scholarly journals Effect of String Notches on Tennis Racket Spin Performance : Ball Spin Rate, Contact Time and Post-Impact Ball Velocity with Ultra-High-Speed Video Analysis(Mechanical Systems)

2010 ◽  
Vol 76 (770) ◽  
pp. 2646-2655 ◽  
Author(s):  
Yoshihiko KAWAZOE ◽  
Yukihiro TAKEDA ◽  
Masamichi NAKAGAWA
Keyword(s):  
Video Analysis ◽  
Contact Time ◽  
High Speed ◽  
Mechanical Systems ◽  
Tennis Racket ◽  
High Speed Video ◽  
Ultra High Speed ◽  
Ball Velocity ◽  
Post Impact

scholarly journals Agreement Between Spatiotemporal Gait Parameters Measured by a Markerless Motion Capture System and Two Reference Systems—a Treadmill-Based Photoelectric Cell and High-Speed Video Analyses: Comparative Study (Preprint)

2020 ◽  
Author(s):  
Felipe García-Pinillos ◽  
Diego Jaén-Carrillo ◽  
Victor Soto Hermoso ◽  
Pedro Latorre Román ◽  
Pedro Delgado ◽  
...  
Keyword(s):  
Video Analysis ◽  
Contact Time ◽  
High Speed ◽  
Step Length ◽  
Flight Time ◽  
Reference Systems ◽  
Random Errors ◽  
Step Frequency ◽  
Temporal Parameters ◽  
High Speed Video

BACKGROUND Markerless systems to capture body motion require no markers to be attached to the body, thereby improving clinical feasibility and testing time. However, the lack of markers might affect the accuracy of measurements. OBJECTIVE This study aimed to determine the absolute reliability and concurrent validity of the Kinect system with MotionMetrix software for spatiotemporal variables during running at a comfortable velocity, by comparing data between the combination system and two widely used systems—OptoGait and high-speed video analysis at 1000 Hz. METHODS In total, 25 runners followed a running protocol on a treadmill at a speed of 12 km/h. The Kinect+MotionMetrix combination measured spatiotemporal parameters during running (ie, contact time, flight time, step frequency, and step length), which were compared to those obtained from two reference systems. RESULTS Regardless of the system, flight time had the highest coefficients of variation (OptoGait: 16.4%; video analysis: 17.3%; Kinect+MotionMetrix: 23.2%). The rest of the coefficients of variation reported were lower than 8.1%. Correlation analysis showed very high correlations (<i>r</i>&gt;0.8; <i>P</i>&lt;.001) and almost perfect associations (intraclass correlation coefficient&gt;0.81) between systems for all the spatiotemporal parameters except contact time, which had lower values. Bland-Altman plots revealed smaller systematic biases and random errors for step frequency and step length and larger systematic biases and random errors for temporal parameters with the Kinect+MotionMetrix system as compared to OptoGait (difference: contact time +3.0%, flight time −7.9%) and high-speed video analysis at 1000 Hz (difference: contact time +4.2%, flight time −11.3%). Accordingly, heteroscedasticity was found between systems for temporal parameters (<i>r</i><sup>2</sup>&gt;0.1). CONCLUSIONS The results indicate that the Kinect+MotionMetrix combination slightly overestimates contact time and strongly underestimates flight time as compared to the OptoGait system and high-speed video analysis at 1000 Hz. However, it is a valid tool for measuring step frequency and step length when compared to reference systems. Future studies should determine the reliability of this system for determining temporal parameters.

scholarly journals Agreement Between Spatiotemporal Gait Parameters Measured by a Markerless Motion Capture System and Two Reference Systems—a Treadmill-Based Photoelectric Cell and High-Speed Video Analyses: Comparative Study

10.2196/19498 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e19498
Author(s):  
Felipe García-Pinillos ◽  
Diego Jaén-Carrillo ◽  
Victor Soto Hermoso ◽  
Pedro Latorre Román ◽  
Pedro Delgado ◽  
...  
Keyword(s):  
Video Analysis ◽  
Contact Time ◽  
High Speed ◽  
Step Length ◽  
Flight Time ◽  
Reference Systems ◽  
Random Errors ◽  
Step Frequency ◽  
Temporal Parameters ◽  
High Speed Video

Background Markerless systems to capture body motion require no markers to be attached to the body, thereby improving clinical feasibility and testing time. However, the lack of markers might affect the accuracy of measurements. Objective This study aimed to determine the absolute reliability and concurrent validity of the Kinect system with MotionMetrix software for spatiotemporal variables during running at a comfortable velocity, by comparing data between the combination system and two widely used systems—OptoGait and high-speed video analysis at 1000 Hz. Methods In total, 25 runners followed a running protocol on a treadmill at a speed of 12 km/h. The Kinect+MotionMetrix combination measured spatiotemporal parameters during running (ie, contact time, flight time, step frequency, and step length), which were compared to those obtained from two reference systems. Results Regardless of the system, flight time had the highest coefficients of variation (OptoGait: 16.4%; video analysis: 17.3%; Kinect+MotionMetrix: 23.2%). The rest of the coefficients of variation reported were lower than 8.1%. Correlation analysis showed very high correlations (r>0.8; P<.001) and almost perfect associations (intraclass correlation coefficient>0.81) between systems for all the spatiotemporal parameters except contact time, which had lower values. Bland-Altman plots revealed smaller systematic biases and random errors for step frequency and step length and larger systematic biases and random errors for temporal parameters with the Kinect+MotionMetrix system as compared to OptoGait (difference: contact time +3.0%, flight time −7.9%) and high-speed video analysis at 1000 Hz (difference: contact time +4.2%, flight time −11.3%). Accordingly, heteroscedasticity was found between systems for temporal parameters (r2>0.1). Conclusions The results indicate that the Kinect+MotionMetrix combination slightly overestimates contact time and strongly underestimates flight time as compared to the OptoGait system and high-speed video analysis at 1000 Hz. However, it is a valid tool for measuring step frequency and step length when compared to reference systems. Future studies should determine the reliability of this system for determining temporal parameters.

