1. IR-UWB Radar-Based Robust Heart Rate Detection Using a Deep Learning Technique Intended for Vehicular Applications
- Author
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Khan, Faheem, Azou, Stéphane, Youssef, Roua, Morel, Pascal, Radoi, Emanuel, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), École Nationale d'Ingénieurs de Brest (ENIB), Equipe Architectures, Microwaves & Photonic Systems (Lab-STICC_ASMP), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Université de Brest (UBO), Equipe Security, Intelligence and Integrity of Information (Lab-STICC_SI3), This research has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 838037. The content of this paper only reflects the authors’ views and the Research Executive Agency is not responsible for any use that may be made of the information it contains., and European Project: 838037, UWB-IODA SF-PC
- Subjects
ultra-wide band ,Computer Networks and Communications ,perceptive car ,deep learning ,[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG] ,Hardware and Architecture ,Control and Systems Engineering ,heart rate detection ,Signal Processing ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,Electrical and Electronic Engineering ,interference mitigation ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
International audience; This paper deals with robust heart rate detection intended for the in-car monitoring of people. There are two main problems associated with radar-based heart rate detection. Firstly, the signal associated with the human heart is difficult to separate from breathing harmonics in the frequency domain. Secondly, the vital signal is affected by any interference signal from hand gestures, lips motion during speech or any other random body motions (RBM). To handle the problem of the breathing harmonics, we propose a novel algorithm based on time series data instead of the conventionally used frequency domain technique. In our proposed method, a deep learning classifier is used to detect the pattern of the heart rate signal. To deal with the interference mitigation from the random body motions, we identify an optimum location for the radar sensor inside the car. In this paper, a commercially available Novelda Xethru X4 radar is used for signal acquisition and vital sign measurement of 5 people. The performance of the proposed algorithm is compared with and found to be superior to that of the conventional frequency domain technique.
- Published
- 2022
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