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Knee Joint

Knee Joint

The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...

Ankle Joint

Ankle Joint

The ankle is formed by the talocrural joint (crural = leg). It consists of the articulations between the talus bone of the foot and the distal ends of the tibia and fibula of the leg. The superior aspect of the talus bone is square-shaped and has three areas of articulation. The top of the talus articulates with the inferior tibia. This is the portion of the ankle joint that carries the body weight between the leg and foot. The sides of the talus are firmly held in position by the articulations...

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Related Experiment Video

Updated: Jul 29, 2025

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Published on: July 22, 2014

An advanced bionic knee joint mechanism with neural network controller.

Changxian Xu¹, Zhongbo Sun¹, Chen Wang¹

¹Department of Control Engineering, Changchun University of Technology, Changchun, China.

Frontiers in Neurorobotics

|May 22, 2023

Summary

This summary is machine-generated.

This study introduces a novel tensegrity knee mechanism for efficient rehabilitation exoskeletons. A unique noise-tolerant controller enhances performance and precision in bionic knee joint applications.

Keywords:

bionic knee joint dynamics kinematics noise-tolerant zeroing neural network model tensegrity

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Area of Science:

Biomedical Engineering
Robotics
Rehabilitation Technology

Background:

Developing efficient knee exoskeletons is crucial for rehabilitation.
Existing bionic knee mechanisms face challenges with noise and disturbances.
Tensegrity structures offer unique mechanical properties for biomechanical applications.

Purpose of the Study:

To develop a high-efficiency rehabilitation knee exoskeleton using a tensegrity-based mechanism.
To improve controller design through kinematic and dynamic modeling.
To enhance the bionic properties of the knee joint by developing limit position functionality.

Main Methods:

Exploration of kinematics and dynamics models for the tensegrity knee mechanism.
Development of limit position functionality based on knee patella limit function.
Implementation of a noise-tolerant zeroing neural network (NTZNN) algorithm for controller design.

Main Results:

The developed tensegrity-based knee mechanism demonstrates high efficiency for exoskeleton applications.
The NTZNN controller exhibits significant anti-noise performance, outperforming conventional controllers.
Simulations and contrast results verify the precision and robustness of the NTZNN controller.

Conclusions:

The proposed tensegrity knee mechanism and NTZNN controller offer a unique and effective solution for rehabilitation exoskeletons.
The anti-noise capability of the NTZNN controller is a key advancement for reliable exoskeleton operation.
Further research can explore advanced control strategies and clinical validation.