A Low-Cost Instrumented Spatial Linkage Accurately Determines ASIS Position during Cycle Ergometry

2007 ◽  
Vol 23 (3) ◽  
pp. 224-229 ◽  
Author(s):  
James C. Martin ◽  
Steven J. Elmer ◽  
Robert D. Horscroft ◽  
Nicholas A.T. Brown ◽  
Barry B. Shultz
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Cost Effective ◽  
Cycle Ergometry ◽  
Two Dimensional ◽  
Motion Capture System ◽  
Valid Measure ◽  
Kinematic Data ◽  
Vertical Error ◽  
Parasagittal Plane

The purpose of this study was to develop and evaluate an alternative method for determining the position of the anterior superior iliac spine (ASIS) during cycling. The approach used in this study employed an instrumented spatial linkage (ISL) system to determine the position of the ASIS in the parasagittal plane. A two-segment ISL constructed using aluminum segments, bearings, and digital encoders was tested statically against a calibration plate and dynamically against a video-based motion capture system. Four well-trained cyclists provided data at three pedaling rates. Statically, the ISL had a mean horizontal error of 0.03 ± 0.21 mm and a mean vertical error of −0.13 ± 0.59 mm. Compared with the video-based motion capture system, the agreement of the location of the ASIS had a mean error of 0.30 ± 0.55 mm for the horizontal dimension and −0.27 ± 0.60 mm for the vertical dimension. The ISL system is a cost-effective, accurate, and valid measure for two-dimensional kinematic data within a range of motion typical for cycling.

DEVELOPMENT OF A MOTION CAPTURE SYSTEM USING KINECT

2015 ◽  
Vol 76 (11) ◽  
Author(s):  
Katherina Bujang ◽  
Ahmad Faiz Ahmad Nazri ◽  
Ahmad Fidaudin Ahmad Azam ◽  
Jamaluddin Mahmud
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Microsoft Kinect ◽  
Motion Capture Data ◽  
Motion Capture System ◽  
Interface Motion ◽  
Measurement Analysis ◽  
Potential Alternative ◽  
Repeatability And Reproducibility ◽  
Data Tracking

Microsoft Kinect has been identified as a potential alternative tool in the field of motion capture due to its simplicity and low cost. To date, the application and potential of Microsoft Kinect has been vigorously explored especially for entertainment and gaming purposes. However, its motion capture capability in terms of repeatability and reproducibility is still not well addressed. Therefore, this study aims to explore and develop a motion capture system using Microsoft Kinect; focusing on developing the interface, motion capture protocol as well as measurement analysis. The work is divided into several stages which include installation (Microsoft Kinect and MATLAB); parameters and experimental setup, interface development; protocols development; motion capture; data tracking and measurement analysis. The results are promising, where the variances are found to be less than 1% for both repeatability and reproducibility analysis. This proves that the current study is significant and the gained knowledge could contribute

Lumbar Hyperextension in Baseball Pitching: A Potential Cause of Spondylolysis

2018 ◽  
Vol 34 (6) ◽  
pp. 429-434 ◽  
Author(s):  
Hardeep Singh ◽  
Mark Lee ◽  
Matthew J. Solomito ◽  
Christian Merrill ◽  
Carl Nissen
Keyword(s):  
Motion Capture ◽  
Glenohumeral Joint ◽  
External Rotation ◽  
Age Groups ◽  
Motion Capture System ◽  
Kinematic Data ◽  
Pelvic Motion ◽  
The Difference ◽  
Lumbar Extension ◽  
Upper Thoracic

Symptomatic spondylolysis/spondylolisthesis is thought to be caused by repetitive lumbar extension. About 8.9% of baseball pitchers that experience back pain will be diagnosed with spondylolysis. Therefore, this study aims to identify and quantify lumbar extension experienced during baseball pitching. It was hypothesized that young pitchers would exhibit less lumbar extension than older pitchers. A total of 187 healthy pitchers were divided into 3 age groups: youth, adolescent, and college. Kinematic data were collected at 250 Hz using a 3-D motion capture system. Lumbar motion was calculated as the difference between upper thoracic motion and pelvic motion over the pitching cycle. Lumbar “hyperextension” was defined as ≥20° past neutral. College pitchers had significantly greater lumbar extension compared with youth and adolescent pitchers at the point of maximum external rotation of the glenohumeral joint during the pitch cycle (−25° [13°], P = .04). For all age groups, lumbar hyperextension was present during the first 66% of the pitch cycle. Most pitchers spent 45% of pitch cycle in ≥30° of lumbar extension. Understanding that lumbar extension and hyperextension are components of the complex, multiplanar motions of the spine associated with baseball pitching can potentially help in both the prevention and management of symptomatic spondylolysis/spondylolisthesis.

