Rancang Bangun Alat Pengukur Jarak Tempuh Lari Laun Menggunakan Sensor Inertial Measurement Unit (IMU) Berbasis Mikrokontroler

Jogging is a form of trotting or running at a slow or leisurely pace. So far, the measurement of running distance is determined by wearables Global Positioning System (GPS) and pedometers. The use of wearables with GPS commonly used by joggers cannot be used in indoor conditions. In addition, the use of a pedometer for measuring the number of steps cannot calculate the specific distance due to the inconsistency of human footsteps. This study aims to design a device to measure the distance traveled in jogging. To measure the distance traveled in a run, an Inertial Measurement Unit (IMU) sensor can be used with a linear acceleration output then reduce the measurement noise by using a Kalman Filter. The acceleration signal is processed into a velocity signal and the velocity signal is processed into a distance signal through integration. From the results of the prototype design, it is able to measure a distance of 25m with an error of 0.78%, a distance of 50m with 0.53% and a distance of 75m with 0.22%. 

Spatial Awareness is Related to Moderate Intensity Running during a Collegiate Rugby Match

International Journal of Exercise Science 9(5): 599-606, 2016. The purpose of the present study was to evaluate the relationship between spatial awareness, agility, and distance covered in global positioning system (GPS) derived velocity zone classifications during a collegiate rugby match. Twelve American collegiate rugby union players (mean±SD; age: 21.2±1.4 y; weight: 85.0±16.0 kg; 7 forwards & 5 backs) on a single team volunteered to participate in this investigation. The distances travelled at low (walking/jogging; \u3c2.7m/s), moderate (cruising/striding; 2.7-5.0 m/s), and high intensities (running/sprinting; \u3e5.0 m/s) were measured for each player using GPS sensors and normalized according to playing time during an official USA Rugby match. Spatial awareness was measured as visual tracking speed from one core session of a 3-dimensional multiple-object-tracking speed (3DMOTS) test (1.35±0.59 cm·sec-1). Agility was assessed utilizing the pro agility (5.05±0.28 sec) and t drill (10.62±0.39 sec). Analysis of variance revealed that athletes travelled the greatest distance during walking/jogging (39.5±4.5 m·min-1) and least distance during running/sprinting (4.9±3.5 m·min-1). Pearson product moment correlations revealed that only distance covered while cruising/striding (20.9±6.5 m·min-1) was correlated to spatial awareness (r=0.798, p=0.002). Agility did not correlate to distance covered at any velocity zone or spatial awareness. Spatial awareness, as determined by 3DMOTS, appears to be related to the moderate intensity movement patterns of rugby union athletes

Recovery self-efficacy and intention as predictors of running or jogging behavior: a cross-lagged panel analysis over a two-year period

Objectives: The study investigates whether two kinds of self-efficacy and intention predict regular running or jogging behavior over 2 yr. Maintenance self-efficacy refers to beliefs about one's ability to maintain a behavior, whereas recovery self-efficacy pertains to beliefs about one's ability to resume a behavior after a setback. Design and methods: Longitudinal data from runners (N=139, 80% men) were collected twice with a time gap of 2 yr. Results: Cross-lagged panel analysis revealed that recovery self-efficacy and intention jointly predicted running/jogging behavior 2 yr later, whereas running/jogging behavior did not predict recovery self-efficacy and intention. No effects of maintenance self-efficacy were found. The majority of participants (n=120) experienced at least one 2-week period of decline in running or jogging behavior. Among those who experienced lapses, recovery self-efficacy remained the only significant social-cognitive predictor of behavior. Conclusions: Recovery self-efficacy is a crucial predictor of regular running or jogging behavior over 2 yr

The Relation Between Selected Student Characteristics and Activity Patterns in a Required High School Physical Education Class.

This study described the activity patterns of students in a high school fitness class and explored the structural relations between particular student characteristics and their coded exercise behavior. Exercise behavior was systematically coded during an 8-week jogging unit in 10 high school physical education classes. Additional measures of distance covered, heart rate, perceived exertion, percent of days participated, and fitness level were also collected. Although percent of time spent jogging was low (18%), with no significant gains made in cardiovascular fitness, the amount of time spent jogging, the distance covered, and fitness level were all significantly correlated (r $\u3e$.48, p $\u3c$.05). A LISREL VI computer program was used to test four structural equation models representing extensions of the Fishbein Behavioral-Intention Model. Two models (1 & 3) included both direct and indirect pathways from attitude, subjective norm, and background to exercise behavior while Models 2 & 4 contained only indirect paths, mediated by intention. Model 4, in support of the Fishbein and Ajzen theory, showed the prediction of exercise behavior by attitude and subjective norm to be significantly mediated by intention. Although only approaching significance, subjective norm was found to be the stronger predictor of intention over attitude. Background variables were found to indirectly influence intention through their significant influence on attitude and subjective norm. Although not significant, but in agreement with other research findings, Model 3 indicates the direct structural relation between attitude and exercise behavior to be slightly stronger than the direct structural relation with intention. For this sample of 9th and 10th graders, significant others, particularly peers and teachers, had a stronger impact on behavior than personal attitudes about activity

