Gaeini, Ali (2023) Design and Implementation of an IMU Sensor System to Estimate a Hockey Puck’s Peak Velocity. Masters thesis, Concordia University.
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Abstract
The rapid advancement in sensor technology can revolutionize how sports dynamics are understood and analyzed. This thesis focuses on designing and implementing an Inertial Measurement Unit (IMU) sensor system to be deployed within a hockey puck to estimate its peak velocity.
The research involved the intricate design of a sensor system comprising an accelerometer, two gyroscopes, and a magnetometer. Moreover, puck preparation was carried out to secure the sensor and battery within the puck to ensure functionality and durability. Furthermore, a data acquisition system is developed to receive, save, and plot data transmitted via Bluetooth Low Energy (BLE) protocol.
Three distinct methods for estimating the puck's peak velocity from the sensor data are compared. It is discovered that the method based on an extended Kalman filter and utilizing data from all three sensor types exhibits superior accuracy. This method is subsequently validated under various hockey shot conditions, reinforcing its practical applicability. Moreover, the relationship between velocity estimation error versus true velocity is investigated.
Primarily designed for research studies, this work offers a foundational understanding of hockey puck dynamics, despite the sensor system not being tailored for real-game scenarios. The insights gained have substantial implications for further sports analytics and player training. Furthermore, the results outline a promising pathway for future sports engineering and wearable technology investigations.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Gaeini, Ali |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Electrical and Computer Engineering |
Date: | 29 August 2023 |
Thesis Supervisor(s): | Cowan, Glenn |
ID Code: | 992980 |
Deposited By: | Ali Gaeini |
Deposited On: | 15 Nov 2023 15:24 |
Last Modified: | 15 Nov 2023 15:24 |
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