Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/20.500.12421/4536
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dc.contributor.authorSaavedra Lozano, Diego Fernando-
dc.contributor.authorCastillo García, Javier Ferney-
dc.date.accessioned2020-10-23T22:57:57Z-
dc.date.available2020-10-23T22:57:57Z-
dc.date.issued2020-08-11-
dc.identifier.isbn978-303053020-4-
dc.identifier.issn18761100-
dc.identifier.urihttp://repository.usc.edu.co/handle/20.500.12421/4536-
dc.description.abstractGait laboratories using image processing are the standardized method to analyze human gait, but these are expensive, require restrictive workspaces, and post-processing times. On the other hand, inertial sensors are cheaper and reach high performance with lower computational cost in its implementation. In this work, a wireless system was implemented for the analysis of human gait using inertial sensors. The inertial sensor was chosen according to its specifications, cost, and pursuant to the characteristics of the human gait. In total, seven inertial sensors were used, arranged on the pelvis, thighs, legs and feet. A calibration algorithm was implemented to adjust the sensor angles with those of their respective body segment based on a known posture. The data capture system was verified comparing the angle of flexion-extension of the knee with the angle obtained by the artificial vision system from the sagittal plane and comparing it with bands of normality. As a result, it was possible to implement a low-cost inertial motion capture system for the analysis of human gait, with its respective graphical interface to visualize the orientation, flexion-extension angles for each segment and joint of the lower limbs. It is concluded that is possible to develop a complete tool for the kinematic analysis of human gait with the information of the artificial vision system or an anthropometric model.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectCapture systemen_US
dc.subjectHuman gaiten_US
dc.subjectInertial sensorsen_US
dc.titleSystem for analysis of human gait using inertial sensorsen_US
dc.typeArticleen_US
Appears in Collections:Artículos Científicos

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