Abstract
Gait phase is widely used for gait trajectory generation, gait control and gait evaluation on lower-limb exoskeletons. So far, a variety of methods have been developed to identify the gait phase for lower-limb exoskeletons. Angular sensors on lower-limb exoskeletons are essential for joint closed-loop controlling; however, other types of sensors, such as plantar pressure, attitude or inertial measurement unit, are not indispensable.Therefore, to make full use of existing sensors, we propose a novel gait phase recognition method for lower-limb exoskeletons using only joint angular sensors. The method consists of two procedures. Firstly, the gait deviation distances during walking are calculated and classified by Fisher’s linear discriminant method, and one gait cycle is divided into eight gait phases. The validity of the classification results is also verified based on large gait samples. Secondly, we build a gait phase recognition model based on multilayer perceptron and train it with the phase-labeled gait data. The experimental result of cross-validation shows that the model has a 94.45% average correct rate of set (CRS) and an 87.22% average correct rate of phase (CRP) on the testing set, and it can predict the gait phase accurately. The novel method avoids installing additional sensors on the exoskeleton or human body and simplifies the sensory system of the lower-limb exoskeleton.
Highlights
The lower-limb exoskeleton, as a mechanical device that is designed around the shape and the function of the human body and can be worn by the operator [1,2], is widely used for the disabled and elderly people for power-assisted walking or for normal people for load-carrying [3,4]
Accurate gait phase recognition is critical to the lower-limb exoskeleton
We propose a novel gait phase recognition method using only joint angular sensors of the lower-limb exoskeleton
Summary
The lower-limb exoskeleton, as a mechanical device that is designed around the shape and the function of the human body and can be worn by the operator [1,2], is widely used for the disabled and elderly people for power-assisted walking or for normal people for load-carrying [3,4]. The lower-limb joints have similar motion in the same gait phase [6,7]. The walking performance of the exoskeleton is mainly determined by the following three aspects: gait trajectory generation, gait execution and gait assessment [3,8,9], which are all related to gait phases. (1) especially in rehabilitation, the exoskeleton walking gait trajectory is usually generated by a motion model or algorithm based on gait phases [10,11]. (2) Due to the similarity of the motion parameters in the same gait phase, many control strategies of the exoskeleton are developed based on gait phases [12,13]. Accurate gait phase recognition is critical to the lower-limb exoskeleton
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