Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Functional Classification of Joints01:09

Functional Classification of Joints

5.1K
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...
5.1K
Structural Classification of Joints01:20

Structural Classification of Joints

4.6K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
4.6K
Ankle Joint01:10

Ankle Joint

2.0K
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...
2.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Structure-Based De Novo Design of Novel Dual DPP IV and PTP 1B Inhibitors (DDPI's).

Chemistry & biodiversity·2026
Same author

NMR-based serum metabolite and lipoprotein profiling for endometriosis across clinically relevant and physiological comparator settings: assessment of diagnostic utility and exploratory biological signals.

BMC medicine·2026
Same author

Exploring the renoprotective potential of Beta vulgaris in diabetic nephropathy: an integrated network pharmacology, molecular docking and dynamics simulation study.

Molecular diversity·2026
Same author

Unseen Wounds: Conceptualizing the Experience of Emotional Pain as a Distinct Neuropsychological Construct.

Cureus·2026
Same author

Adaptive-Lag approach for assessing baroreflex functions: validation with the eurobavar dataset.

Journal of human hypertension·2026
Same author

Dysregulated NK-cell gene expression defines the enduring symptoms of long COVID-19.

Frontiers in immunology·2026

Related Experiment Video

Updated: Sep 29, 2025

3D Kinematic Gait Analysis for Preclinical Studies in Rodents
10:19

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

Published on: August 3, 2019

10.8K

Gait Classification With Gait Inherent Attribute Identification From Ankle's Kinematics.

Yogesh Singh, Vineet Vashista

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |March 24, 2022
    PubMed
    Summary

    This study developed a real-time ankle joint algorithm using IMU sensors to classify walking modes like upstairs, downstairs, and treadmill. The system achieved high accuracy, showing potential for robotic gait interventions.

    More Related Videos

    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
    06:54

    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

    Published on: March 4, 2018

    14.3K
    Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
    04:37

    Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

    Published on: July 6, 2022

    2.5K

    Related Experiment Videos

    Last Updated: Sep 29, 2025

    3D Kinematic Gait Analysis for Preclinical Studies in Rodents
    10:19

    3D Kinematic Gait Analysis for Preclinical Studies in Rodents

    Published on: August 3, 2019

    10.8K
    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
    06:54

    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

    Published on: March 4, 2018

    14.3K
    Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
    04:37

    Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

    Published on: July 6, 2022

    2.5K

    Area of Science:

    • Biomechanics
    • Robotics
    • Human-Computer Interaction

    Background:

    • The ankle joint is crucial for mobility and stability during ambulation.
    • Gait patterns vary significantly in daily activities, impacting ankle-environment interaction.
    • Real-time classification of diverse walking modes is essential for advanced gait analysis and assistive technologies.

    Purpose of the Study:

    • To develop and validate a real-time algorithm for classifying human walking modes using ankle kinematic data.
    • To investigate the integration of biomechanical principles and subject-specific calibration for enhanced gait classification accuracy.
    • To assess the algorithm's potential for multimodal gait interventions in robotics.

    Main Methods:

    • Utilized a single-degree-of-freedom (DoF) Inertial Measurement Unit (IMU) axis on the ankle.
    • Extracted biomechanical and subject-specific walking attributes for real-time classification.
    • Implemented heuristics to combine sensor data from both feet for improved decision-making.
    • Tested the algorithm on forty healthy participants across various walking conditions (upstairs, downstairs, treadmill, overground, stationary).

    Main Results:

    • Achieved high classification accuracy: 89.57% for left sensors and 87.55% for right sensors.
    • Demonstrated effective real-time classification of five distinct walking modes.
    • Showcased improved performance by combining predictions from bilateral sensors.
    • Observed similar multimodal walking features in elderly participants via a case study.

    Conclusions:

    • The proposed algorithm reliably classifies multimodal human walking in real-time using ankle IMU data.
    • The system's biomechanical and subject-specific approach offers a robust framework for gait analysis.
    • The algorithm shows significant potential as an automatic switching mechanism for robotic gait interventions.