Journal
2019 FIRST INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION, CONTROL, ARTIFICIAL INTELLIGENCE, AND ROBOTICS (ICA-SYMP 2019)
Volume -, Issue -, Pages 69-72Publisher
IEEE
DOI: 10.1109/ica-symp.2019.8646253
Keywords
Lower Limp Exoskeleton; Gait phase recognition; C4.5; MLP; NARX
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Feedhak control of exoskeleton suit requires recognition of gait phases occurred in one gait cycle. This paper presents C4.5 decision tree algorithm compared with multilayer perceptron (MLP) and nonlinear autoregressive with exogenous variable (NARX) recognizing three different gait phases of a passive lower limp exoskeleton: Stance, Swing, and Push. Two IMU sensors on hip and knee joint and two FSR sensors in a self-made shoe provide four inputs for the algorithms. Test data at different walking speeds are collected. The experimental results show classification success rate of each algorithm when algorithm trained with different size of pattern. The result of implementation on Arduino is verified.
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