ethics approval. Instrumentation This study used six 100-Hz inertial sensors (Nanotrak; Catapult Sports, Docklands, Australia) to track trunk, pelvis, and lower limb kinematics. Inertial sensors are a validated tool for kinematic analyses ( Cuesta-Vargas, Galán-Mercant, & Williams, 2010 ; Steins, Dawes
Anna C. Severin, Brendan J. Burkett, Mark R. McKean, Aaron N. Wiegand and Mark G.L. Sayers
Benita Olivier, Samantha-Lynn Quinn, Natalie Benjamin, Andrew Craig Green, Jessica Chiu and Weijie Wang
and excursion were captured by the Xsens inertial sensor motion analysis system (MVN Link Biomech system; Xsens Technologies B.V., Enschede, The Netherlands), which consists of 17 motion trackers measuring movement at a rate of 240 Hz. The sensors were attached to the participant at the standardized
Rienk M.A. van der Slikke, Annemarie M.H. de Witte, Monique A.M. Berger, Daan J.J. Bregman and Dirk Jan H.E.J. Veeger
accurate and objective measures. To quote a wheelchair basketball coach: “you can’t improve it, if you lack information.” In preceding research, a method using inertial sensors proved reliable and accurate 4 in measuring WMP and discriminated well between athletes of different classification and
Nicola Marotta, Andrea Demeco, Gerardo de Scorpio, Angelo Indino, Teresa Iona and Antonio Ammendolia
subject’s dominant leg. We followed the recommendation of The European project Surface EMG for noninvasive assessment of muscles for electrode placement. An inertial sensor (IS; G sensor; BTS Bioengineering Corp) recorded the timing of the drop fall from the platform to ground contact. The combined data
Paul G. Montgomery and Brendan D. Maloney
global positioning system (GPS), inertial sensor, and physiological data to determine the response to each game. As the number of tournament game increases from pool games to quarterfinal (QF), semifinal (SF), and championship (CH) games, the hypothesis was that these parameters would decrease over a
Jonathan S. Akins, Nicholas R. Heebner, Mita Lovalekar and Timothy C. Sell
Ankle ligament sprains are the most common injury in soccer. The high rate of these injuries demonstrates a need for novel data collection methodologies. Therefore, soccer shoes and shin guards were instrumented with inertial sensors to measure ankle joint kinematics in the field. The purpose of this study was to assess test-retest reliability and concurrent criterion validity of a kinematic assessment using the instrumented soccer equipment. Twelve soccer athletes performed athletic maneuvers in the laboratory and field during 2 sessions. In the laboratory, ankle joint kinematics were simultaneously measured with the instrumented equipment and a conventional motion analysis system. Reliability was assessed using ICC and validity was assessed using correlation coefficients and RMSE. While our design criteria of good test-retest reliability was not supported (ICC > .80), sagittal plane ICCs were mostly fair to good and similar to motion analysis results; and sagittal plane data were valid (r = .90−.98; RMSE < 5°). Frontal and transverse plane data were not valid (r < .562; RMSE > 3°). Our results indicate that the instrumented soccer equipment can be used to measure sagittal plane ankle joint kinematics. Biomechanical studies support the utility of sagittal plane measures for lower extremity injury prevention.
Oren Tirosh, Guy Orland, Alon Eliakim, Dan Nemet and Nili Steinberg
This study aimed to identify differences in ground impact shock attenuation between overweight and healthy-weight children during running. Twenty overweight children aged 8.4 (1.1) years and 12 healthy-weight children aged 10.7 (1.3) years ran on a treadmill (120% of baseline speed) while wearing 2 inertial sensors located on their distal tibia and lower back (L3). Peak acceleration attenuation coefficient at foot contact and transfer function of the acceleration were calculated. Peak positive acceleration values were not significantly different between the overweight children and healthy-weight children (3.98 [1.17] g and 3.71 [0.84] g, respectively, P = .49). Children with healthy weight demonstrated significant greater attenuation as evident by greater peak acceleration attenuation coefficient (35.4 [19.3] and 11.9 [27.3], respectively, P < .05) and lower transfer function of the acceleration values (−3.8 [1.9] and −1.2 [1.5], respectively, P < .05). Despite the nonsignificant differences between groups in tibia acceleration at foot–ground impact that was found in the current study, the shock absorption of overweight children was reduced compared with their healthy-weight counterparts.
