scholarly journals Dual Kinect v2 system can capture lower limb kinematics reasonably well in a clinical setting: concurrent validity of a dual camera markerless motion capture system in professional football players

2018 ◽  
Vol 4 (1) ◽  
pp. e000441 ◽  
Author(s):  
Argyro Kotsifaki ◽  
Rodney Whiteley ◽  
Clint Hansen
Keyword(s):  
Motion Capture ◽  
Excellent Agreement ◽  
Lower Limb ◽  
Motion Capture System ◽  
Kinect V2 ◽  
Markerless Motion Capture ◽  
Flexion Extension ◽  
Limb Kinematics ◽  
Kinematic Evaluation ◽  
Lower Limb Kinematics

ObjectivesTo determine whether a dual-camera markerless motion capture system can be used for lower limb kinematic evaluation in athletes in a preseason screening setting.DesignDescriptive laboratory study.SettingLaboratory setting.ParticipantsThirty-four (n=34) healthy athletes.Main outcome measuresThree dimensional lower limb kinematics during three functional tests: Single Leg Squat (SLS), Single Leg Jump, Modified Counter-movement Jump. The tests were simultaneously recorded using both a marker-based motion capture system and two Kinect v2 cameras using iPi Mocap Studio software.ResultsExcellent agreement between systems for the flexion/extension range of motion of the shin during all tests and for the thigh abduction/adduction during SLS were seen. For peak angles, results showed excellent agreement for knee flexion. Poor correlation was seen for the rotation movements.ConclusionsThis study supports the use of dual Kinect v2 configuration with the iPi software as a valid tool for assessment of sagittal and frontal plane hip and knee kinematic parameters but not axial rotation in athletes.

scholarly journals Multi-Camera Portable Markerless Motion Capture System Accurately Captures Lower Limb Kinematics During Functional Tasks

2021 ◽  
Vol 53 (8S) ◽  
pp. 176-176
Author(s):  
Cortney Armitano-Lago ◽  
Courtney Chaaban ◽  
M Spencer Cain ◽  
Ryan MacPherson ◽  
Jackson R. Elpers ◽  
...  
Keyword(s):  
Motion Capture ◽  
Lower Limb ◽  
Motion Capture System ◽  
Markerless Motion Capture ◽  
Limb Kinematics ◽  
Lower Limb Kinematics

scholarly journals The Influence of Minimalist and Maximalist Footwear on Patellofemoral Kinetics During Running

2016 ◽  
Vol 32 (4) ◽  
pp. 359-364 ◽  
Author(s):  
Jonathan Sinclair ◽  
Jim Richards ◽  
James Selfe ◽  
James Fau-Goodwin ◽  
Hannah Shore
Keyword(s):  
Motion Capture ◽  
Lower Limb ◽  
Patellofemoral Joint ◽  
Musculoskeletal Modeling ◽  
Camera Motion ◽  
Motion Capture System ◽  
Current Investigation ◽  
Limb Kinematics ◽  
Pain Symptoms ◽  
Lower Limb Kinematics

The current study aimed to comparatively examine the effects of minimalist, maximalist, and conventional footwear on the loads experienced by the patellofemoral joint during running. Twenty male participants ran over a force platform at 4.0 m×s–1. Lower limb kinematics were collected using an 8-camera motion capture system allowing patellofemoral kinetics to be quantified using a musculoskeletal modeling approach. Differences in patellofemoral kinetic parameters were examined using one-way repeatedmeasures ANOVA. The results showed the peak patellofemoral force and pressure were significantly larger in conventional (4.70 ± 0.91 BW, 13.34 ± 2.43 MPa) and maximalist (4.74 ± 0.88 BW, 13.59 ± 2.63 MPa) compared with minimalist footwear (3.87 ± 1.00 BW, 11.59 ± 2.63 MPa). It was also revealed that patellofemoral force per mile was significantly larger in conventional (246.81 ± 53.21 BW) and maximalist (251.94 ± 59.17 BW) as compared with minimalist (227.77 ± 58.60 BW) footwear. As excessive loading of the patellofemoral joint has been associated with the etiology of patellofemoral pain symptoms, the current investigation indicates that minimalist footwear may be able reduce runners’ susceptibility to patellofemoral disorders.

scholarly journals Concurrent assessment of gait kinematics using marker-based and markerless motion capture

2020 ◽  
Author(s):  
Robert Kanko ◽  
Elise Laende ◽  
Elysia Davis ◽  
W. Scott Selbie ◽  
Kevin J. Deluzio
Keyword(s):  
Motion Capture ◽  
Lower Limb ◽  
Video Data ◽  
Motion Capture System ◽  
Kinematic Data ◽  
Markerless Motion Capture ◽  
Common Marker ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

