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Isolating In-Situ Grip and Push Force Distribution from Hand-Handle Contact Pressure with an Industrial Electric Nutrunner.

Cederick LandryDaniel LoewenHarish RaoBrendan L PintoRobert BahenskyNaveen Chandrashekar
Published in: Sensors (Basel, Switzerland) (2021)
The developed algorithm can aid in better understanding the risk of injury associated with different tasks through the notion of grip and push force distribution. This was shown to be important as even workers with considerable power tool experience applied significantly more grip and push force than other participants, all of whom successfully completed each task. Moreover, the fact that both forces were uncorrelated shows the need for extracting them independently.
Keyphrases
  • single molecule
  • machine learning
  • working memory
  • heavy metals
  • risk assessment