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KIAM Preprint № 109, Moscow, 2021
Authors: Podoprosvetov A.V., Luzina M.E., Aliseychik A.P., Pavlovsky E.V., Orlov I.A.
Neural networks for prediction of human actions
Abstract:
This work is devoted to the prediction of human actions. The article proposes a machine learning algorithm for predicting human physical actions, created using a software package for collecting data, processing data and training a regression algorithm on the processed data. The results obtained are associated with the automatic determination of the beginning and type of physical action performed by a person. The work is aimed at improving control systems for industrial use of exoskeletons designed to increase human strength through an external frame. In the future, it is possible to use the research results for better interaction with assistive devices in enterprises.
Keywords:
physical activity prediction, neural networks, data processing, industrial exoskeletons, action prediction
Publication language: russian,  pages: 16
Research direction:
Theoretical and applied problems of mechanics
Russian source text:
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About authors:
  • Podoprosvetov Aleksei Valerievich,  orcid.org/0000-0002-3608-7895KIAM RAS
  • Luzina Margarita Evgenievna,  orcid.org/0000-0001-7196-8017RSUH
  • Aliseychik Anton Pavlovich,  orcid.org/0000-0002-1756-5396KIAM RAS
  • Pavlovsky Evgeny Vladimirovich,  orcid.org/0000-0002-6286-3202KIAM RAS
  • Orlov Igor Aleksandrovich,  orcid.org/0000-0002-5634-9426KIAM RAS