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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...

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Related Experiment Video

Updated: Feb 18, 2026

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

Markerless Knee Joint Position Measurement Using Depth Data during Stair Walking.

Ami Ogawa¹, Akira Mita², Ayanori Yorozu³

¹School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. ami_ogawa@keio.jp.

Sensors (Basel, Switzerland)

|November 23, 2017

Summary

Monitoring stair walking with Microsoft Kinect v2 can help detect early musculoskeletal diseases. A new depth data method for knee joint tracking is more accurate than skeleton tracking, aiding in early disease detection.

Keywords:

3D motion capture system Kinect v2 VICON depth data gait measurement knee joint position markerless measurement skeleton tracking stair climbing stair descending

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Related Experiment Videos

Last Updated: Feb 18, 2026

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Published on: March 14, 2017

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

Area of Science:

Biomechanics
Medical Technology
Rehabilitation Engineering

Background:

Stair climbing and descending are crucial daily activities.
Monitoring stair walking can facilitate early detection of musculoskeletal diseases.
Markerless systems are needed for unobtrusive gait analysis during stair locomotion.

Purpose of the Study:

To evaluate the accuracy of Microsoft Kinect v2's skeleton tracking for stair walking.
To develop and assess a novel method using Kinect v2 depth data for 3D knee joint position estimation during stair walking.
To compare the accuracy of the novel depth data method against Kinect v2's skeleton tracking.

Main Methods:

Utilized Microsoft Kinect v2 for markerless motion capture during stair walking.
Developed a new algorithm to estimate the 3D knee joint position using depth data from Kinect v2.
Employed a 3D motion capture system as the gold standard for simultaneous measurement and comparison.

Main Results:

The novel depth data method demonstrated higher accuracy in estimating 3D knee joint position compared to Kinect v2's skeleton tracking.
The mean error for the depth data method was 43.2 ± 27.5 mm.
The mean error for Kinect v2's skeleton tracking was 50.4 ± 23.9 mm.

Conclusions:

The developed depth data method offers a more accurate approach for monitoring stair walking using Kinect v2.
This technique holds potential for non-invasive, early detection of musculoskeletal disorders through stair activity analysis.
Markerless monitoring of stair walking can be advanced with depth data processing for clinical applications.