scholarly journals SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System

2020 ◽  
Vol 14 ◽  
Author(s):  
Grady W. Jensen ◽  
Patrick van der Smagt ◽  
Egon Heiss ◽  
Hans Straka ◽  
Tobias Kohl
Keyword(s):  
Open Source ◽  
Motion Capture ◽  
High Speed ◽  
Low Cost ◽  
Camera Motion ◽  
Motion Capture System

scholarly journals Comparison of the Performance of the Leap Motion ControllerTM with a Standard Marker-Based Motion Capture System

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1750
Author(s):  
Amartya Ganguly ◽  
Gabriel Rashidi ◽  
Katja Mombaur
Keyword(s):  
Motion Capture ◽  
Gold Standard ◽  
Low Cost ◽  
Ring Finger ◽  
Healthcare Services ◽  
Leap Motion ◽  
Motion Capture System ◽  
Flexion Extension ◽  
Standard Marker ◽  
Motion Capture Systems

Over the last few years, the Leap Motion Controller™ (LMC) has been increasingly used in clinical environments to track hand, wrist and forearm positions as an alternative to the gold-standard motion capture systems. Since the LMC is marker-less, portable, easy-to-use and low-cost, it is rapidly being adopted in healthcare services. This paper demonstrates the comparison of finger kinematic data between the LMC and a gold-standard marker-based motion capture system, Qualisys Track Manager (QTM). Both systems were time synchronised, and the participants performed abduction/adduction of the thumb and flexion/extension movements of all fingers. The LMC and QTM were compared in both static measuring finger segment lengths and dynamic flexion movements of all fingers. A Bland–Altman plot was used to demonstrate the performance of the LMC versus QTM with Pearson’s correlation (r) to demonstrate trends in the data. Only the proximal interphalangeal joint (PIP) joint of the middle and ring finger during flexion/extension demonstrated acceptable agreement (r = 0.9062; r = 0.8978), but with a high mean bias. In conclusion, the study shows that currently, the LMC is not suitable to replace gold-standard motion capture systems in clinical settings. Further studies should be conducted to validate the performance of the LMC as it is updated and upgraded.

Design, Implementation, and Evaluation of Optical Low-Cost Motion Capture System

2011 ◽  
Author(s):  
Abhinav Chadda ◽  
Wenjuan Zhu ◽  
Ming C. Leu ◽  
Xiaoqing F. Liu
Keyword(s):  
Measurement Error ◽  
Software Architecture ◽  
Motion Capture ◽  
Real World ◽  
Virtual World ◽  
Low Cost ◽  
Architecture Design ◽  
Motion Capture System ◽  
Design Development ◽  
Coordinate Frames

This paper describes the design, implementation and evaluation of a low-cost motion capture system with support of interfaces for practically any types of cameras. We present the system’s software architecture design, development of software to implement and integrate several existing algorithms, and effective approaches to address practical issues such as object calibration and synchronizing the real-world and virtual-world coordinate frames. The motion capture system is developed to work with active markers and all the processing is done by the software on a mid-level workstation. With the Firefly MV cameras used, the developed system is capable of working at 60 frames per second, having the ability to simultaneously track the positions and orientations of five objects, with latency averaging about 15 ms, and with an average measurement error of about 0.65 mm between the distance of each pair of four LEDs mounted on a target that is placed 1.5–3.5 m from the cameras.

scholarly journals Accuracy of a Low-Cost 3D-Printed Wearable Goniometer for Measuring Wrist Motion

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4799
Author(s):  
Calvin Young ◽  
Sarah DeDecker ◽  
Drew Anderson ◽  
Michele L. Oliver ◽  
Karen D. Gordon
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Wearable Device ◽  
Matching Task ◽  
Motion Capture System ◽  
Wrist Motion ◽  
Flexion Extension ◽  
Optical Motion ◽  
3D Printed ◽  
Optical Motion Capture

Wrist motion provides an important metric for disease monitoring and occupational risk assessment. The collection of wrist kinematics in occupational or other real-world environments could augment traditional observational or video-analysis based assessment. We have developed a low-cost 3D printed wearable device, capable of being produced on consumer grade desktop 3D printers. Here we present a preliminary validation of the device against a gold standard optical motion capture system. Data were collected from 10 participants performing a static angle matching task while seated at a desk. The wearable device output was significantly correlated with the optical motion capture system yielding a coefficient of determination (R2) of 0.991 and 0.972 for flexion/extension (FE) and radial/ulnar deviation (RUD) respectively (p < 0.0001). Error was similarly low with a root mean squared error of 4.9° (FE) and 3.9° (RUD). Agreement between the two systems was quantified using Bland–Altman analysis, with bias and 95% limits of agreement of 3.1° ± 7.4° and −0.16° ± 7.7° for FE and RUD, respectively. These results compare favourably with current methods for occupational assessment, suggesting strong potential for field implementation.

Low-cost human motion capture system for postural analysis onboard ships

2011 ◽  
Author(s):  
Erica Nocerino ◽  
Sebastiano Ackermann ◽  
Silvio Del Pizzo ◽  
Fabio Menna ◽  
Salvatore Troisi
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Human Motion ◽  
Motion Capture System ◽  
Human Motion Capture ◽  
Postural Analysis
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