Receive Signal Strength- Based Human Activity Recognition

Dib W, Ghanem K, Ababou A, Nedil M, Eskofier B (2021)

Publication Type: Conference contribution

Publication year: 2021

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 365-366

Conference Proceedings Title: 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings

Event location: Singapore, SGP

ISBN: 9781728146706

DOI: 10.1109/APS/URSI47566.2021.9704667

Abstract

A novel approach based on Received Signal Strength Indicator (RSSI) used to discriminate Human Activities for biomedical applications, is presented in this paper. The proposed method use a machine-learning algorithm with discriminative features extracted from the slow fading component of the received signal. The impact of the demeaning window size used for the extraction of the slow fading is investigated and an overall accuracy of 94% is obtained with a window size of 50ms.

Involved external institutions

Centre de Developpement des Technologies Avancées (CDTA) DZ Algeria (DZ) Université du Québec en Abitibi-Témiscamingue CA Canada (CA) University of Science and Technology Houari Boumediene DZ Algeria (DZ)

How to cite

APA:

Dib, W., Ghanem, K., Ababou, A., Nedil, M., & Eskofier, B. (2021). Receive Signal Strength- Based Human Activity Recognition. In 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings (pp. 365-366). Singapore, SGP: Institute of Electrical and Electronics Engineers Inc..

MLA:

Dib, Wassila, et al. "Receive Signal Strength- Based Human Activity Recognition." Proceedings of the 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021, Singapore, SGP Institute of Electrical and Electronics Engineers Inc., 2021. 365-366.

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