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Performance of machine learning models in estimation of ground reaction forces during balance exergaming.

Elise Klæbo VonstadKerstin BachBeatrix VereijkenXiaomeng SuJan Harald Nilsen
Published in: Journal of neuroengineering and rehabilitation (2022)
This study demonstrates that an LSTM model can estimate 3-dimensional GRF components using 2D kinematic data extracted from standard 2D digital video cameras. The [Formula: see text] component is estimated more accurately than [Formula: see text] and [Formula: see text] components, especially when using 2D-DV data. Weight-shifting performance during exergaming can thus be extracted using kinematic data only, which can enable effective independent in-home balance exergaming.
Keyphrases
  • machine learning
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  • human milk
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  • body mass index
  • artificial intelligence
  • physical activity
  • weight loss
  • preterm infants
  • upper limb
  • low birth weight