IEEE Trans Neural Syst Rehabil Eng
May 2024
To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this study, resulting in enhanced classification accuracy. The structure of the ELM algorithm is enhanced using the logistic regression (LR) algorithm, significantly reducing the number of hidden layer nodes. Hence, this algorithm can be adopted for real-time human locomotion intent recognition on portable devices with only 234 parameters to store.
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February 2023
In this article, a new hydraulic semi-active knee (HSAK) prosthesis is proposed. Compared with knee prostheses driven by hydraulic-mechanical coupling or electromechanical systems, we novelly combine independent active and passive hydraulic subsystems to solve the incompatibility between low passive friction and high transmission ratio of current semi-active knees. The HSAK not only has the low friction to follow the intentions of users, but also performs adequate torque output.
View Article and Find Full Text PDFMicromachines (Basel)
December 2021
Conventional motors with complicated electromagnetic structures are difficult to miniaturise for millimetre- and centimetre-sized robots. Instead, small-scale robots are actuated using a variety of functional materials. We proposed a novel robot propelled by a piezoelectric ceramic in this work.
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April 2021
This paper aims to further our previous study to investigate the effect of speed on the human metatarsophalangeal (MP) joint kinematics during running on level ground. The 3D motion of the foot segments was captured by a twelve-camera motion analysis system, and the ground reaction forces and moments were recorded by using a six-force plate array. The relative movement between the tarsometatarsi (hindfoot) and phalanges (forefoot) segments were recorded to obtain the 3D orientation and position of the functional axis (FA) of the MP joint.
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