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Editorial
. 2024 Aug 14;24(16):5250.
doi: 10.3390/s24165250.

Human Activity Recognition, Monitoring, and Analysis Facilitated by Novel and Widespread Applications of Sensors

Hui Liu  1   2 , Hugo Gamboa  2 , Tanja Schultz  1
Affiliations
Editorial

Human Activity Recognition, Monitoring, and Analysis Facilitated by Novel and Widespread Applications of Sensors

Hui Liu et al. Sensors (Basel). .

Abstract

The Special Issue Sensors for Human Activity Recognition has received a total of 30 submissions so far, and from these, this new edition will publish 10 academic articles [...].

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Conflict of interest statement

The authors declare no conflict of interest.

References

    1. Liu H., Gamboa H., Schultz T., editors. Sensors for Human Activity Recognition. MDPI; Basel, Switzerland: 2023. - DOI
    1. Liu H., Gamboa H., Schultz T. Sensor-Based Human Activity and Behavior Research: Where Advanced Sensing and Recognition Technologies Meet. Sensors. 2023;23:125. doi: 10.3390/s23010125. - DOI - PMC - PubMed
    1. Liu H., Hartmann Y., Schultz T. A Practical Wearable Sensor-Based Human Activity Recognition Research Pipeline; Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies—Volume 5: HEALTHINF; Vienna, Austria. 9–11 February 2022; pp. 847–856. - DOI
    1. Kwon Y., Kang K., Bae C. Analysis and evaluation of smartphone-based human activity recognition using a neural network approach; Proceedings of the IJCNN 2015—International Joint Conference on Neural Networks; Killarney, Ireland. 12–17 July 2015; pp. 1–5. - DOI
    1. Straczkiewicz M., James P., Onnela J.P. A systematic review of smartphone-based human activity recognition methods for health research. npj Digit. Med. 2021;4:148. doi: 10.1038/s41746-021-00514-4. - DOI - PMC - PubMed

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