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.

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.

Kinematics Characteristic of Exoskeleton Walking Robot for Older People

2014 ◽  
Vol 644-650 ◽  
pp. 167-170 ◽  
Author(s):  
Yong Chen ◽  
Sheng Lin ◽  
Rong Hua Li ◽  
Lian Dong Zhang
Keyword(s):  
Older People ◽  
High Speed ◽  
Video Camera ◽  
Step Length ◽  
Walking Robot ◽  
Step Frequency ◽  
High Speed Video ◽  
High Speed Video Camera ◽  
Gait Parameters ◽  
The Impact

The movement processes of the older people during walking on level ground were captured by the high-speed video camera with the speed of 500 frames per second. The gait parameters of the older people during walking on level ground were obtained by the quantitative analysis of the successive photographs captured by the high-speed video camera. Kinematics features of the older people during walking on level ground were discussed. Along with the growth of the age, step velocity, step frequency and step length were reduced, and gait cycle was rising. According to the morphology of the older people during walking on level ground, a mechanical model was put forward to aid the design of the exoskeleton walking robot. The couple walking characteristics between the older wearer and the exoskeleton walking robot was studied. In the single support phase of the exoskeleton walking robot, the change of the hip joint was gradually decreased to provide the driving force for the stable walk, the change of the knee joint was increased and following decreased and then increased to forward the older people's body center of gravity, and the change of the ankle joint was gradually increased to reduce the impact force of the ground. The results would provide the basic theory to bionic references for improving the reasonable properties of the exoskeleton walking robot. This work would provide certain theoretical and practical base in developing the exoskeleton walking robot on bionic structural design.

scholarly journals Relationship between Step Characteristics and Race Performance during 5000-m Race

Sports ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 131
Author(s):  
Hiromasa Ueno ◽  
Sho Nakazawa ◽  
Yohsuke Takeuchi ◽  
Masaaki Sugita
Keyword(s):  
Contact Time ◽  
High Speed ◽  
Body Height ◽  
Step Length ◽  
Step Frequency ◽  
Race Time ◽  
Length Step ◽  
Endurance Runners ◽  
The Relationship ◽  
Race Performance

This study examined the relationship between step characteristics and race time in a 5000-m race. Twenty-one male Japanese endurance runners performed a 5000-m race. Step length, step frequency, contact time, and flight time of two gait cycles (i.e., four consecutive ground contacts) were measured every 400-m by using high-speed video image. Moreover, step length was normalized to body height to minimize the effect of body size. In addition to step characteristics on each lap, the averages of all laps and the per cent change from the first half to the second half were calculated. The average step frequency and step length normalized to body height correlated significantly with the 5000-m race time (r = −0.611, r = −0.575, respectively, p < 0.05 for both). Per cent changes in contact time and step length correlated significantly with the 5000-m race time (r = 0.514, r = −0.486, respectively, p < 0.05 for both). These findings suggest that, in addition to higher step frequency and step length normalized to body height, smaller changes in step length during a given race may be an important step characteristic to achieving superior race performance in endurance runners.

Absolute reliability and validity of the OptoGaitTM system to measure spatiotemporal gait parameters during running

2020 ◽  
pp. 175433712097740
Author(s):  
Felipe García-Pinillos ◽  
Pedro A Latorre-Román ◽  
Jose M Chicano-Gutiérrez ◽  
Emilio J Ruiz-Malagón ◽  
Juan A Párraga-Montilla ◽  
...  
Keyword(s):  
Video Analysis ◽  
Concurrent Validity ◽  
High Speed ◽  
Reliability And Validity ◽  
T Test ◽  
Validity And Reliability ◽  
High Speed Video ◽  
Gait Characteristics ◽  
Spatiotemporal Parameters ◽  
Absolute Reliability

