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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.

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Live S. Luteberget, Benjamin R. Holme and Matt Spencer

gyroscopes. In addition, magnetometers are also imbedded in many IMUs. Information from IMUs is independent of GPS signals and can thus be used in indoor environments, as well as outdoors. IMU technology has been used by various team sports in training and games. 6 – 9 By using specific software algorithms

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Lydia R. Vollavanh, Kathleen M. O’Day, Elizabeth M. Koehling, James M. May, Katherine M. Breedlove, Evan L. Breedlove, Eric A. Nauman, Debbie A. Bradney, J. Eric Goff and Thomas G. Bowman

acceleration (rad/s 2 ) with a triaxial accelerometer and rotational gyroscope, respectively (Figure  1A ). 13 The sensor sampled linear accelerations at a rate of 1 kHz and rotational accelerations at 800 Hz. 27 Prior to each event, practice or game, researchers adhered the sensors to the skin at the right

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Anna C. Severin, Brendan J. Burkett, Mark R. McKean, Aaron N. Wiegand and Mark G.L. Sayers

This study examined the effect of water immersion on trunk and lower limb kinematics during squat exercises in older participants. A total of 24 active older adults (71.4 ± 5.4 years) performed squats and split squats on land and while partially submerged in water. Inertial sensors (100 Hz) were used to record trunk and lower body kinematics. Water immersion increased the squat depth (squat: p = .028, d = 0.63 and split squat: p = .005, d = 0.83) and reduced the trunk flexion range (squat: p = .006, d = 0.76 and split squat: p < .001, d = 1.35) during both exercises. In addition, water immersion increased the hip range of motion during the split squat (p = .002, d = 0.94). Waveform analyses also indicated differences in the timing of the movements. These results showed that water-based exercise generates a different exercise outcome and appears to provide an alternative option for older adults, enabling exercisers to perform these tasks in a manner not possible on land.

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Ryan M. Chambers, Tim J. Gabbett and Michael H. Cole

Commercially available microtechnology devices containing global positioning systems (GPSs) and microsensors (accelerometers, gyroscopes, and magnetometers) are commonly used to quantify the physical demands of rugby union. 1 During match play and training, players are divided into subgroups of

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Mohammadreza Pourahmadi, Hamid Hesarikia, Ali Ghanjal and Alireza Shamsoddini

, touchscreen displays, wireless internet capability, a set of powerful embedded sensors (accelerometers, magnetometers, and gyroscopes), and audio/video media storage, along with a unique ability to run various downloadable apps. 3 These technologies enable the smartphones to detect joint position and

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Paul A. Ullucci, Frank Tudini and Matthew F. Moran

Context: Assessment of upper cervical range of motion (UCROM) and mobility is commonly performed in the clinical setting for patients suffering from headache, neck pain, and vestibular dysfunction. Reliable and reproducible measurement of this motion is often difficult or too expensive to perform in the clinical setting. Smartphone applications using the device’s internal gyroscope offer an easy and inexpensive means of measuring UCROM, but their reliability has not been reported in the literature. Objective: To assess the reliability of an inclinometer application installed on 2 different devices (iPhone 6 [IP] and android [AN]) and to measure UCROM in a healthy population. Design: Two examiners assessed passive UCROM. Each examiner was assigned to a specific smartphone, and a repeated-measures design consisting of 3 trials for each examiner–phone was performed. The order of testing was randomized, and the examiners were blinded to UCROM measures. Setting: Laboratory. Participants: A total of 38 subjects (19 females and 19 males; age: 23.8 [1.2] y) without pain or injury to the neck or spine for at least 3 months. Intervention: Each examiner passively flexed the head fully, rotated the head fully in 1 direction, and then in another. Peak rotation measures were recorded from each smartphone. Three trials were performed for each phone, with a 2-minute break between examiners/phones. Main Outcome Measures: Intraclass correlation coefficient using a 2-way mixed, absolute agreement model was obtained (1) between each examiner–phone and (2) within each examiner–phone for the measurements in each rotation direction. Results: Interphone/examiner reliability comparing average peak and total UCROM for each device was excellent (.87, .81). Intraphone/examiner reliability, determined across 3 trials, was also excellent (AN right rot. = .91, AN left rot. = .96; IP right rot. = .98, IP left rot. = .95). Conclusion: UCROM can be reliably measured using a smartphone inclinometer application.

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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.

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Dean J. McNamara, Tim J. Gabbett, Peter Blanch and Luke Kelly

including Australian football and rugby league use microtechnology and global positioning system (GPS) devices to monitor external workload. 7 – 9 In addition to GPS data, a combination of accelerometers (electromechanical devices that measure acceleration forces), gyroscopes (electronic devices that

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Lindsey Tulipani, Mark G. Boocock, Karen V. Lomond, Mahmoud El-Gohary, Duncan A. Reid and Sharon M. Henry

; APDM Inc., Portland, OR) was used to measure movements of the femur and tibia bilaterally, as well as the lumbar spine and pelvis. Six miniature sensors (size = 48.5 mm × 36.5 mm × 13.5 mm, weight = 22 g) comprised of accelerometers and gyroscopes sampling at 128 Hz measured the linear acceleration and