2015

IET International Conference on Technologies for Active and Assisted Living

Gait Analysis on the move: The Infinite Gait Walkway

Stefan Wakolbinger, Josef Alois Birchbauer, Severin Küberl

Siemens AG Österreich, Corporate Technology, Video Analytics Austria

Keywords

gait analysis, smart walker, assistive robotics

Abstract

In order to analyze human gait patterns, highly accurate data must be collected at high frame rates. The state of the art is to deploy a carpet-like structure instrumented with pressure sensors, which allows for measuring position, orientation and pressure of each foot at each step. Since such gait “walkway carpets” are highly expensive1 and also limited in length, we propose an alternative in the form of a wheeled walker equipped with a consumer depth camera. We have designed and implemented algorithms that derive the same set of parameters from the depth data as in a gait walkway system, however without the need for the physical presence of a walkway carpet. Moreover, we are able to provide additional information, due to continuous observation of the gait cycle, i.e. not only when the user steps on the ground. In order to retrieve actual foot pressure information, we use a shoe insole sensor. Our experiments show that the system is able to collect gait relevant data with sufficient accuracy and frame rates. While the feet's position accuracy depends primarily on the noise of the depth sensor and is typically at a precision of less than 3 mm, the orientation accuracy is around 1-2 degrees for typical foot orientations.

Moticon's Summary

The paper explores advancements in gait analysis, essential for diagnosing and managing neurological, systemic, and age-related diseases. Traditional subjective gait assessments are enhanced with new technologies for objective, continuous monitoring. The study introduces a four-wheeled walker equipped with depth sensors and odometers, capturing detailed biomechanical gait data without requiring a physical gait walkway. Additionally, Moticon sensor insoles are used to obtain plantar pressure information. Algorithms process depth data to estimate foot positions, orientations, and pressures, achieving real-time analysis at 15-30 fps. Results showed accurate tracking of foot movements, comparable to state-of-the-art systems, with minor errors in position and orientation. The system's continuous monitoring capability offers significant improvements in clinical gait analysis. Future work will enhance outdoor compatibility and integrate additional sensors for comprehensive gait assessment, potentially aiding fall prevention and treatment optimization.

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