observation. 12 , 13 Objective measurement of kinematics outside the laboratory requires wearable sensors that are easy to apply, unobtrusive, and reach a level of accuracy sufficient to answer the study question. Inertial measurement units (IMUs) have grown in popularity for the measurement of joint motion
Melissa M.B. Morrow, Bethany Lowndes, Emma Fortune, Kenton R. Kaufman and M. Susan Hallbeck
David Whiteside, Olivia Cant, Molly Connolly and Machar Reid
Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not possible given players’ heavy travel schedules.
To develop an automated stroke-classification system to help quantify hitting load in tennis.
Nineteen athletes wore an inertial measurement unit (IMU) on their wrist during 66 video-recorded training sessions. Video footage was manually notated such that known shot type (serve, rally forehand, slice forehand, forehand volley, rally backhand, slice backhand, backhand volley, smash, or false positive) was associated with the corresponding IMU data for 28,582 shots. Six types of machine-learning models were then constructed to classify true shot type from the IMU signals.
Across 10-fold cross-validation, a cubic-kernel support vector machine classified binned shots (overhead, forehand, or backhand) with an accuracy of 97.4%. A second cubic-kernel support vector machine achieved 93.2% accuracy when classifying all 9 shot types.
With a view to monitoring external load, the combination of miniature inertial sensors and machine learning offers a practical and automated method of quantifying shot counts and discriminating shot types in elite tennis players.
Cheryl Cooky, Faye L. Wachs, Michael Messner and Shari L. Dworkin
Using intersectionality and hegemony theory, we critically analyze mainstream print news media’s response to Don Imus’ exchange on the 2007 NCAA women’s basketball championship game. Content and textual analysis reveals the following media frames: “invisibility and silence”; “controlling images versus women’s self-definitions”; and, “outside the frame: social issues in sport and society.” The paper situates these media frames within a broader societal context wherein 1) women’s sports are silenced, trivialized and sexualized, 2) media representations of African-American women in the U. S. have historically reproduced racism and sexism, and 3) race and class relations differentially shape dominant understandings of African-American women’s participation in sport. We conclude that news media reproduced monolithic understandings of social inequality, which lacked insight into the intersecting nature of oppression for women, both in sport and in the United States.
Emmett L. Gill Jr.
The following is a narrative and critique of the Rutgers University Women’s Basketball Team/Don Imus Morning Show (RUIMUS) controversy. Using a convenience sample of regional and national media accounts and observations this piece summarizes the confirmed events of the RUIMUS controversy. The first objective of the manuscript is to provide a synopsis of the RUIMUS controversy. The second purpose is to explore how White privilege (McIntosh, 2003), new racism (Littlefield, 2008), sexism and their intersection operated during the lifespan of the RUIMUS controversy. The analyses illustrated the presence of the core elements of White privilege, new racism, sexism and double jeopardy, along with accounts of alienation, racial ambiguity, masculine characterizations and becoming visible through a prolonged controversy. The practical implications of these findings for sport managers are presented, and include postcontroversy student-athlete counseling, social and corrective justice, and proactive communications.
Eirik H. Wik, Live S. Luteberget and Matt Spencer
Team handball matches place diverse physical demands on players, which may result in fatigue and decreased activity levels. However, previous speed-based methods of quantifying player activity may not be sensitive for capturing short-lasting team-handball-specific movements.
To examine activity profiles of a women’s team handball team and individual player profiles, using inertial measurement units.
Match data were obtained from 1 women’s national team in 9 international matches (N = 85 individual player samples), using the Catapult OptimEye S5. PlayerLoad/min was used as a measure of intensity in 5- and 10-min periods. Team profiles were presented as relative to the player’s match means, and individual profiles were presented as relative to the mean of the 5-min periods with >60% field time.
A high initial intensity was observed for team profiles and for players with ≥2 consecutive periods of play. Substantial declines in PlayerLoad/min were observed throughout matches for the team and for players with several consecutive periods of field time. These trends were found for all positional categories. Intensity increased substantially in the final 5 min of the first half for team profiles. Activity levels were substantially lower in the 5 min after a player’s most intense period and were partly restored in the subsequent 5-min period.
Possible explanations for the observed declines in activity profiles for the team and individual players include fatigue, situational factors, and pacing. However, underlying mechanisms were not accounted for, and these assumptions are therefore based on previous team-sport studies.
