scholarly journals Comparison of execution times of Kaedah A for different movement trajectories using Virtual Sensei Lite

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Mohd Firdaus Abdul Razak ◽  
Mohd Saiful Aizat Mohd Shafie ◽  
Muhamad Sharafee Shamsudin ◽  
Muhamad Faris Che Aminudin
Keyword(s):  
Motion Capture ◽  
Maximum Velocity ◽  
Motion Capture System ◽  
Kinect Sensor ◽  
Left Hand ◽  
Curve Path ◽  
Movement Trajectories ◽  
Kinematic Characteristics ◽  
Execution Times

The main objective of this study is to compare the execution times produced by fending off techniques of Seni Silat Cekak Malaysia (SSCM), Kaedah A for different movement trajectories. Three kind of movement trajectories for Kaedah A were carried out which were Trajectory A (normal path), Trajectory B (curve path) and Trajectory C (starting by pulling the hand to the back and continue as Trajectory A). The experiments were conducted using motion capture system where the movement position of the left hand during the execution of Kaedah A were recorded by Kinect sensor, prior to storing and processing via Virtual Sensei (VS) Lite software. A total of four (4) experienced practitioners from SSCM with their consent were selected to perform Kaedah A techniques. The data acquired were further analyzed to determine their kinematic characteristics. Results showed that the execution of Kaedah A using Trajectory A produced the shortest time and highest velocity with average of 0.071±0.007s and 6.438±0.863ms-1 respectively, compared to Trajectory B (0.087±0.011s, 5.230±0.578 ms-1) and Trajectory C (0.149±0.015s, 2.903±0.273ms-1). Therefore, Trajectory A is considered to be more efficient than Trajectory B and Trajectory C in terms of execution times and maximum velocity produced by Kaedah A.

scholarly journals Placement Recommendations for Single Kinect-Based Motion Capture System in Unilateral Dynamic Motion Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1076
Author(s):  
Laisi Cai ◽  
Dongwei Liu ◽  
Ye Ma
Keyword(s):  
Motion Analysis ◽  
Motion Capture ◽  
Upper Limb ◽  
Kinematic Model ◽  
Sensor Placement ◽  
Motion Capture System ◽  
Kinect Sensor ◽  
3D Motion ◽  
Flexion Extension ◽  
3D Motion Capture

Low-cost, portable, and easy-to-use Kinect-based systems achieved great popularity in out-of-the-lab motion analysis. The placement of a Kinect sensor significantly influences the accuracy in measuring kinematic parameters for dynamics tasks. We conducted an experiment to investigate the impact of sensor placement on the accuracy of upper limb kinematics during a typical upper limb functional task, the drinking task. Using a 3D motion capture system as the golden standard, we tested twenty-one Kinect positions with three different distances and seven orientations. Upper limb joint angles, including shoulder flexion/extension, shoulder adduction/abduction, shoulder internal/external rotation, and elbow flexion/extension angles, are calculated via our developed Kinect kinematic model and the UWA kinematic model for both the Kinect-based system and the 3D motion capture system. We extracted the angles at the point of the target achieved (PTA). The mean-absolute-error (MEA) with the standard represents the Kinect-based system’s performance. We conducted a two-way repeated measure ANOVA to explore the impacts of distance and orientation on the MEAs for all upper limb angles. There is a significant main effect for orientation. The main effects for distance and the interaction effects do not reach statistical significance. The post hoc test using LSD test for orientation shows that the effect of orientation is joint-dependent and plane-dependent. For a complex task (e.g., drinking), which involves body occlusions, placing a Kinect sensor right in front of a subject is not a good choice. We suggest that place a Kinect sensor at the contralateral side of a subject with the orientation around 30∘ to 45∘ for upper limb functional tasks. For all kinds of dynamic tasks, we put forward the following recommendations for the placement of a Kinect sensor. First, set an optimal sensor position for capture, making sure that all investigated joints are visible during the whole task. Second, sensor placement should avoid body occlusion at the maximum extension. Third, if an optimal location cannot be achieved in an out-of-the-lab environment, researchers could put the Kinect sensor at an optimal orientation by trading off the factor of distance. Last, for those need to assess functions of both limbs, the users can relocate the sensor and re-evaluate the functions of the other side once they finish evaluating functions of one side of a subject.

scholarly journals The Development of Motion Capture System Based on Kinect Sensor and Bluetooth-Gloves

2017 ◽  
Vol 176 ◽  
pp. 506-513 ◽  
Author(s):  
V.N. Iliukhin ◽  
K.B. Mitkovskii ◽  
D.A. Bizyanova ◽  
A.A. Akopyan
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Kinect Sensor

A study on validating KinectV2 in comparison of Vicon system as a motion capture system for using in Health Engineering in industry

