Inner-Cycle Phases Can Be Estimated from a Single Inertial Sensor by Long Short-Term Memory Neural Network in Roller-Ski Skating

Inner-Cycle Phases Can Be Estimated from a Single Inertial Sensor by Long Short-Term Memory Neural Network in Roller-Ski Skating

Objective: The aim of this study was to provide a new machine learning method to determine temporal events and inner-cycle parameters (e.g., cycle, pole and ski contact and swing time) in cross-country roller-ski skating on the field, using a single inertial measurement unit (IMU). Methods: The deve...

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Bibliographic Details
Main Authors: Frédéric Meyer, Magne Lund-Hansen, Trine M. Seeberg, Jan Kocbach, Øyvind Sandbakk, Andreas Austeng
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
cross-country skiing
IMU
wearable sensors
LSTM
neural network
Online Access:https://www.mdpi.com/1424-8220/22/23/9267

Internet

https://www.mdpi.com/1424-8220/22/23/9267

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