scholarly journals Use of the Azure Kinect to measure foot clearance during obstacle crossing

2021 ◽  
Author(s):  
Kohei Yoshimoto ◽  
Masahiro Shinya
Keyword(s):  
Motion Capture ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Random Errors ◽  
Obstacle Crossing ◽  
Risk Of Falls ◽  
Optical Motion ◽  
Foot Clearance ◽  
Optical Motion Capture ◽  
Motion Capture Systems

Obstacle crossing is a typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome these shortcomings, we aimed to develop a practical and inexpensive solution for measuring obstacle-crossing behavior by using the Microsoft Azure Kinect, one of the most promising markerless motion capture systems. We validated the Azure Kinect as a tool to measure foot clearance and compared its performance to that of an optical motion capture system (Qualisys). We also determined the effect of the Kinect sensor placement on measurement performance. Sixteen healthy young men crossed obstacles of different heights (50, 150, and 250 mm). Kinect sensors were placed in front of and beside the obstacle as well as diagonally between those positions. As indices of measurement quality, we counted the number of measurement failures and calculated the systematic and random errors between the foot clearance measured by the Kinect and Qualisys. We also calculated the Pearson correlation coefficients between the Kinect and Qualisys measurements. The number of measurement failures and the systematic and random error were minimized when the Kinect was placed diagonally in front of the obstacle on the same side as the trail limb. The high correlation coefficient (r > 0.890) observed between the Kinect and Qualisys measurements suggests that the Azure Kinect has excellent potential for measuring foot clearance during obstacle-crossing tasks.

scholarly journals Use of computer innovative technologies in improving the dartsmen training

2020 ◽  
Vol 26 ◽  
pp. 00061
Author(s):  
Elina Makarova ◽  
Vladislav Dubatovkin ◽  
Nataliya Berezinskaya ◽  
Lyudmila Barkhatova ◽  
Elena Oleynik
Keyword(s):  
Motion Capture ◽  
Body Parts ◽  
Visual Material ◽  
Video Cameras ◽  
Dart Throwing ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Effective Use ◽  
Near Future ◽  
Motion Capture Systems

The research is focused on studying the possibility of effective use of the dart grip system, the work of the athlete’s hand, to prepare the dartsman for competitions using the MOSAR complex. The experiment uses optical motion capture systems, a set of video cameras, led parameter sensors, and devices that allow to record the movement of body parts and a dart. This method of training and controlling dart throwing can serve as educational and visual material for training future athletes. The use of such motion capture systems in the near future may become one of the main aspects of training, both beginners and professionals, in many sports.

scholarly journals IMU gyroscopes are a valid alternative to 3D optical motion capture system for angular kinematics analysis in tennis

2020 ◽  
pp. 175433712096544 ◽  
Author(s):  
Gabriel Delgado-García ◽  
Jos Vanrenterghem ◽  
Emilio J Ruiz-Malagón ◽  
Pablo Molina-García ◽  
Javier Courel-Ibáñez ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Motion Capture ◽  
Correlation Coefficients ◽  
Strong Relationship ◽  
System Level ◽  
Optical Motion ◽  
Measurement Units ◽  
The Difference ◽  
Optical Motion Capture ◽  
Level Of Agreement

Whereas 3D optical motion capture (OMC) systems are considered the gold standard for kinematic assessment in sport science, they present some drawbacks that limit its use in the field. Inertial measurement units (IMUs) incorporating gyroscopes have been considered as a more practical alternative. Thus, the aim of the study was to evaluate the level of agreement for angular velocity between IMU gyroscopes and an OMC system for varying tennis strokes and intensities. In total, 240 signals of angular velocity from different body segments and types of strokes (forehand, backhand and service) were recorded from four players (two competition players and two beginners). The angular velocity of the IMU gyroscopes was compared to the angular velocity from the OMC system. Level of agreement was evaluated by correlation coefficients, magnitudes of errors in absolute and relative values and Bland-Altman plots. Differences between both systems were highly consistent within players’ skill (i.e. along the broad range of velocities) and axes ( x, y, z). Correlations ranged from 0.951 to 0.993, indicating a very strong relationship and concordance. The magnitude of the differences ranged from 4.4 to 35.4 deg·s−1. The difference relative to the maximum angular velocity achieved was less than 5.0%. The study concluded that IMUs and OMC systems showed comparable values. Thus, IMUs seem to be a valid alternative to detect meaningful differences in angular velocity during tennis groundstrokes in field-based experimentation.