2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Mahvash Jebeli ◽  
Alireza Bilesan ◽  
Ahmadreza Arshi
Keyword(s):  
Motion Capture ◽  
Three Dimensional ◽  
Vertical Axis ◽  
Coefficient Of Determination ◽  
Motion Capture System ◽  
Kinect Sensor ◽  
3D Data ◽  
Human Movements ◽  
Analysis Laboratory ◽  
Industrial Environments

AbstractThe currently available commercial motion capture systems are constrained by space requirement and thus pose difficulties when used in developing kinematic description of human movements within the existing manufacturing and production cells. The Kinect sensor does not share similar limitations but it is not as accurate. The proposition made in this article is to adopt the Kinect sensor in to facilitate implementation of Health Engineering concepts to industrial environments. This article is an evaluation of the Kinect sensor accuracy when providing three dimensional kinematic data. The sensor is thus utilized to assist in modeling and simulation of worker performance within an industrial cell. For this purpose, Kinect 3D data was compared to that of Vicon motion capture system in a gait analysis laboratory. Results indicated that the Kinect sensor exhibited a coefficient of determination of 0.9996 on the depth axis and 0.9849 along the horizontal axis and 0.2767 on vertical axis. The results prove the competency of the Kinect sensor to be used in the industrial environments.

Gender differences in the Achilles tendon load during the fencing lunge

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Jonathan Kenneth Sinclair ◽  
Lindsay Bottoms
Keyword(s):  
Gender Differences ◽  
Achilles Tendon ◽  
Motion Capture ◽  
Tendon Injury ◽  
Force Platform ◽  
Motion Capture System ◽  
3D Motion ◽  
Loading Rates ◽  
Tendon Pathology ◽  
3D Motion Capture

AbstractRecent epidemiological analyses in fencing have shown that injuries and pain linked specifically to fencing training/competition were evident in 92.8% of fencers. Specifically the prevalence of Achilles tendon pathology has increased substantially in recent years, and males have been identified as being at greater risk of Achilles tendon injury compared to their female counterparts. This study aimed to examine gender differences in Achilles tendon loading during the fencing lunge.Achilles tendon load was obtained from eight male and eight female club level epee fencers using a 3D motion capture system and force platform information as they completed simulated lunges. Independent t-tests were performed on the data to determine whether differences existed.The results show that males were associated with significantly greater Achilles tendon loading rates in comparison to females.This suggests that male fencers may be at greater risk from Achilles tendon pathology as a function of fencing training/ competition.

Magnetic motion capture system using LC resonant magnetic marker composed of Ni–Zn ferrite core

2006 ◽  
Vol 99 (8) ◽  
pp. 08B312 ◽  
Author(s):  
S. Hashi ◽  
M. Toyoda ◽  
M. Ohya ◽  
Y. Okazaki ◽  
S. Yabukami ◽  
...  
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Ferrite Core ◽  
Zn Ferrite ◽  
Magnetic Marker

scholarly journals Modeling and evaluating beat gestures for social robots

2021 ◽  
Author(s):  
Unai Zabala ◽  
Igor Rodriguez ◽  
José María Martínez-Otzeta ◽  
Elena Lazkano
Keyword(s):  
Motion Capture ◽  
Motion Capture System ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Desirable Feature ◽  
Quantitative Results ◽  
Path Lengths ◽  
End Effectors ◽  
The One ◽  
Made In

AbstractNatural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemented by the Fréchet Gesture Distance (FGD) that aims to measure the fidelity of the generated gestures with respect to the provided ones. Results show that the described system is able to learn natural gestures just by observation and improves the one developed with a simpler motion capture system. The quantitative results are sustained by questionnaire based human evaluation.

Assessing the Ergonomic Benefits of a New Adjustable Forklift Backrest

2020 ◽  
Vol 64 (1) ◽  
pp. 976-980
Author(s):  
Pranav Madhav Kuber ◽  
Ehsan Rashedi
Keyword(s):  
Comparative Study ◽  
Motion Capture ◽  
Center Of Pressure ◽  
Body Movement ◽  
Pressure Change ◽  
Motion Capture System ◽  
Design Features ◽  
Wide Range ◽  
Body Sizes ◽  
The Mean

A new forklift backrest has been developed by incorporating adjustability concepts into the design to facilitate comfort to a wide range of users. We have conducted a comparative study between the new and original backrests to assess the effectiveness of design features. Using the phenomenon of restlessness, discomfort of the user was associated with the amount of body movement, where we have used a motion- capture system and a force platform to quantify the individuals’ movement for a wide range of body sizes. Meanwhile, subjective comfort and design feedback were collected using a questionnaire. Our results showed a reduction in the mean torso movement and the maximum center of pressure change of location by 300 and 6 mm, respectively, for the new design. Taking advantage of adjustability feature, the new backrest design exhibited enhanced comfort for longer durations and reduced magnitude of discomfort for a wide range of participants’ body sizes.

Sign in / Sign up

Export Citation Format

Share Document