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Location Independent Vital Sign Monitoring and Gesture Recognition Using Wi-Fi

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Contactless Human Activity Analysis

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 200))

Abstract

Recent years have witnessed the rapid progress of Wi-Fi based contactless sensing. Compared to traditional wearable based approaches, Wi-Fi sensing does not require the target to wear any sensors and is able to capture rich context information of human target in a non-intrusive manner. Though promising, one major issue hindering the adoption of Wi-Fi sensing is the location and orientation dependence of the performance, i.e., if the human target changes the location or orientation, the sensing performance may degrade significantly. This chapter delves into this issue, analyzes the factors affecting the sensing performance and presents solutions to addressing this issue, moving Wi-Fi sensing one step closer towards real-life deployment.

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Notes

  1. 1.

    Throughout this chapter, “static path vector”, “static signal vector” and “static vector” are used interchangeably.

  2. 2.

    Throughout this chapter, “dynamic path vector”, “dynamic signal vector” and “dynamic vector” are used interchangeably.

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Correspondence to Daqing Zhang .

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Zhang, D., Niu, K., Xiong, J., Zhang, F., Li, S. (2021). Location Independent Vital Sign Monitoring and Gesture Recognition Using Wi-Fi. In: Ahad, M.A.R., Mahbub, U., Rahman, T. (eds) Contactless Human Activity Analysis. Intelligent Systems Reference Library, vol 200. Springer, Cham. https://doi.org/10.1007/978-3-030-68590-4_7

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