DEVELOPMENT OF MOTION CAPTURE SYSTEM USING DUAL VIDEO CAMERAS FOR THE GAIT DESIGN OF A BIPED ROBOT

2011 ◽  
Vol 08 (02) ◽  
pp. 275-299 ◽  
Author(s):  
JUNG-YUP KIM ◽  
YOUNG-SEOG KIM
Keyword(s):  
Motion Capture ◽  
Human Walking ◽  
Human Gait ◽  
Motion Capture System ◽  
System Calibration ◽  
Walking Gait ◽  
Video Cameras ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

This paper, describes the development of a motion capture system with novel features for biped robots. In general, motion capture is effectively utilized in the field of computer animation. In the field of humanoid robotics, the number of studies attempting to design human-like gaits by using expensive optical motion capture systems is increasing. The optical motion capture systems used in these studies have involved a large number of cameras because such systems use small-sized ball markers; hence the position accuracy of the markers and the system calibration are very significant. However, since the human walking gait is a simple periodic motion rather than a complex motion, we have developed a specialized motion capture system for this study using dual video cameras and large band-type markers without high-level system calibration in order to capture the human walking gait. In addition to its lower complexity, the proposed capture method requires only a low-cost system and has high space efficiency. An image processing algorithm is also proposed for deriving the human gait data. Finally, we verify the reliability and accuracy of our system by comparing a zero moment point (ZMP) trajectory calculated by the motion captured data with a ZMP trajectory measured by foot force sensors.

Non-rigid alignment pipeline applied to human gait signals acquired with optical motion capture systems and inertial sensors

2020 ◽  
Vol 98 ◽  
pp. 109429 ◽  
Author(s):  
Rubén Soussé ◽  
Jorge Verdú ◽  
Ricardo Jauregui ◽  
Ventura Ferrer-Roca ◽  
Simone Balocco
Keyword(s):  
Motion Capture ◽  
Inertial Sensors ◽  
Human Gait ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

scholarly journals Comparison of Gait Analysis Between a Triaxial Accelerometer-Based Device and an Optical Motion Capture System

2020 ◽  
Author(s):  
Taisuke Ito ◽  
Yuichi Ota
Keyword(s):  
Gait Analysis ◽  
Motion Capture ◽  
Measurement Accuracy ◽  
Reaction Force ◽  
Correlation Coefficients ◽  
P Value ◽  
Motion Capture System ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Good Agreement

AYUMI EYE is an accelerometer-based gait analysis device that measures the 3D accelerations of the human trunk. This study investigated the measurement accuracy of the AYUMI EYE as hardware as well as the accuracy of the gait cycle extraction program via simultaneous measurements using AYUMI EYE, a ground reaction force (GRF), and an optical motion capture system called VICON. The study was conducted with four healthy individuals as participants. The gait data were obtained by simulating four different patterns for three trials each: normal walking, anterior-tilt walking, hemiplegic walking, and shuffling walking. The AYUMI EYE and VICON showed good agreement for both the acceleration and displacement data. The durations of subsequent stride cycles calculated using the AYUMI EYE and GRF were in good agreement based on the calculated cross-correlation coefficients (CCs) with an r value of 0.896 and p-value less than 0.05, and their accuracies for these results were sufficient.

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.

scholarly journals Performance of Optical Structural Vibration Monitoring Systems in Experimental Modal Analysis

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1239
Author(s):  
Maksat Kalybek ◽  
Mateusz Bocian ◽  
Nikolaos Nikitas
Keyword(s):  
Modal Analysis ◽  
Motion Capture ◽  
Experimental Modal Analysis ◽  
Vibration Monitoring ◽  
Structural Vibration ◽  
Monitoring Systems ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems ◽  
Optical Vibration

Image-based optical vibration measurement is an attractive alternative to the conventional measurement of structural dynamics predominantly relying on accelerometry. Although various optical vibration monitoring systems are now readily available, their performance is currently not well defined, especially in the context of experimental modal analysis. To this end, this study provides some of the first evidence of the capability of optical vibration monitoring systems in modal identification using input–output measurements. A comparative study is conducted on a scaled model of a 3D building frame set in a laboratory environment. The dynamic response of the model to an impulse excitation from an instrumented hammer, and an initial displacement, is measured by means of five optical motion capture systems. These include commercial and open-source systems based on laser Doppler velocimetry, fiducial markers and marker-less pattern recognition. The performance of these systems is analysed against the data obtained with a set of high-precision accelerometers. It is shown that the modal parameters identified from each system are not always equivalent, and that each system has limitations inherent to its design. Informed by these findings, a guidance for the deployment of the considered optical motion capture systems is given, aiding in their choice and implementation for structural vibration monitoring.

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