IMU Airtime Detection in Snowboard Halfpipe: U-Net Deep Learning Approach Outperforms Traditional Threshold Algorithms

IMU Airtime Detection in Snowboard Halfpipe: U-Net Deep Learning Approach Outperforms Traditional Threshold Algorithms

Airtime is crucial for high-rotation tricks in snowboard halfpipe performance, significantly impacting trick difficulty, the primary judging criterion. This study aims to enhance the detection of take-off and landing events using inertial measurement unit (IMU) data in conjunction with machine learn...

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Bibliographic Details
Main Authors: Tom Gorges, Padraig Davidson, Myriam Boeschen, Andreas Hotho, Christian Merz
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Sensors
Subjects:
event detection
freestyle sports
binary segmentation
airtime
convolutional neural network
elite athletes
Online Access:https://www.mdpi.com/1424-8220/24/21/6773
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