Robert J. Aughey
Global positioning system (GPS) technology was made possible after the invention of the atomic clock. The first suggestion that GPS could be used to assess the physical activity of humans followed some 40 y later. There was a rapid uptake of GPS technology, with the literature concentrating on validation studies and the measurement of steady-state movement. The first attempts were made to validate GPS for field sport applications in 2006. While GPS has been validated for applications for team sports, some doubts continue to exist on the appropriateness of GPS for measuring short high-velocity movements. Thus, GPS has been applied extensively in Australian football, cricket, hockey, rugby union and league, and soccer. There is extensive information on the activity profile of athletes from field sports in the literature stemming from GPS, and this includes total distance covered by players and distance in velocity bands. Global positioning systems have also been applied to detect fatigue in matches, identify periods of most intense play, different activity profiles by position, competition level, and sport. More recent research has integrated GPS data with the physical capacity or fitness test score of athletes, game-specific tasks, or tactical or strategic information. The future of GPS analysis will involve further miniaturization of devices, longer battery life, and integration of other inertial sensor data to more effectively quantify the effort of athletes.
David R. Howell, Jessie R. Oldham, Melissa DiFabio, Srikant Vallabhajosula, Eric E. Hall, Caroline J. Ketcham, William P. Meehan III and Thomas A. Buckley
Gait impairments have been documented following sport-related concussion. Whether preexisting gait pattern differences exist among athletes who participate in different sport classifications, however, remains unclear. Dual-task gait examinations probe the simultaneous performance of everyday tasks (ie, walking and thinking), and can quantify gait performance using inertial sensors. The purpose of this study was to compare the single-task and dual-task gait performance of collision/contact and noncontact athletes. A group of collegiate athletes (n = 265) were tested before their season at 3 institutions (mean age= 19.1 ± 1.1 years). All participants stood still (single-task standing) and walked while simultaneously completing a cognitive test (dual-task gait), and completed walking trials without the cognitive test (single-task gait). Spatial-temporal gait parameters were compared between collision/contact and noncontact athletes using MANCOVAs; cognitive task performance was compared using ANCOVAs. No significant single-task or dual-task gait differences were found between collision/contact and noncontact athletes. Noncontact athletes demonstrated higher cognitive task accuracy during single-task standing (P = .001) and dual-task gait conditions (P = .02) than collision/contact athletes. These data demonstrate the utility of a dual-task gait assessment outside of a laboratory and suggest that preinjury cognitive task performance during dual-tasks may differ between athletes of different sport classifications.
Matthias W. Hoppe, Christian Baumgart and Jürgen Freiwald
To investigate differences in running activities between adolescent and adult tennis players during match play. Differences between winning and losing players within each age group were also examined.
Forty well-trained male players (20 adolescents, 13 ± 1 y; 20 adults, 25 ± 4 y) played a simulated singles match against an opponent of similar age and ability. Running activities were assessed using portable devices that sampled global positioning system (10 Hz) and inertial-sensor (accelerometer, gyroscope, and magnetometer; 100 Hz) data. Recorded data were examined in terms of velocity, acceleration, deceleration, metabolic power, PlayerLoad, and number of accelerations toward the net and the forehand and backhand corners.
Adult players spent more time at high velocity (≥4 m/s2), acceleration (≥4 m/s2), deceleration (≤–4 m/s2), and metabolic power (≥20 W/kg) (P ≤ .009, ES = 0.9–1.5) and performed more accelerations (≥2 m/s2) toward the backhand corner (P < .001, ES = 2.6–2.7). No differences between adolescent winning and losing players were evident overall (P ≥ .198, ES = 0.0–0.6). Adult winning players performed more accelerations (2 to <4 m/s2) toward the forehand corner (P = .026, ES = 1.2), whereas adult losing players completed more accelerations (≥2 m/s2) toward the backhand corner (P ≤ .042, ES = 0.9).
This study shows that differences in running activities between adolescent and adult tennis players exist in high-intensity measures during simulated match play. Furthermore, differences between adolescent and adult players, and also between adult winning and losing players, are present in terms of movement directions. Our findings may be helpful for coaches to design different training drills for both age groups of players.