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DOI: 10.3791/60857-v
Bram J.C. Bastiaansen*1, Erik Wilmes*2, Michel S. Brink1, Cornelis J. de Ruiter2, Geert J.P. Savelsbergh2, Annemarijn Steijlen3, Kaspar M.B. Jansen3, Frans C.T. van der Helm4, Edwin A. Goedhart5, Doris van der Laan6, Riemer J.K. Vegter1, Koen A.P.M. Lemmink1
1Center for Human Movement Sciences, University Medical Center,University of Groningen, 2Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences,Vrije Universiteit Amsterdam, 3Emerging Materials, Department of Design Engineering,Delft University of Technology, 4Department of Biomechanical Engineering,Delft University of Technology, 5FIFA Medical Center,Royal Netherlands Football Association, 6Royal Dutch Hockey Association
This study focuses on monitoring athletes' lower extremities to enhance performance and reduce injury risks in team sports. By utilizing inertial measurement units (IMUs), the research aims to provide detailed insights into athletes' kinematics during training and competition.
Monitoring athletes is essential for improving performance and reducing injury risk in team sports. Current methods to monitor athletes do not include the lower extremities. Attaching multiple inertial measurement units to the lower extremities could improve monitoring athletes in the field.
A correct balance between training and recovery leads to adaptations of the human body. Monitoring this training process is essential to optimize performance and reduce injury risk. The main advantage of the sensor setup is that it focuses on the lower extremities of athletes and thereby provides additional information to current monitoring systems in the field.
Team sports, like soccer and hockey, are characterized by fast changes of directions, accelerations, and decelerations. This requires a specific sensor setup. Muscle injuries are a serious problem in team sports and we think with this method, we can reduce these type of injuries and at the same time enhance performance.
Demonstrators of the procedure will be Bram Bastiaansen and Erik Wilmes, PhD students on our team. Obtain written informed consent from subjects that meet the inclusion criteria. Have the subject fill out a questionnaire about their background in team sports.
Obtain information about the subject's gender, age, body weight, and height. After the subject has changed into sports clothing, align all IMUs next to each other and push a button on top of the sensor to activate the IMUs. The sensor is activated when the green light blinks.
Then, tap all of the IMUs together on a hard surface to ensure that a mechanical peak has been generated. Before attaching the IMUs, shave the subject's body hair at the sacrum between both posterior superior iliac spines, at the anteromedial part of both the right and left tibia, and at the lateral part of both right and left thighs. When all of the regions have been shaved, apply adhesive spray to the exposed skin in a sweeping motion, holding the applicator at least 10 centimeters away from the skin.
After waiting five to 10 seconds for the spray to dry, remove the protective layer from the double-sided adhesive tape on the IMUs and place each IMU at one of the shaved locations. Sensor placement is a critical step for accurate estimation of lower extremity kinematics in the field. Write down the IMU labels and anatomical locations for later reference and attach stretching tape over each measurement unit to make sure the sensors are secured to the skin.
To calibrate the IMU sensors, instruct the subject to stand still in a neutral position with their feet hip-width apart and their hands at their sides for five seconds. Next, instruct the subject to perform a calibration procedure consisting of left hip flexion followed by right hip flexion and a bowing movement. After waiting at least five seconds, have the subject repeat the calibration procedure.
Instruct the subject to perform a warmup procedure before starting the 30-meter linear sprint test. To start the test, instruct the subject to stand on the field with their preferred foot on the starting line and their shoulders behind the starting line. Inform the subject that the test leader will count down from three to zero and shout, start.
Instruct the subject to sprint as fast as possible until the 30-meter end point has been reached, at which point the subject should decelerate as quickly as possible to a standstill position. Allow the subject to ask questions and to perform a practice run when desired. After confirming that the subject is ready, make sure the subject is in the correct starting position before having the test leader initiate the test.
Start the timer when the start sign has been given and the subject has started the sprint test. Verbally encourage the subject to achieve maximal performance during the sprint and stop the timer when the subject has covered a 30-meter distance. Include a two-minute rest period between each trial and have the subject repeat the test two more times.
After the third trial, instruct the subject to perform a cooling down procedure before detaching the IMUs from the subject. To process data, open MATLAB and import the raw IMU data files. To align the sensor coordinate frame to the body segment, select the index numbers of the data file from when the subject was standing still during the calibration.
Then select the index numbers of the data of the trunk movement during the calibration and the index numbers of the data of the calibration movements of the right and left legs. In this example, kinematic variables obtained by the IMUs are used in a segmental model to detect alterations. The kinematic data of the subject can be changed to the variables of interest.
This figure illustrates an example of kinematic data of the lower extremity during the linear sprint test. Note that the kinematic data for the subject changed when the subject was decelerating. Remember that sensor placement and sensor calibration are crucial steps for estimating lower extremity kinematics in the field.
Combining our methods, we've commonly used monitoring systems, such as global positioning systems, enables for scientists and practitioners to better understand the training load to which athletes are exposed. In the future, our method can be integrated into smart garments. This may help professionals to evaluate and optimize training and rehabilitation programs.
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