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Generalized Radar-Based Detection of Respiratory Abnormalities in Indoor Environments

Year: 2025

Type: conference-paper

Abstract: This study investigates the use of various types of radar to recognize respiratory abnormalities in an indoor environment. Unlike prior approaches limited to fixed scenarios, our approach accommodates not only diverse measured angles and distances of the subject but also radar setups, exposing a Machine Learning method to a wide range of signal properties. Utilizing classical feature engineering and optimized hyperparameters, data from different radar types-Frequency Modulated Continuous Wave (FMCW) and Ultra-Wideband (UWB)—accurately classify respiratory behavior as normal or abnormal. This achieves a high accuracy of$\mathbf{9 8. 1 7 \%}$on a test dataset comprising diverse respiratory patterns from various radar setups and target positions.

Source: 2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)

DOI: 10.1109/imbioc63524.2025.10989684

Authors: Pouya Mehrjouseresht, Jitse Kennes, Ihsane Gryech, Dominique M. M.-P. Schreurs, Sofie Pollin

Institution: KU Leuven

Language: English

Topic: Non-Invasive Vital Sign Monitoring

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4410428902

FWCI:

Cites: 13

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Related to: 10