Verifying Head Impacts Recorded by a Wearable Sensor using Video Footage in Rugby League: a Preliminary Study

Carey, Lauchlan John; Stanwell, Peter; Terry, Douglas P.; McIntosh, Andrew S.; Caswell, Shane V.; Gardner, Andrew J.

doi:10.1186/s40798-019-0182-3

Cited by 28 publications

(26 citation statements)

References 61 publications

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“…One rugby study that included six concussions used the X-Patch to determine the number of head impacts that occurred but did not report the magnitude of the head acceleration. 32 The accuracy of the X-Patch has been investigated and the linear acceleration was found to be in reasonable agreement with a reference sensor but the angular acceleration was underestimated by up to 25%. 33 Sim-G is a headband sensor developed by Triax Ltd. A validation study of this sensor found that due to the movement of the sensors relative to the skull, PLA errors could be up to 370%.…”

Section: Introductionmentioning

confidence: 93%

Concussion and the severity of head impacts in mixed martial arts

Tiernan

Meagher

O’Sullivan

et al. 2020

Proc Inst Mech Eng H

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Concern about the consequences of head impacts in US football has motivated researchers to investigate and develop instrumentation to measure the severity of these impacts. However, the severity of head impacts in unhelmeted sports is largely unknown as miniaturised sensor technology has only recently made it possible to measure these impacts in vivo. The objective of this study was to measure the linear and angular head accelerations in impacts in mixed martial arts, and correlate these with concussive injuries. Thirteen mixed martial arts fighters were fitted with the Stanford instrumented mouthguard (MiG2.0) participated in this study. The mouthguard recorded linear acceleration and angular velocity in 6 degrees of freedom. Angular acceleration was calculated by differentiation. All events were video recorded, time stamped and reported impacts confirmed. A total of 451 verified head impacts above 10g were recorded during 19 sparring events (n = 298) and 11 competitive events (n = 153). The average resultant linear acceleration was 38.0624.3g while the average resultant angular acceleration was 256761739 rad/s2. The competitive bouts resulted in five concussions being diagnosed by a medical doctor. The average resultant acceleration (of the impact with the highest angular acceleration) in these bouts was 86.7618.7g and 756163438 rad/s2. The average maximum Head Impact Power was 20.6kW in the case of concussion and 7.15kW for the uninjured athletes. In conclusion, the study recorded novel data for sub-concussive and concussive impacts. Events that resulted in a concussion had an average maximum angular acceleration that was 24.7% higher and an average maximum Head Impact Power that was 189% higher than events where there was no injury. The findings are significant in understanding the human tolerance to short-duration, high linear and angular accelerations.

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Section: Introductionmentioning

confidence: 93%

Concussion and the severity of head impacts in mixed martial arts

Tiernan

Meagher

O’Sullivan

et al. 2020

Proc Inst Mech Eng H

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“…Measurement methods fall primarily into two categories: (1) video analysis and (2) the analysis of time series data acquired by inertial sensors such as accelerometers and gyroscopes [6,11,16,19]. In the former, orthogonal xyz spatial components of well-defined fiducial markers are tracked through a time-series sequence of video frames.…”

Section: Introductionmentioning

confidence: 99%

“…In the former, orthogonal xyz spatial components of well-defined fiducial markers are tracked through a time-series sequence of video frames. This information can then be numerically processed to estimate the dynamics of the markers over the measurement period [19]. In the latter, the orthogonal xyz components of linear acceleration and rotational velocity are measured by the inertial sensors.…”

Section: Introductionmentioning

confidence: 99%

Comparison of head impact measurements via an instrumented mouthguard and an anthropometric testing device

et al. 2020

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The purpose of this study was to determine and compare the efficacy of head impact measurements via an electronic sensor framework, embedded within a mouthguard, against an anthropometric testing device. Development of the former is in response to the growing issue of head impacts and concussion in rugby union. Testing was conducted in a vehicle safety laboratory using a standard impact protocol utilising the headforms of anthropometric testing devices. The headforms were subjected to controlled front and side impacts. For each impact, the linear acceleration and rotational velocity was measured over a 104-ms interval at a frequency of 1 kHz. The magnitude of peak linear acceleration and peak rotational velocity was determined from the measured time-series traces and statistically compared. The peak linear acceleration and rotational velocity had intraclass correlation coefficients of 0.95 and 0.99, respectively. The root-mean-square error between the measurement systems was 4.3 g with a standard deviation of 3.5 g for peak linear acceleration and 0.7 rad/s with a standard deviation of 0.4 rad/s for rotational velocity. Bland and Altman analysis indicated a systematic bias of 2.5 g and − 0.5 rad/s and limits of agreement (1.96 × standard deviation) of ± 13.1 g and ± 1.25 rad/s for the instrumented mouthguard. These results provide the basis on which the instrumented mouthguard can be further developed for deployment and application within professional rugby, with a view to accurately and reliably quantify head collision dynamics.

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“…The former often come in the shape of inertial measurement units (IMUs). Since these IMUs gather data for a single point in space the placement of the IMU is critical for the measurement [ 17 , 19 , 20 , 21 , 22 ]. Depending on the application the IMU may be placed directly on the skin [ 17 ] a wristband, harness or similar [ 23 , 24 ], but also within a ball, shoe or alike is common [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Using Wearable Sensors and a Convolutional Neural Network for Catch Detection in American Football

Hollaus

Stabinger

Mehrle

et al. 2020

Sensors

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Highly efficient training is a must in professional sports. Presently, this means doing exercises in high number and quality with some sort of data logging. In American football many things are logged, but there is no wearable sensor that logs a catch or a drop. Therefore, the goal of this paper was to develop and verify a sensor that is able to do exactly that. In a first step a sensor platform was used to gather nine degrees of freedom motion and audio data of both hands in 759 attempts to catch a pass. After preprocessing, the gathered data was used to train a neural network to classify all attempts, resulting in a classification accuracy of 93%. Additionally, the significance of each sensor signal was analysed. It turned out that the network relies most on acceleration and magnetometer data, neglecting most of the audio and gyroscope data. Besides the results, the paper introduces a new type of dataset and the possibility of autonomous training in American football to the research community.

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Verifying Head Impacts Recorded by a Wearable Sensor using Video Footage in Rugby League: a Preliminary Study

Cited by 28 publications

References 61 publications

Concussion and the severity of head impacts in mixed martial arts

Concussion and the severity of head impacts in mixed martial arts

Comparison of head impact measurements via an instrumented mouthguard and an anthropometric testing device

Using Wearable Sensors and a Convolutional Neural Network for Catch Detection in American Football

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