Multimodal sensing for assisted living using radar

Book chapter (2020)

Authors

Aman Shrestha University of Glasgow
Haobo Li University of Glasgow
F. Fioranelli Microwave Sensing, Signals & Systems - EEMCS
Julien Le Kernec University of Glasgow, University of Cergy-Pontoise, University of Electronic Science and Technology of China
Research Group
Microwave Sensing, Signals & Systems (EEMCS) (TU Delft)
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Published Date

2020

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Microwave Sensing, Signals & Systems

Abstract

This chapter will explore the different sensor and fusion topologies, using active radar sensing in conjunction with other sensing technologies as support for assisted living and healthcare applications. Initially, the sensors and their outputs will be described, with specifics of signal processing of the different sensors and the machine learning for classification detailed. The results of applying these methods to the assisted living scenario will then be presented. This chapter will give insight into activity classification with radar and additional sensing technologies, in particular, wearable inertial and magnetic sensors, focusing on the key information fusion approaches and main improvements using experimental data as validation.