Studying Accuracy of Machine Learning Models Trained on Lab Lifting Data in Solving Real-World Problems Using Wearable Sensors for Workplace Safety

Joseph Bertrand, Nick Griffey, Ming-Lun Lu, Rashmi Jha
9/11/2023
cs.LGcs.AI

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Abstract

Porting ML models trained on lab data to real-world situations has long been a challenge. This paper discusses porting a lab-trained lifting identification model to the real-world. With performance much lower than on training data, we explored causes of the failure and proposed four potential solutions to increase model performance

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Cite this paper

@article{bertrand2023studying,
  title  = {Studying Accuracy of Machine Learning Models Trained on Lab Lifting Data in Solving Real-World Problems Using Wearable Sensors for Workplace Safety},
  author = {Joseph Bertrand and Nick Griffey and Ming-Lun Lu and Rashmi Jha},
  year   = {2023},
  eprint = {2309.05831},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.05831v1}
}

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