Computer model for leg agility quantification and assessment for Parkinson’s disease patients
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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.
KeywordsParkinson’s disease Leg agility Fuzzy logic Assessment
We are grateful to the patients and healthcare professionals that contributed with their participation, ideas, and suggestions to accomplish this work.
Compliance with ethical standards
All procedures performed in this work were in accordance with The Code of Ethics of the World Medical Association and with Data Protection and Privacy Laws. The collected data was under explicit written patients consent.
Conflicts of interest
The authors declare that they have no conflict of interest.
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