Validity of a Trunk-Mounted Accelerometer to Measure Physical Collisions in Contact Sports

Wundersitz, Daniel; Gastin, Paul B.; Robertson, Sam; Netto, Kevin

doi:10.1123/ijspp.2014-0381

Cited by 25 publications

(24 citation statements)

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“…The three orthogonal acceleration signals were filtered using a 4 th -order Butterworth bandpass filter with cut-offs set at 0.1 Hz and 15.0 Hz. These frequencies were chosen to remove gravity [5,15] and noise [37,38] components, respectively. The magnitude of the instantaneous acceleration vector was calculated by taking the square root of the sum of the square of the three orthogonal accelerations [36].…”

Section: Data Analysesmentioning

confidence: 99%

Construct Validity of Accelerometry-Derived Force to Quantify Basketball Movement Patterns

et al. 2017

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This study assessed the construct validity of accelerometry-derived net force to quantify the external demands of basketball movements. Twenty-eight basketballers completed the Yo-Yo intermittent recovery test (Yo-Yo-IR1) and basketball exercise simulation test (BEST). Intensity was quantified using accelerometry-derived average net force (AvF) and PlayerLoad per minute (PL/min). Within-player correlations were determined between intensity and running speed during Yo-Yo-IR1. Measured AvF was determined for movements during the BEST and predicted AvF was calculated using movement speed and correlations from Yo-Yo-IR1. Relationships between AvF and running speed during Yo-Yo-IR1 were nearly perfect (r=0.95, 95% CI: 0.94-0.96; p<0.001) and stronger than correlations between running speed and PL/min (r=0.80, 95% CI: 0.73-0.87; p<0.001). Differences between measured and predicted AvF were small during jogging and running (<1%), but large for basketball movements including jumping, change-of-direction and shuffling (15%-41%). As hypothesised, AvF differed by playing position (11%-16%; <0.001) and reflected the additional demand upon players with larger body mass and lower movement efficiency. Both sprint speed and AvF reduced during the course of the BEST (≤0.013). These findings confirm the construct validity of AvF to quantify the external demand of basketball movements. Accelerometry-derived net force has the potential to quantify the external demands of basketballers during training and competition.

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Section: Data Analysesmentioning

confidence: 99%

Construct Validity of Accelerometry-Derived Force to Quantify Basketball Movement Patterns

et al. 2017

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“…Previous studies investigating the concurrent validity of IMUs primarily identified external rather than internal factors affecting validity, with respect to manufacturer-provided parameters [14,15,19]. Findings clearly point towards the intensity of motion as well as the performed movement task itself affecting the IMU’s concurrent validity [14,19], with higher errors being found for high-intensity movements such as sprinting, jumping, and tackling.…”

Section: Introductionmentioning

confidence: 99%

“…However, pre-processed parameters provided within the proprietary software of tracking devices typically rely on KF-based algorithms. Even though the validity of these parameters has previously been examined, current research is mostly restricted to evaluating the resultant acceleration magnitude [14,15]. More detailed analysis in the horizontal and vertical movement planes is not typically provided by manufacturers, even though this is crucial for comprehensive and meaningful analysis of athletes’ locomotor demands during sports.…”

Section: Introductionmentioning

confidence: 99%

Validation of Wearable Sensors during Team Sport-Specific Movements in Indoor Environments

Roell¹,

Mahler²,

Lienhard³

et al. 2019

Sensors

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The aim of this study was to determine possible influences, including data processing and sport-specific demands, on the validity of acceleration measures by an inertial measurement unit (IMU) in indoor environments. IMU outputs were compared to a three-dimensional (3D) motion analysis (MA) system and processed with two sensor fusion algorithms (Kalman filter, KF; Complementary filter, CF) at temporal resolutions of 100, 10, and 5 Hz. Athletes performed six team sport-specific movements whilst wearing a single IMU. Mean and peak acceleration magnitudes were analyzed. Over all trials (n = 1093), KF data overestimated MA resultant acceleration by 0.42 ± 0.31 m∙s−2 for mean and 4.18 ± 3.68 m∙s−2 for peak values, while CF processing showed errors of up to 0.57 ± 0.41 m∙s−2 and −2.31 ± 2.25 m∙s−2, respectively. Resampling to 5 Hz decreased the absolute error by about 14% for mean and 56% for peak values. Still, higher acceleration magnitudes led to a large increase in error. These results indicate that IMUs can be used for assessing accelerations in indoor team sports with acceptable means. Application of a CF and resampling to 5 Hz is recommended. High-acceleration magnitudes impair validity to a large degree and should be interpreted with caution.

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“…16 Unsurprisingly, spikes in accelerometer data can occur during a high-intensity acceleration or change of direction and may indeed be recorded by this equipment as an 'impact', 17 which can be incorrectly interpreted by practitioners as a collision or contact event with an opponent. 16 Although wearable microtechnology has demonstrated validity when measuring collision and impact forces during walking, running, and team sport movements, 17,18 research is yet to investigate the accuracy of a microtechnology device to distinguish between collision events and other spikes in accelerometer data during professional rugby league match-play.…”

mentioning

confidence: 99%

Wearable microtechnology can accurately identify collision events during professional rugby league match-play

Hulin

Gabbett²,

Johnston

et al. 2017

Journal of Science and Medicine in Sport

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Objectives: Collision frequency during rugby league matches is associated with team success, greater and longer lasting fatigue and increased injury risk. This study researched the sensitivity and specificity of microtechnology to count collision events during rugby league matches. Design: Diagnostic accuracy studyMethods: While wearing a microtechnology device (Catapult, Optimeye S5), eight professional rugby league players were subjected to a total of 380 collision events during matches. Video footage of each match was synchronised with microtechnology data. The occurrence of each collision event was coded in comparison with whether that event was or was not detected by microtechnology.Results: Microtechnology detected 371 true-positive collision events (sensitivity = 97.6 ± 1.5%). When low-intensity (<1 PlayerLoad AU), short duration (<1 second) events were excluded from the analysis, specificity was 91.7 ± 2.5%, accuracy was 92.7 ± 1.3%, positive likelihood ratio was 11.4 ×/÷ 1.4 and the typical error of estimate was 7.8% ×/÷ 1.9 (d = 0.29 ×/÷ 1.9, small). Microtechnology collisions 2 were strongly and positively correlated with video coded collision events (r = 0.96). The ability of microtechnology to detect collision events improved as the intensity and duration of the collision increased. Conclusions:Microtechnology can identify 97.6% of collision events during rugby league match-play.The typical error associated with measuring contact events can be reduced to 7.8%, with accuracy (92.7%) and specificity (91.7%) improving, when low-intensity (<1 PlayerLoad AU) and short duration (<1 second) collision reports are excluded. This provides practitioners with a measurement of contact workload during professional rugby league matches.

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Validity of a Trunk-Mounted Accelerometer to Measure Physical Collisions in Contact Sports

Abstract: The findings indicate that the MinimaxX S4 accelerometer can accurately measure physical-collision peak impact accelerations when data are filtered at a 20-Hz cutoff frequency. As a result, accelerometers may be useful to measure physical collisions in contact sports.

Cited by 25 publications

References 0 publications

Construct Validity of Accelerometry-Derived Force to Quantify Basketball Movement Patterns

Construct Validity of Accelerometry-Derived Force to Quantify Basketball Movement Patterns

Validation of Wearable Sensors during Team Sport-Specific Movements in Indoor Environments

Wearable microtechnology can accurately identify collision events during professional rugby league match-play

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