Evaluation of rodents' respiratory activity using a bioradar. Issue 9 (1st December 2015)

• Record Type: Journal Article
• Authors: Anishchenko, Lesya; Gennarelli, Gianluca; Tataraidze, Alexander; Gaysina, Ekatherina; Soldovieri, Francesco; Ivashov, Sergey
• Is Part Of: IET radar, sonar & navigation. Volume 9:Issue 9(2015)
• Page Start: 1296
• Page End: 1302
• Publication Date: 2015-12-01
• Subjects: Doppler radar -- radar signal processing -- pneumodynamics -- patient monitoring -- biomedical equipment -- filtering theory -- medical signal processing; rodent respiratory activity -- drug administration -- pharmacological experimentation -- breathing activity -- animal body -- bioradar devices -- contactless monitoring -- respiratory rhythm -- living rodents -- sleeping rats -- continuous wave Doppler radar -- signal processing -- data processing strategy -- motion artefact filtering procedure -- breathing pattern variability -- sleep phases -- biological information -- bioradiolocation -- frequency 13.8 GHz; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2014.0553
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : The estimation of breathing activity of laboratory animals after drug administration attracts considerable interest in the context of the pharmacological experimentation. So far, this task has been mostly accomplished by means of expensive and cumbersome procedures requiring the application of sensors on the animal body. In this study, the authors present a feasibility study on the possible usage of bioradar devices for contactless monitoring the respiratory rhythm of living rodents. Experiments are performed in laboratory conditions on sleeping rats by using a continuous wave Doppler radar operating at 13.8 GHz. The recorded signals are processed by means of a data processing strategy, based on a novel motion artefacts filtering procedure, with the final aim to characterise the breathing pattern variability during the sleep phases. The achieved results are consistent with biological information available from the literature confirming the potential application of bioradiolocation instead of standard on‐body monitoring methods.