Abstract
In this paper, we propose an approach for gait phase detection for flat and inclined surfaces that can be used for an ankle-foot orthosis and the humanoid robot Sweaty. To cover different use cases, we use a rule-based algorithm. This offers the required flexibility and real-time capability. The inputs of the algorithm are inertial measurement unit and ankle joint angle signals. We show that the gait phases with the orthosis worn by a human participant and with Sweaty are reliably recognized by the algorithm under the condition of adapted transition conditions. E.g., the specificity for human gait on flat surfaces is 92 %. For the robot Sweaty, 95 % results in fully recognized gait cycles. Furthermore, the algorithm also allows the determination of the inclination angle of the ramp. The sensors of the orthosis provide 6.9\(^\circ \) and that of the robot Sweaty 7.7\(^\circ \) when walking onto the reference ramp with slope angle 7.9\(^\circ \).
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Acknowledgment
Special thanks to Seifert Technical Orthopaedics for their support in the field of orthosis and for the possibility to do the trials with the participants. The research work on the orthosis was financed by the Federal Ministry of Economic Affairs and Climate Action of Germany.
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Gießler, M., Breig, M., Wolf, V., Schnekenburger, F., Hochberg, U., Willwacher, S. (2023). Gait Phase Detection on Level and Inclined Surfaces for Human Beings with an Orthosis and Humanoid Robots. In: Eguchi, A., Lau, N., Paetzel-Prüsmann, M., Wanichanon, T. (eds) RoboCup 2022: Robot World Cup XXV. RoboCup 2022. Lecture Notes in Computer Science(), vol 13561. Springer, Cham. https://doi.org/10.1007/978-3-031-28469-4_4
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