Accuracy Evaluation on the Respiration Rate Estimation using Off-the-shelf Pulse-Doppler Radar

Li, X., Li, S., Li, H. and Fioranelli, F. (2019) Accuracy Evaluation on the Respiration Rate Estimation using Off-the-shelf Pulse-Doppler Radar. In: IEEE MTT-S 2019 International Microwave Biomedical Conference (IMBioC2019), Nanjing, China, 6-8 May 2019, (Accepted for Publication)

Li, X., Li, S., Li, H. and Fioranelli, F. (2019) Accuracy Evaluation on the Respiration Rate Estimation using Off-the-shelf Pulse-Doppler Radar. In: IEEE MTT-S 2019 International Microwave Biomedical Conference (IMBioC2019), Nanjing, China, 6-8 May 2019, (Accepted for Publication)

[img] Text
178870.pdf - Accepted Version
Restricted to Repository staff only

481kB

Abstract

This student paper presents preliminary results of using a pulse Doppler radar to detect the respiration rate of human subjects, examining the accuracy of the approach and evaluating the parameters to obtain the most precise result. In the study, the respiration data is recorded by repeatedly detecting people seated in front of the radar at different ranges as well as different aspect angles each time. Then Movement Target Indication, short-time Fourier transform and the analysis of the choice of doppler bins and window size of STFT are performed to evaluate the respiration rate and its precision. The results indicate that the respiration rate can be successfully detected at various ranges and angles and the relationship between Doppler bins and window size in processing is also observed to help us find the most accurate respiration rate.

Item Type:Conference Proceedings
Status:Accepted for Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Fioranelli, Dr Francesco and Li, Haobo
Authors: Li, X., Li, S., Li, H., and Fioranelli, F.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Related URLs:

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3015260Intelligent RF Sensing for Fall and Health PredictionFrancesco FioranelliEngineering and Physical Sciences Research Council (EPSRC)EP/R041679/1ENG - Systems Power & Energy