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Activity Recognition Based on Micro-Doppler Signature with In-Home Wi-Fi

Chen, Q; Tan, B; Chetty, K; Woodbridge, K; (2016) Activity Recognition Based on Micro-Doppler Signature with In-Home Wi-Fi. In: Proceedings of the 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom). (pp. pp. 216-221). IEEE: Munich, Germany. Green open access

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Abstract

Device free activity recognition and monitoring has become a promising research area with increasing public interest in pattern of life monitoring and chronic health conditions. This paper proposes a novel framework for inhome Wi-Fi signal-based activity recognition in e-healthcare applications using passive micro-Doppler (m-D) signature classification. The framework includes signal modeling, Doppler extraction and m-D classification. A data collection campaign was designed to verify the framework where six m-D signatures corresponding to typical daily activities are sucessfully detected and classified using our software defined radio (SDR) demo system. Analysis of the data focussed on potential discriminative characteristics, such as maximum Doppler frequency and time duration of activity. Finally, a sparsity induced classifier is applied for adaptting the method in healthcare application scenarios and the results are compared with those from the well-known Support Vector Machine (SVM) method.

Type: Proceedings paper
Title: Activity Recognition Based on Micro-Doppler Signature with In-Home Wi-Fi
Event: 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)
Location: Munich, GERMANY
Dates: 14 September 2016 - 16 September 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/HealthCom.2016.7749457
Publisher version: https://doi.org/10.1109/HealthCom.2016.7749457
Language: English
Additional information: Copyright © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Activity Recognition, micro-Doppler signature, Passive Wi-Fi radar, sparsity induced classification
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/1519610
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