fernández
Luis Alejandro Sánchez-Pérez
Juan Manuel Martínez-Hernández
Publication date: 13-09-2018
Publisher: Springer Berlin Heidelberg
Published in: Medical & Biological Engineering & Computing / Issue 2/2019
Print ISSN: 0140-0118
Electronic ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-018-1894-0

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