22 December 2015 Quantifying Parkinson's disease progression by simulating gait patterns
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Proceedings Volume 9681, 11th International Symposium on Medical Information Processing and Analysis; 96810J (2015) https://doi.org/10.1117/12.2211250
Event: 11th International Symposium on Medical Information Processing and Analysis (SIPAIM 2015), 2015, Cuenca, Ecuador
Modern rehabilitation protocols of most neurodegenerative diseases, in particular the Parkinson Disease, rely on a clinical analysis of gait patterns. Currently, such analysis is highly dependent on both the examiner expertise and the type of evaluation. Development of evaluation methods with objective measures is then crucial. Physical models arise as a powerful alternative to quantify movement patterns and to emulate the progression and performance of specific treatments. This work introduces a novel quantification of the Parkinson disease progression using a physical model that accurately represents the main gait biomarker, the body Center of Gravity (CoG). The model tracks the whole gait cycle by a coupled double inverted pendulum that emulates the leg swinging for the single support phase and by a damper-spring System (SDP) that recreates both legs in contact with the ground for the double phase. The patterns generated by the proposed model are compared with actual ones learned from 24 subjects in stages 2,3, and 4. The evaluation performed demonstrates a better performance of the proposed model when compared with a baseline model(SP) composed of a coupled double pendulum and a mass-spring system. The Frechet distance measured differences between model estimations and real trajectories, showing for stages 2, 3 and 4 distances of 0.137, 0.155, 0.38 for the baseline and 0.07, 0.09, 0.29 for the proposed method.
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Luisa Cárdenas, Luisa Cárdenas, Fabio Martínez, Fabio Martínez, Angélica Atehortúa, Angélica Atehortúa, Eduardo Romero, Eduardo Romero, } "Quantifying Parkinson's disease progression by simulating gait patterns", Proc. SPIE 9681, 11th International Symposium on Medical Information Processing and Analysis, 96810J (22 December 2015); doi: 10.1117/12.2211250; https://doi.org/10.1117/12.2211250

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