Normal human gait patterns in Peruvian individuals: an exploratory assessment using VICON motion capture system

R. Dongo; M. Moscoso; R. Callupe; J. Pajaya; D. Elías

doi:10.1117/12.2285978

17 November 2017 Normal human gait patterns in Peruvian individuals: an exploratory assessment using VICON motion capture system

R. Dongo, M. Moscoso, R. Callupe, J. Pajaya, D. Elías

Author Affiliations +

Proceedings Volume 10572, 13th International Conference on Medical Information Processing and Analysis; 1057209 (2017) https://doi.org/10.1117/12.2285978
Event: 13th International Symposium on Medical Information Processing and Analysis, 2017, San Andres Island, Colombia

Abstract

Gait analysis is of clinical relevance for clinicians. However, normal gait patterns used in foreign literature could be different from local individuals. The aim of this study was to determine the normal gait patterns and parameters of Peruvian individuals in order to have a local referent for clinical assessments and making diagnosis and treatment Peruvian people with lower motor neuron injuries. A descriptive study with 34 subjects was conducted to assess their gait cycle. VICON® cameras were used to capture body movements. For the analyses, we calculated spatiotemporal gait parameters and average angles of displacement of the hip, knee, and ankle joints with their respective 95% confidence intervals. The results showed gait speed was 0.58m/s, cadence was 102.1steps/min, and the angular displacement of the hip, knee and ankle joints were all lower than those described in the literature. In the graphs, gait cycles were close to those reported in previous studies, but the parameters of speed, cadence and angles of displacements are lower than the ones shown in the literature. These results could be used as a better reference pattern in the clinical setting.

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R. Dongo, M. Moscoso, R. Callupe, J. Pajaya, and D. Elías "Normal human gait patterns in Peruvian individuals: an exploratory assessment using VICON motion capture system", Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 1057209 (17 November 2017); https://doi.org/10.1117/12.2285978

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