scholarly journals Concurrent Validity Of Inertial Measurement Units With 3D Motion Analysis System For Joint Kinematics

2021 ◽  
Vol 53 (8S) ◽  
pp. 130-131
Author(s):  
Kathryn Balardi ◽  
Michael Johnson ◽  
Jaclyn Ross ◽  
Susan Chinworth ◽  
Srikant Vallabhajosula
Keyword(s):  
Motion Analysis ◽  
Concurrent Validity ◽  
Joint Kinematics ◽  
Motion Analysis System ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Measurement Units ◽  
Analysis System

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.

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

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.

Development of a Wearable Motion Analysis System for Evaluation and Rehabilitation of Mild Traumatic Brain Injury (mTBI)

2012 ◽  
Author(s):  
Stephanie L. Carey ◽  
Kevin Hufford ◽  
Amanda Martori ◽  
Mario Simoes ◽  
Francy Sinatra ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Brain Injuries ◽  
Training Session ◽  
Motion Analysis System ◽  
Laboratory Setting ◽  
Inertial Measurement ◽  
Gait Parameters ◽  
Measurement Units ◽  
Analysis System ◽  
Set Up

Mild traumatic brain injuries (mTBI) stem from a number of causes such as illnesses, strokes, accidents or battlefield traumas. These injuries can cause issues with everyday tasks, such as gait, and are linked with vestibular dysfunction [1]. Current technology that measures gait parameters often requires time consuming set up and post processing and is limited to the laboratory setting. The purpose of this study was to develop a wearable motion analysis system (WMAS) using five commercially available inertial measurement units (IMU) working in unison to record and output four gait parameters in a clinically relevant way. The WMAS has the potential to be used to 1) help diagnose mTBI or other neurocognitive disorders; 2) provide feedback to a clinician during a training session; 3) collect gait parameter data outside of the laboratory setting to determine rehabilitation progress; 4) provide quantitative outcome measures for rehabilitation efficacy.

scholarly journals The Validity of Wireless Earbud-Type Wearable Sensors for Head Angle Estimation and the Relationships of Head with Trunk, Pelvis, Hip, and Knee during Workouts

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 597
Author(s):  
Ae-Ryeong Kim ◽  
Ju-Hyun Park ◽  
Si-Hyun Kim ◽  
Kwang Bok Kim ◽  
Kyue-Nam Park
Keyword(s):  
Motion Analysis ◽  
Sagittal Plane ◽  
Wearable Sensors ◽  
Frontal Plane ◽  
Measurement Unit ◽  
Motion Analysis System ◽  
3D Motion ◽  
Trunk Motion ◽  
3D Motion Analysis ◽  
Analysis System

The present study was performed to investigate the validity of a wireless earbud-type inertial measurement unit (Ear-IMU) sensor used to estimate head angle during four workouts. In addition, relationships between head angle obtained from the Ear-IMU sensor and the angles of other joints determined with a 3D motion analysis system were investigated. The study population consisted of 20 active volunteers. The Ear-IMU sensor measured the head angle, while a 3D motion analysis system simultaneously measured the angles of the head, trunk, pelvis, hips, and knees during workouts. Comparison with the head angle measured using the 3D motion analysis system indicated that the validity of the Ear-IMU sensor was very strong or moderate in the sagittal and frontal planes. In addition, the trunk angle in the frontal plane showed a fair correlation with the head angle determined with the Ear-IMU sensor during a single-leg squat, reverse lunge, and standing hip abduction; the correlation was poor in the sagittal plane. Our results indicated that the Ear-IMU sensor can be used to directly estimate head motion and indirectly estimate trunk motion.

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