Quantifying gait patterns in Parkinson's disease

Mónica Romero; Angélica Atehortúa; Eduardo Romero

doi:10.1117/12.2285966

17 November 2017 Quantifying gait patterns in Parkinson's disease

Mónica Romero, Angélica Atehortúa, Eduardo Romero

Proceedings Volume 10572, 13th International Conference on Medical Information Processing and Analysis; 105720A (2017) https://doi.org/10.1117/12.2285966
Event: 13th International Symposium on Medical Information Processing and Analysis, 2017, San Andres Island, Colombia

Abstract

Parkinson’s disease (PD) is constituted by a set of motor symptoms, namely tremor, rigidity, and bradykinesia, which are usually described but not quantified. This work proposes an objective characterization of PD gait patterns by approximating the single stance phase a single grounded pendulum. This model estimates the force generated by the gait during the single support from gait data. This force describes the motion pattern for different stages of the disease. The model was validated using recorded videos of 8 young control subjects, 10 old control subjects and 10 subjects with Parkinson’s disease in different stages. The estimated force showed differences among stages of Parkinson disease, observing a decrease of the estimated force for the advanced stages of this illness.

Citation Download Citation

Mónica Romero, Angélica Atehortúa, and Eduardo Romero "Quantifying gait patterns in Parkinson's disease", Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105720A (17 November 2017); https://doi.org/10.1117/12.2285966

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