Project Details
Description
This project aims to develop a theoretical framework for sensing and detecting human activities based on wireless radio signals. The framework advances the state-of-the-arts by discovering the fundamental theory, and define a set of principles to guide practical system design. The framework will be validated and demonstrated its scientific merit through building several applications such as contactless human activity detecton and vital signs monitoring. This should benefit existing hospital and clinical patient services and promote home-care and self-care services at nationwide.
| Status | Finished |
|---|---|
| Effective start/end date | 1/12/20 → 31/12/21 |
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MDLdroid: a ChainSGD-reduce approach to mobile deep learning for personal mobile sensing
Zhang, Y., Gu, T. & Zhang, X., Feb 2022, In: IEEE/ACM Transactions on Networking. 30, 1, p. 134-147 14 p.Research output: Contribution to journal › Article › peer-review
11 Link opens in a new tab Citations (Scopus) -
MDLdroidLite: a release-and-inhibit control approach to resource-efficient deep neural networks on mobile devices
Zhang, Y., Gu, T. & Zhang, X., Oct 2022, In: IEEE Transactions on Mobile Computing. 21, 10, p. 3670-3686 17 p.Research output: Contribution to journal › Article › peer-review
6 Link opens in a new tab Citations (Scopus) -
WiFi-Sleep: sleep stage monitoring using commodity Wi-Fi devices
Yu, B., Wang, Y., Niu, K., Zeng, Y., Gu, T., Wang, L., Guan, C. & Zhang, D., 15 Sept 2021, In: IEEE Internet of Things Journal. 8, 18, p. 13900-13913 14 p.Research output: Contribution to journal › Article › peer-review
149 Link opens in a new tab Citations (Scopus)