The biomechanics of walking and running, in both ground and treadmill conditions, have been extensively analysed and important differences have been reported. Despite some previous studies having examined the validity and reliability of the OptoGait™ system for measuring gait characteristics during walking, no previous works have determined the reliability and validity of this system while running on a treadmill. Therefore, this study aimed to determine the absolute reliability (within-subject variation) and evaluate the concurrent validity of the OptoGait™ system for measuring spatiotemporal variables while running at a comfortable speed by comparing data with a highly accurate system of measuring those parameters (i.e. video analysis at 1000 Hz). Forty-nine endurance runners performed a running protocol on a treadmill at a comfortable speed. Two systems were used to collect data: OptoGait™ system and high-speed video analysis at 1000 Hz. The coefficient of variation (CV) was calculated as a measure of absolute reliability. The OptoGait™ system reported a CV range between 2.2% and 11.4% for spatiotemporal parameters, while the video analysis showed a CV range between 0.02% and 9.9%. To determine concurrent validity, intra class correlation coefficients (ICC) and pairwise comparisons of means (t-test) were calculated between data from both systems. Although the paired t-test demonstrated significant differences between systems, a high level of agreement (ICC > 0.89) was obtained in spatiotemporal parameters between systems. When compared to a high-speed video analysis at 1000 Hz, the results indicate that the OptoGait™ system is a reliable and valid tool to measure spatiotemporal gait characteristics while running on a treadmill at a comfortable speed.

scholarly journals How do Amateur Endurance Runners Alter Spatiotemporal Parameters and Step Variability as Running Velocity Increases? A Sex Comparison

2020 ◽  
Vol 72 (1) ◽  
pp. 39-49
Author(s):  
Felipe García-Pinillos ◽  
Daniel Jerez-Mayorga ◽  
Pedro Á. Latorre-Román ◽  
Rodrigo Ramirez-Campillo ◽  
Fernando Sanz-López ◽  
...  
Keyword(s):  
Sex Differences ◽  
Standard Deviation ◽  
Step Length ◽  
Flight Time ◽  
Step Frequency ◽  
Time Step ◽  
Spatiotemporal Parameters ◽  
Length Step ◽  
Endurance Runners

AbstractThis study aimed to analyse the effects of running velocity on spatiotemporal parameters and step variability in amateur endurance runners, according to sex. A group of 51 males and 46 females performed an incremental running test on a treadmill (10-16 km/h). Spatiotemporal parameters (contact and flight time, step length, step frequency and step angle [CT, FT, SL, SF, SA]) and step variability, in terms of within-participant standard deviation (SD), were recorded through the OptoGait System. The ANOVA showed significant differences in the magnitude of the spatiotemporal parameters as running velocity increased (p < 0.001). It also revealed significant differences in step variability (p < 0.005) over the entire running protocol. Between-sex differences in CT, SL, SL-normalized and SF (p < 0.05, ES = 0.4-0.8) were found. Differences were also found in step variability at high velocities (15-16 km/h), with males showing a greater SD than females. In conclusion, increasing running velocity makes CT shorter, FT and SL longer, and SF and SA greater in amateur endurance runners, changing step variability, regardless of sex. Additionally, some between-sex differences were found in spatiotemporal parameters and step variability.

scholarly journals Audio-Based System for Automatic Measurement of Jump Height in Sports Science

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2543
Author(s):  
Basilio Pueo ◽  
Jose J. Lopez ◽  
Jose M. Jimenez-Olmedo
Keyword(s):  
High Speed ◽  
Muscle Power ◽  
Audio Signal ◽  
Automatic Measurement ◽  
Flight Time ◽  
Systematic Bias ◽  
Jump Height ◽  
Random Errors ◽  
Signal Processing Algorithm ◽  
Sports Science

Jump height tests are employed to measure the lower-limb muscle power of athletic and non-athletic populations. The most popular instruments for this purpose are jump mats and, more recently, smartphone apps, which compute jump height through manual annotation of video recordings to extract flight time. This study developed a non-invasive instrument that automatically extracts take-off and landing events from audio recordings of jump executions. An audio signal processing algorithm, specifically developed for this purpose, accurately detects and discriminates the landing and take-off events in real time and computes jump height accordingly. Its temporal resolution theoretically outperforms that of flight-time-based mats (typically 1000 Hz) and high-speed video rates from smartphones (typically 240 fps). A validation study was carried out by comparing 215 jump heights from 43 active athletes, measured simultaneously with the audio-based system and with of a validated, commercial jump mat. The audio-based system produced nearly identical jump heights than the criterion with low and proportional systematic bias and random errors. The developed audio-based system is a trustworthy instrument for accurately measuring jump height that can be readily automated as an app to facilitate its use both in laboratories and in the field.

Sign in / Sign up

Export Citation Format

Share Document