Håvard Myklebust, Øyvind Gløersen and Jostein Hallén
In regard to simplifying motion analysis and estimating center of mass (COM) in ski skating, this study addressed 3 main questions concerning the use of inertial measurement units (IMU): (1) How accurately can a single IMU estimate displacement of os sacrum (S1) on a person during ski skating? (2) Does incorporating gyroscope and accelerometer data increase accuracy and precision? (3) Moreover, how accurately does S1 determine COM displacement? Six world-class skiers roller-ski skated on a treadmill using 2 different subtechniques. An IMU including accelerometers alone (IMU-A) or in combination with gyroscopes (IMU-G) were mounted on the S1. A reflective marker at S1, and COM calculated from 3D full-body optical analysis, were used to provide reference values. IMU-A provided an accurate and precise estimate of vertical S1 displacement, but IMU-G was required to attain accuracy and precision of < 8 mm (root-mean-squared error and range of displacement deviation) in all directions and with both subtechniques. Further, arm and torso movements affected COM, but not the S1. Hence, S1 displacement was valid for estimating sideways COM displacement, but the systematic amplitude and timing difference between S1 and COM displacement in the anteroposterior and vertical directions inhibits exact calculation of energy fluctuations.
Elena Bergamini, Pélagie Guillon, Valentina Camomilla, Hélène Pillet, Wafa Skalli and Aurelio Cappozzo
The proper execution of the sprint start is crucial in determining the performance during a sprint race. In this respect, when moving from the crouch to the upright position, trunk kinematics is a key element. The purpose of this study was to validate the use of a trunk-mounted inertial measurement unit (IMU) in estimating the trunk inclination and angular velocity in the sagittal plane during the sprint start. In-laboratory sprint starts were performed by five sprinters. The local acceleration and angular velocity components provided by the IMU were processed using an adaptive Kalman filter. The accuracy of the IMU inclination estimate and its consistency with trunk inclination were assessed using reference stereophotogrammetric measurements. A Bland-Altman analysis, carried out using parameters (minimum, maximum, and mean values) extracted from the time histories of the estimated variables, and curve similarity analysis (correlation coefficient > 0.99, root mean square difference < 7 deg) indicated the agreement between reference and IMU estimates, opening a promising scenario for an accurate in-field use of IMUs for sprint start performance assessment.
M. Monda, A. Goldberg, P. Smitham, M. Thornton and I. McCarthy
To study mobility in older populations it can be advantageous to use portable gait analysis systems, such as inertial measurement units (IMUs), which can be used in the community. To define a normal range, 136 active subjects were recruited with an age range of 18 to 97. Four IMUs were attached to the subjects, one on each thigh and shank. Subjects were asked to walk 10 m at their own self-selected speed. The ranges of motion of thigh, shank, and knee in both swing and stance phase were calculated, in addition to stride duration. Thigh, shank, and knee range of movement in swing and stance were significantly different only in the > 80 age group. Regressions of angle against age showed a cubic relationship. Stride duration showed a weak linear relationship with age, increasing by approximately 0.1% per year.
Timo Rantalainen, Nicolas H. Hart, Sophia Nimphius and Daniel W. Wundersitz
Inertial measurement units (IMU) provide a convenient tool for gait stability assessment. However, it is unclear how various gait characteristics relate to each other and whether gait characteristics can be obtained from resultant acceleration. Therefore, step duration variability was measured in treadmill walking from 39 young ambulant volunteers (age 24.2 [± 2.5] y; height 1.79 [± 0.09] m; mass 71.6 [± 12.0] kg) using motion capture. Accelerations and gyrations were simultaneously recorded with an IMU. Harmonic ratio, maximum Lyapunov exponents, and multiscale sample entropy (MSE) were calculated. Step duration variability was positively associated with MSE with coarseness levels = 3–6 (r = –.33 to –.42, P ≤ .045). Harmonic ratio and MSE with all coarseness levels were negatively associated (r = –.45 to –.57, P ≤ .004). The MSE with coarseness level = 2 was negatively associated with short-term maximum Lyapunov exponents (r = –.32, P = .047). The agreement between resultant and vertical acceleration derived gait characteristics was excellent (ICC = 0.97–0.99). In conclusion, MSE with varying coarseness levels was associated with the other gait characteristics evaluated in the study. Resultant and vertical acceleration derived results had excellent agreement, which suggests that resultant acceleration is a viable alternative to considering the acceleration dimensions independently.
Roel De Ridder, Julien Lebleu, Tine Willems, Cedric De Blaiser, Christine Detrembleur and Philip Roosen
, data fusion of linear acceleration (accelerometer) and angular velocity (gyroscope) combined in an inertial measurement unit (IMU) permits compensation. 3 Notwithstanding the closer the IMU is positioned to the point of contact (eg, on the shank) the better gait events can be correctly detected, 4