AbstractKinematic analysis is a useful and widespread tool used in research and clinical biomechanics for the estimation of human pose and the quantification of human movement. Common marker-based optical motion capture systems are expensive, time intensive, and require highly trained operators to obtain kinematic data. Markerless motion capture systems offer an alternative method for the measurement of kinematic data with several practical benefits. This work compared the kinematics of human gait measured using a deep learning algorithm-based markerless motion capture system to those of a common marker-based motion capture system. Thirty healthy adult participants walked on a treadmill while data were simultaneously recorded using eight video cameras (markerless) and seven infrared optical motion capture cameras (marker-based). Video data were processed using markerless motion capture software, marker-based data were processed using marker-based capture software, and both sets of data were compared. The average root mean square distance (RMSD) between corresponding joints was less than 3 cm for all joints except the hip, which was 4.1 cm. Lower limb segment angles indicated pose estimates from both systems were very similar, with RMSD of less than 6° for all segment angles except those that represent rotations about the long axis of the segment. Lower limb joint angles captured similar patterns for flexion/extension at all joints, ab/adduction at the knee and hip, and toe-in/toe-out at the ankle. These findings demonstrate markerless motion capture can measure similar 3D kinematics to those from marker-based systems.

Analysis of the Relationships between Balance Ability and Walking in Terms of Muscle Activities and Lower Limb Kinematics and Kinetics

Biomechanics ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 190-201
Author(s):  
Pathmanathan Cinthuja ◽  
Graham Arnold ◽  
Rami J. Abboud ◽  
Weijie Wang
Keyword(s):  
Regression Analysis ◽  
Lower Limb ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression Analysis ◽  
Vastus Medialis ◽  
Balance Test ◽  
Balance Ability ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Kinematics And Kinetics

There is a lack of evidence about the ways in which balance ability influences the kinematic and kinetic parameters and muscle activities during gait among healthy individuals. The hypothesis is that balance ability would be associated with the lower limb kinematics, kinetics and muscle activities during gait. Twenty-nine healthy volunteers (Age 32.8 ± 9.1; 18 males and 11 females) performed a Star Excursion Balance test to measure their dynamic balance and walked for at least three trials in order to obtain a good quality of data. A Vicon® 3D motion capture system and AMTI® force plates were used for the collection of the movement data. The selected muscle activities were recorded using Delsys® Electromyography (EMG). The EMG activities were compared using the maximum values and root mean squared (RMS) values within the participants. The joint angle, moment, force and power were calculated using a Vicon Plug-in-Gait model. Descriptive analysis, correlation analysis and multivariate linear regression analysis were performed using SPSS version 23. In the muscle activities, positive linear correlations were found between the walking and balance test in all muscles, e.g., in the multifidus (RMS) (r = 0.800 p < 0.0001), vastus lateralis (RMS) (r = 0.639, p < 0.0001) and tibialis anterior (RMS) (r = 0.539, p < 0.0001). The regression analysis models showed that there was a strong association between balance ability (i.e., reaching distance) and the lower limb muscle activities (i.e., vastus medialis–RMS) (R = 0.885, p < 0.0001), and also between balance ability (i.e., reaching distance) and the lower limb kinematics and kinetics during gait (R = 0.906, p < 0.0001). In conclusion, the results showed that vastus medialis (RMS) muscle activity mainly contributes to balance ability, and that balance ability influences the lower limb kinetics and kinematics during gait.

scholarly journals Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

2021 ◽  
pp. 110414
Author(s):  
Robert M. Kanko ◽  
Elise K. Laende ◽  
Gerda Strutzenberger ◽  
Marcus Brown ◽  
W. Scott Selbie ◽  
...  
Keyword(s):  
Deep Learning ◽  
Motion Capture ◽  
Learning Algorithm ◽  
Motion Capture System ◽  
Deep Learning Algorithm ◽  
Markerless Motion Capture ◽  
Gait Parameters

Rate of loading, but not lower limb kinematics or muscle activity, is moderated by limb and aerial variation when surfers land aerials

2021 ◽  
pp. 1-9
Author(s):  
James R. Forsyth ◽  
Christopher J. Richards ◽  
Ming-Chang Tsai ◽  
John W. Whitting ◽  
Diane L. Riddiford-Harland ◽  
...  
Keyword(s):  
Lower Limb ◽  
Muscle Activity ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Rate Of Loading

Changes in drive phase lower limb kinematics during a 60min cycling time trial

2012 ◽  
Vol 15 (2) ◽  
pp. 169-174 ◽  
Author(s):  
Mark G.L. Sayers ◽  
Amanda L. Tweddle ◽  
Joshua Every ◽  
Aaron Wiegand
Keyword(s):  
Lower Limb ◽  
Time Trial ◽  
Cycling Time Trial ◽  
Limb Kinematics ◽  
Lower Limb Kinematics ◽  
Cycling Time
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