An Effective Framework for Automated Identification of Human Activity

Authors

  • Neha Bansal, Atul Bansal, Manish Gupta Author

DOI:

https://doi.org/10.48047/4x901863

Keywords:

Human activity recognition, Machine Learning, Convolutional Neural Networks, Classifiers, Bluetooth, Sound Sensors

Abstract

The integration of human-computer interaction technologies into everyday life has sparked the attention of researchers in
creating increasingly sophisticated autonomous systems. These human-computer interaction systems can achieve success in
practical applications by resolving the deficiencies in current methodologies. This study concentrates on a significant application of human-computer interaction called human activity recognition.

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References

D. K. Vishwakarma, R. Kapoor, and A. Dhiman, “A Proposed Unified Framework for the Recognition of Human Activity by Exploiting the Characteristics of Action Dynamics,” Robotics and Autonomous Systems, Vol. 77, pp. 25-38, 2016.

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Published

2025-02-03

Issue

Vol. 54 No. 3 (2025): Year 2025, Volume 54, Issue 3

Section

Articles

License

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How to Cite

An Effective Framework for Automated Identification of Human Activity (Neha Bansal, Atul Bansal, Manish Gupta , Trans.). (2025). Cuestiones De Fisioterapia, 54(3), 3562-3570. https://doi.org/10.48047/4x901863