ANALYSIS OF EXTERNAL LOAD DURING SSG 5VS5 WITH AND WITHOUT EXTERNAL WILDCARD (JOLLY) SOCCER PLAYERS

5vs5 with external jolly shows higher and very significant (p<0.0005) values in the parameter of maximum speed, maximum power, sprint distance; however, 5vs5 without external jolly shows higher and very significant (p <0.0005) values in walking/jogging distance covered, average power in recovery time between power session, the time spent and the distance covered at low intensity power (< 20.00 W/kg). In conclusion, the 5vs5 format with the use of goalkeepers is recommended for those who have been used for at least 60 minutes during the match; however, the 5vs5 format with goalkeepers and external jolly is recommended for those who did not take part in the game or did not play 60 minutes

Evaluation of Pose Tracking Accuracy in the First and Second Generations of Microsoft Kinect

Microsoft Kinect camera and its skeletal tracking capabilities have been embraced by many researchers and commercial developers in various applications of real-time human movement analysis. In this paper, we evaluate the accuracy of the human kinematic motion data in the first and second generation of the Kinect system, and compare the results with an optical motion capture system. We collected motion data in 12 exercises for 10 different subjects and from three different viewpoints. We report on the accuracy of the joint localization and bone length estimation of Kinect skeletons in comparison to the motion capture. We also analyze the distribution of the joint localization offsets by fitting a mixture of Gaussian and uniform distribution models to determine the outliers in the Kinect motion data. Our analysis shows that overall Kinect 2 has more robust and more accurate tracking of human pose as compared to Kinect 1.Comment: 10 pages, IEEE International Conference on Healthcare Informatics 2015 (ICHI 2015

Alterations in Team Physical Performance and Possession in Elite Gaelic Football Competition

Differences in performance between winning and losing were examined in 1 elite Gaelic football team in 20 games across 2 complete competitive seasons. Possession was codified using Dartfish TeamPro software and distance covered; walking, jogging, running, and running at high and maximum speeds, was evaluated using Catapult Optimeye S5 player tracking devices. Distance covered in low intensity activity (LIA, ˂4.0 m.s-1 ), high intensity running (HIR, ≥4.0 m·s-1 ) and very high intensity running (VHIR, ≥5.5 m·s-1 ) was also examined along with PlayerLoad™, which represented a composite of all accelerations. Data from 53 players (n=405 files) was collated into specific match periods to facilitate a temporal analysis between the first and second halves and from quarter 1 (Q1) to quarter 4 (Q4), with significance accepted at p ≤ 0.05. Total distance and running was higher in games lost, whereas total distance, walking and LIA was higher in halves lost. Only walking was higher in quarters lost. The percentage of possession declined in halves and quarters lost. In games lost, high speed running declined in the second half. From Q1 to Q4; PlayerLoad™, total distance, jogging, high speed running, HIR and VHIR, decreased in all games combined and in games lost. Possession frequency declined in Q4 in all games and in games won. Overall, total distance was higher in games lost and physical performance declines were more pronounced when examined by match quarter compared to half and were only apparent in games lost. Similarly, reductions in possession frequency and percentage were more evident when examined by quarter or period lost, respectively. These findings can inform the prescription of conditioning and field-training strategies to mitigate the reductions in performance observed in losing and towards the end of games

The effect of an early dismissal on player work-rate in a professional soccer match

The aim of this study was to examine the effects of an early dismissal (after 5-minutes play) on work-rate in a professional soccer match. A computerised player tracking system was used to assess the work-rates of seven players who completed the match on the team with 10 players. A minute-by-minute analysis of the remaining 91mins following the dismissal was performed for the total distance covered, the distance covered in five categories of movement intensity and the recovery time between high-intensity efforts for each player. The data were calculated for each half and for three equal intervals within each half and profiled against normative data for the same players obtained from analyses of 15 games in the same season. Following the dismissal, the players covered a greater total distance than normal (p<0.025), particularly in moderate-intensity activities (p<0.01) and had shorter recovery times between high-intensity efforts (p<0.025). In contrast, there was a significant reduction between game halves for total distance covered at both the highest (p<0.025) and lowest running intensities (p<0.01). However, there were no differences in high-intensity activities across the three intervals in the second-half. These findings suggest that in 11 v 11, players may not always utilise their full physical potential as this match illustrated an increase in overall work-rate when reduced to 10 players. However, as a team with 10 players is likely to incur higher levels of fatigue, tactical alterations may be necessary and/or players may adopt a pacing strategy to endure the remainder of the match

ANALYSIS OF MATCH ACTIVITIES IN HIGH SCHOOL SOCCER PLAYERS USING A MOBILE GPS AND VTR METHODS

The purposes of this study were to obtain the match activity of high school soccer player, and to examine the measured value between GPS and VTR methods during a match play. The players' match activity ratios of total distance covered were walking 37.8%, jogging 16.6%, running 32.2%, sprinting 6.8%, back-walking 3.9% and back-running 3.1%, respectively. The total distance covered by GPS method was 5140.7 ± 476.6 m, and by VTR method was 5105.6 ± 459.8 m. As for the total distance covered, no significant difference was found between GPS and VTR methods. These finding,s gave suggestion that the distance covered by soccer player could be used with mobile GPS receiver. In the near future, more new accurate data will be got with GPS technique of new receiver in high quality