Influence of RunScribe™ placement on the accuracy of spatiotemporal gait characteristics during running

2019 ◽  
Vol 234 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Felipe García-Pinillos ◽  
José M Chicano-Gutiérrez ◽  
Emilio J Ruiz-Malagón ◽  
Luis E Roche-Seruendo
Keyword(s):  
Video Analysis ◽  
Contact Time ◽  
High Speed ◽  
Intraclass Correlation ◽  
Step Length ◽  
Flight Time ◽  
Systematic Bias ◽  
Step Frequency ◽  
High Speed Video ◽  
Spatiotemporal Parameters

This study aimed to examine the influence of RunScribe location (i.e. lace shoe vs heel shoe) on the accuracy of spatiotemporal gait characteristics during running by comparing data with a high-speed video analysis system at 1000 Hz. A total of 49 endurance runners performed a running protocol on a treadmill at comfortable velocity. Two systems were used to determine spatiotemporal parameters (i.e. contact time, flight time, step frequency, and step length) during running: high-speed video analysis at 1000 Hz and two different RunScribe placements (i.e. lace shoe vs heel shoe). The pairwise comparisons showed some between-system differences in both lace shoe (contact time: p = 0.009; step frequency: p = 0.001) and heel shoe (flight time: p = 0.006; step frequency: p = 0.010), although the effect sizes were small (effect size < 0.3 in all cases). The intraclass correlation coefficients revealed an almost perfect association between systems for contact time and flight time (intraclass correlation coefficient: 0.85–0.90), and step length and step frequency (intraclass correlation coefficient: 0.96–0.97), regardless of the RunScribe placement. Bland–Altman plots revealed that the lace shoe location yielded smaller systematic bias, random errors, and narrower limits of agreement for spatiotemporal parameters during running, except for SF, which had a higher accuracy in a heel shoe location. The results suggest that RunScribe is a valid system to measure spatiotemporal parameters during running on a treadmill according to a high-speed video analysis at 1000 Hz. In addition, the data indicate that the location of the RunScribe system (lace shoe vs heel shoe) plays an important role on the accuracy of spatiotemporal parameters. The lace shoe placement showed smaller systematic bias, random errors, and narrower limits of agreement for contact time, flight time, and step length, whereas the heel shoe placement was slightly more accurate for the step frequency.

Newly Developed Two-Tip Optical-Fiber Probe for Accurate Measurement of High-Speed Micro-Droplets: Simultaneous Measurement of Their Velocities and Diameters

2009 ◽  
Author(s):  
Keisuke Matsuda ◽  
Yusuke Ozawa ◽  
Takayuki Saito
Keyword(s):  
Optical Fiber ◽  
High Velocity ◽  
High Speed ◽  
Video Camera ◽  
Medium Size ◽  
Fiber Probe ◽  
Optical Fiber Probe ◽  
High Speed Video ◽  
Ultra High Speed ◽  
High Speed Video Camera

Optical fiber probing is very useful and reliable for bubbles/droplets measurement particularly in the gas-liquid two-phase flows that have dense dispersed phase and are impossible to be measured via usual visualization techniques. For the practical purpose of small- or medium-size bubbles/droplets measurement, one of the authors successfully developed a Four-Tip Optical-fiber Probe (F-TOP) and reported their excellent performance in industrial uses. Recently, particular demands for measuring properties of micro bubbles/droplets have increased in researches on multi-phase flows. However, no one succeeded in simultaneously measuring diameters and velocities of high-speed micro-droplets (velocity &gt; 50 m/s; 50 μm &lt; diameter &lt; 500 μm). We made a challenge of measuring such tiny droplets via newly developed optical fiber probe equipped with two tips (Two-Tip Optical-fiber Probe: T-TOP). We have succeeded in this difficult measurement with it. Each optical fiber probe composing the T-TOP is made of a silica optical fiber (125 μm in external diameter, 50 μm in core diameter, 37.5 μm in clad thickness). The optical fiber was fine-drawn using a micro pipette puller, and this yielded a sub-μm-scale tip. The interval of the fiber axes and the gap of the tips were arranged depending on the droplets diameter range. In this paper, we demonstrate the performance of the T-TOP. First, we confirm its practicality in industrial use. The strength of the T-TOP is confirmed by exposure test of high-velocity and high-temperature steam flows. Second, we consider the influence of the flow on the measurement of T-TOP; the optical noise due to probe vibration by the high-velocity gas flow around the T-TOP is considered. Next, we confirm its performance using an orifice-type nozzle (300 μm &lt; droplets diameter &lt; 500 μm; droplets velocities &lt; 40 m/s). We confirm the performance of the T-TOP; the results of T-TOP are compared with those of the visualization of the droplets by using an ultra-high-speed video camera. At the same time, we consider the process of droplet contact with the T-TOP via visualization of ultra-high-speed video camera.

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