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.
Hannah W. Tucker, Emily R. Tobin, and Matthew F. Moran
, specifically single-leg maximal hop and hold (SLH), have commonly been included. 2 – 4 Body-worn inertial measurement units (IMUs) have been utilized to establish a strong correlation between tibial acceleration and peak landing forces during a vertical jump 5 ; however, only one study has reported on their
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.
Jonathan S. Dufour, Alexander M. Aurand, Eric B. Weston, Christopher N. Haritos, Reid A. Souchereau, and William S. Marras
– 12 Broadly, technologies that have emerged to capture and assess human motion include (1) markered optical motion capture, (2) markerless optical motion capture, and (3) inertial measurement unit (IMU) sensors. Each technology has significant advantages and disadvantages. Often considered the “gold
Suzanna Russell, Marni J. Simpson, Angus G. Evans, Tristan J. Coulter, and Vincent G. Kelly
Purpose: To investigate and explore the relationships between physiological and perceptual recovery and stress responses to elite netball tournament workloads. Methods: Nine elite female netballers were observed across a 3-day (T1–3), 4-match tournament. Participants provided salivary samples for cortisol and alpha-amylase analysis, completed the Short Recovery Stress Scale (SRSS), and reported session ratings of perceived exertion. Inertial measurement units and heart-rate monitors determined player load, changes of direction (COD), summated heart-rate zones, and jumps. Results: Analysis revealed 6 significant SRSS time effects: (1) decreased recovery markers of physical performance (P = .042), emotional balance (P = .034), and overall recovery (P = .001) and (2) increased perceptual stress markers of muscular stress (P = .001), negative emotional state (P = .026), and overall stress (P = .010). Salivary cortisol decreased over the tournament (T1–3) before progressively increasing posttournament with greater salivary samples for cortisol on T+2 compared with T3 (P = .014, ES = −1.29; −2.24 to −0.22]) and T+1 (P = .031, ES = −1.54; −2.51 to −0.42). SRSS overall recovery moderately negatively correlated with COD (r = −.41, P = .028) and session ratings of perceived exertion (r = −.40, P = .034). Cumulative workload did not relate to posttournament perceptual or salivary responses. Percentage change in salivary variables related (P < .05) to total player load, total COD, and overall recovery across specific cumulative time periods. Conclusions: During and after an elite netball tournament, athletes indicated increased perceptual stress and lack of recovery. The SRSS is a valuable tool for recovery–stress monitoring in elite tournament netball. It is recommended that practitioners monitor COD due to its negative influence on perceived overall recovery.
Jordan L. Fox, Cody J. O’Grady, and Aaron T. Scanlan
Purpose: To investigate the relationships between external and internal workloads using a comprehensive selection of variables during basketball training and games. Methods: Eight semiprofessional, male basketball players were monitored during training and games for an entire season. External workload was determined as PlayerLoad™: total and high-intensity accelerations, decelerations, changes of direction, and jumps and total low-intensity, medium-intensity, high-intensity, and overall inertial movement analysis events. Internal workload was determined using the summated-heart-rate zones and session rating of perceived exertion models. The relationships between external and internal workload variables were separately calculated for training and games using repeated-measures correlations with 95% confidence intervals. Results: PlayerLoad was more strongly related to summated-heart-rate zones (r = .88 ± .03, very large [training]; r = .69 ± .09, large [games]) and session rating of perceived exertion (r = .74 ± .06, very large [training]; r = .53 ± .12, large [games]) than other external workload variables (P < .05). Correlations between total and high-intensity accelerations, decelerations, changes of direction, and jumps and total low-intensity, medium-intensity, high-intensity, and overall inertial movement analysis events and internal workloads were stronger during training (r = .44–.88) than during games (r = .15–.69). Conclusions: PlayerLoad and summated-heart-rate zones possess the strongest dose–response relationship among a comprehensive selection of external and internal workload variables in basketball, particularly during training sessions compared with games. Basketball practitioners may therefore be able to best anticipate player responses when prescribing training drills using these variables for optimal workload management across the season.
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.