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Functional Classification of Joints

Functional Classification of Joints

Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...

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Related Experiment Video

Updated: Jan 15, 2026

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

Published on: February 12, 2018

Quantitative Assessment of Upper Limb Multi-Modal Feature Fusion Under Task-Oriented Movement.

Keping Liu, Guang Liu, Zhifei Zhai

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society

|January 13, 2026

Summary

This study introduces a new method for objectively assessing upper limb motor function in stroke survivors using multi-modal feature fusion. The novel approach enhances quantitative analysis and shows strong correlation with clinical scores for improved rehabilitation.

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Last Updated: Jan 15, 2026

An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

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Published on: February 12, 2018

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Published on: March 28, 2018

Author Spotlight: Enhancing Upper Limb Rehabilitation in Stroke Patients Through Advanced Robotic and Neuromodulation Technologies

Author Spotlight: Enhancing Upper Limb Rehabilitation in Stroke Patients Through Advanced Robotic and Neuromodulation Technologies

Published on: October 11, 2024

Area of Science:

Rehabilitation Medicine
Biomedical Engineering
Neuroscience

Background:

Traditional post-stroke motor function assessment relies on clinical experience, lacking quantitative analysis.
Objective assessment of upper limb motor status in hemiplegic patients is crucial for effective rehabilitation.

Purpose of the Study:

To propose and validate a novel, objective assessment method for upper limb motor function in post-stroke hemiplegic patients.
To develop a multi-modal feature fusion framework integrating kinematic and muscle synergy data for comprehensive motor function analysis.

Main Methods:

Extracted features from multi-modal upper limb movement data (kinematics and muscle synergy).
Quantified kinematic and muscle synergy using singular value decomposition (SVD) and similarity metric index.
Developed an aggregated classifier and a probability-based functional scoring mechanism using multi-modal feature fusion.

Main Results:

Integrating synergy analysis improved classification accuracy by over 2.3%.
Multi-modal feature fusion achieved 90.75% classification accuracy.
Assessment results showed significant correlation with standard clinical trial scores (r=-0.81, p=0.0147).

Conclusions:

The proposed multi-modal feature fusion method provides an objective and quantitative assessment of upper limb motor function post-stroke.
This novel framework demonstrates feasibility for clinical application in assessing hemiplegic patients, enhancing rehabilitation strategies.