TY - JOUR
T1 - Computer model for leg agility quantification and assessment for Parkinson’s disease patients
AU - Ornelas-Vences, Christopher
AU - Sánchez-Fernández, Luis Pastor
AU - Sánchez-Pérez, Luis Alejandro
AU - Martínez-Hernández, Juan Manuel
N1 - Publisher Copyright:
© 2018, International Federation for Medical and Biological Engineering.
PY - 2019/2/13
Y1 - 2019/2/13
N2 - 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. [Figure not available: see fulltext.]
AB - 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. [Figure not available: see fulltext.]
KW - Assessment
KW - Fuzzy logic
KW - Leg agility
KW - Parkinson’s disease
UR - http://www.scopus.com/inward/record.url?scp=85053504441&partnerID=8YFLogxK
U2 - 10.1007/s11517-018-1894-0
DO - 10.1007/s11517-018-1894-0
M3 - Artículo
C2 - 30215213
AN - SCOPUS:85053504441
SN - 0140-0118
VL - 57
SP - 463
EP - 476
JO - Medical and Biological Engineering and Computing
JF - Medical and Biological Engineering and Computing
IS - 2
ER -