scholarly journals Test-retest reliability of knee kinematics measurement during gait with 3D motion analysis system

2018 ◽  
Vol 9 (6S) ◽  
pp. 1236 ◽  
Author(s):  
F. Z. Fairus ◽  
N. A. M. Nordin ◽  
D. K. A Singh
Keyword(s):  
Motion Analysis ◽  
Knee Kinematics ◽  
Motion Analysis System ◽  
Retest Reliability ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Analysis System ◽  
Test Retest Reliability

scholarly journals Optimising filtering parameters for a 3D motion analysis system

2015 ◽  
Vol 25 (5) ◽  
pp. 808-814 ◽  
Author(s):  
Sander Schreven ◽  
Peter J. Beek ◽  
Jeroen B.J. Smeets
Keyword(s):  
Motion Analysis ◽  
Motion Analysis System ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Analysis System

MOVEMENT MEASUREMENT VALIDITY AND RELIABILITY OF THE IMAGE J PROGRAM FOR KINEMATIC ANALYSIS

2016 ◽  
Vol 16 (08) ◽  
pp. 1640028 ◽  
Author(s):  
JEONG J. LEE ◽  
JOSHUA H. YOU
Keyword(s):  
Motion Analysis ◽  
Kinematic Analysis ◽  
Motion Analysis System ◽  
Validity And Reliability ◽  
Retest Reliability ◽  
Dynamic Movement ◽  
Angle Data ◽  
Hemiparetic Stroke ◽  
Analysis System ◽  
Test Retest Reliability

Background: While advanced motion analysis systems can provide accurate kinematic information, the majorities of motion analysis systems are stationary, expensive and time consuming. Image J is a Java-based image processing program that was originally developed at the National Institutes of Health and has rapidly gained widespread acceptance among rehabilitation specialists as a portable and affordable alternative motion analysis system. However, the validity and reliability of the Image J program have not been well established. Objective: The purpose of this study was to investigate the validity and test–retest reliability of the Image J kinematic analysis system. The Image J kinematic analysis system is designed to produce precise kinematic evidence during normal and pathological static and dynamic movement patterns. Methods: The Image J motion analysis system was concurrently compared with the electrogoniometer system as a reference standard measure by obtaining sagittal kinematic knee joint angle data. Results: Image J motion analysis system measurement revealed outstanding validity ([Formula: see text] and [Formula: see text]). The test–retest reliability for kinematic knee angle data showed remarkable consistency (Cronbach’s [Formula: see text]). Conclusions: This study provides the first evidence highlighting the Image J kinematic analysis system’s excellent validity and reliability for evaluating human kinematic movements in elderly people with hemiparetic stroke.

scholarly journals Can We Accurately Measure Axial Segment Coordination during Turning Using Inertial Measurement Units (IMUs)?

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2518 ◽  
Author(s):  
Fuengfa Khobkhun ◽  
Mark A. Hollands ◽  
Jim Richards ◽  
Amornpan Ajjimaporn
Keyword(s):  
Motion Analysis ◽  
Movement Disorders ◽  
Clinical Settings ◽  
Motion Analysis System ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Measurement Units ◽  
Analysis System

Camera-based 3D motion analysis systems are considered to be the gold standard for movement analysis. However, using such equipment in a clinical setting is prohibitive due to the expense and time-consuming nature of data collection and analysis. Therefore, Inertial Measurement Units (IMUs) have been suggested as an alternative to measure movement in clinical settings. One area which is both important and challenging is the assessment of turning kinematics in individuals with movement disorders. This study aimed to validate the use of IMUs in the measurement of turning kinematics in healthy adults compared to a camera-based 3D motion analysis system. Data were collected from twelve participants using a Vicon motion analysis system which were compared with data from four IMUs placed on the forehead, middle thorax, and feet in order to determine accuracy and reliability. The results demonstrated that the IMU sensors produced reliable kinematic measures and showed excellent reliability (ICCs 0.80–0.98) and no significant differences were seen in paired t-tests in all parameters when comparing the two systems. This suggests that the IMU sensors provide a viable alternative to camera-based motion capture that could be used in isolation to gather data from individuals with movement disorders in clinical settings and real-life situations.

PRIMAS: a real-time 3D motion-analysis system

1994 ◽  
Author(s):  
Jan C. Sabel ◽  
Hans L. J. van Veenendaal ◽  
E. Hans Furnee
Keyword(s):  
Real Time ◽  
Motion Analysis ◽  
Motion Analysis System ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Analysis System

scholarly journals Determine the Foot Strike Pattern Using Inertial Sensors

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Tzyy-Yuang Shiang ◽  
Tsung-Yu Hsieh ◽  
Yin-Shin Lee ◽  
Chen-Chi Wu ◽  
Meng-Chieh Yu ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Pitch Angle ◽  
Rapid Development ◽  
Motion Analysis System ◽  
Science Field ◽  
3D Motion ◽  
Sport Science ◽  
3D Motion Analysis ◽  
Foot Strike ◽  
Analysis System

From biomechanical point of view, strike pattern plays an important role in preventing potential injury risk in running. Traditionally, strike pattern determination was conducted by using 3D motion analysis system with cameras. However, the procedure is costly and not convenient. With the rapid development of technology, sensors have been applied in sport science field lately. Therefore, this study was designed to determine the algorithm that can identify landing strategies with a wearable sensor. Six healthy male participants were recruited to perform heel and forefoot strike strategies at 7, 10, and 13 km/h speeds. The kinematic data were collected by Vicon 3D motion analysis system and 2 inertial measurement units (IMU) attached on the dorsal side of both shoes. The data of each foot strike were gathered for pitch angle and strike index analysis. Comparing the strike index from IMU with the pitch angle from Vicon system, our results showed that both signals exhibited highly correlated changes between different strike patterns in the sagittal plane (r=0.98). Based on the findings, the IMU sensors showed potential capabilities and could be extended beyond the context of sport science to other fields, including clinical applications.

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