scholarly journals 3D motion reconstruction for real-world camera motion

CVPR 2011 ◽  
2011 ◽  
Author(s):  
Yingying Zhu ◽  
Mark Cox ◽  
Simon Lucey
Keyword(s):  
Real World ◽  
Camera Motion ◽  
Motion Reconstruction ◽  
3D Motion

The relationship of hip rotation range, hip rotator strength and balance in healthy individuals

2020 ◽  
Vol 33 (5) ◽  
pp. 761-767
Author(s):  
Yongwook Kim ◽  
Seungmook Kang
Keyword(s):  
Motion Analysis ◽  
External Rotation ◽  
Dynamic Balance ◽  
Three Dimensional ◽  
Camera Motion ◽  
3D Motion ◽  
3D Motion Analysis ◽  
Balance Ability ◽  
Analysis System ◽  
The Relationship

BACKGROUND: Few studies have explored the relationship between muscle strength, range of motion (ROM), and balance in the horizontal plane of the hip joint using three-dimensional (3D) motion analysis. OBJECTIVE: We investigate the relationships of hip internal rotation (IR) and external rotation (ER) ROM, measured using a 3D motion capture system, with hip internal and external rotator strength and single-leg standing balance. METHODS: The participants were 40 healthy adults. Kinematic data on hip ROM were collected using an eight-camera motion analysis system. Hip rotational strength measurements were obtained using hand-held isometric dynamometry. A Single-leg standing test and a pendular test were conducted to evaluate static and dynamic balance ability using BioRescue. RESULTS: Significant correlations were found between hip strength and each variable measured during hip ROM assessments (p< 0.05). Significant positive correlations were found between the hip IR/ER strength ratio and the IR/ER ROM ratio (r= 0.72, p< 0.01). The subgroup with a normal IR/ER ratio of hip rotator strength and ROM showed significantly better dynamic balance ability than the subgroup with a hip rotator muscle imbalance (p< 0.05). CONCLUSIONS: There is a significant relationship between hip IR/ER strength and IR/ER ROM with a normal hip IR/ER strength and ROM ratio positively affecting dynamic balance ability.

The performance of a low-cost bio-amplifier on 3D human arm movement reconstruction

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Kayode P. Ayodele ◽  
Eniola A. Akinboboye ◽  
Morenikeji A. Komolafe
Keyword(s):  
Low Cost ◽  
Sampling Rate ◽  
Correlation Coefficients ◽  
Arm Movement ◽  
Spatial Filter ◽  
Microsoft Kinect ◽  
Linear Regression Models ◽  
Average Correlation ◽  
Motion Reconstruction ◽  
3D Motion

AbstractObjectivesIn this study, the performance of OpenBCI, a low-cost bio-amplifier, is assessed when used for 3D motion reconstruction.MethodsEleven scalp electrode locations from three subjects were used, with sampling rate of 125 Hz, subsequently band-pass filtered from 0.5 to 40 Hz. After segmentation into epochs, information-rich frequency ranges were determined using filter bank common spatial filter. Simultaneously, the actual hand motions of subjects were captured using a Microsoft Kinect sensor. Multimodal data streams were synchronized using the lab streaming layer (LSL) application. A modified version of an existing multiple linear regression models was employed to learn the relationship between the electroencephalography (EEG) feature input and the recorded kinematic data. To assess system performance with limited data, 10-fold cross validation was used.ResultsThe most information-rich frequency bands for subjects were found to be in the ranges of 5 – 9 Hz and 33 – 37 Hz. Hand lateralization accuracy for the three subjects were 97.4, 78.7 and 96.9% respectively. 3D position reconstructed with an average correlation coefficient of 0.21, 0.47 and 0.38 respectively along three pre-defined axes, with the corresponding average correlation coefficients for velocity being 0.21, 0.36 and 0.25 respectively. The results compare favourably with a cross-section of existing results, while cost-per-electrode costs were 76% lower than the average per-electrode cost for similar systems and 44% lower than the cheapest previously-reported system.ConclusionsThis study has shown that low-cost bio-amplifiers such as the OpenBCI can be used for 3D motion reconstruction tasks.

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