Contactless Heart and Respiration Rates Estimation and Classification of Driver Physiological States Using CW Radar and Temporal Neural Networks - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Sensors Année : 2023

Contactless Heart and Respiration Rates Estimation and Classification of Driver Physiological States Using CW Radar and Temporal Neural Networks

Résumé

The measurement and analysis of vital signs are a subject of significant research interest, particularly for monitoring the driver's physiological state, which is of crucial importance for road safety. Various approaches have been proposed using contact techniques to measure vital signs. However, all of these methods are invasive and cumbersome for the driver. This paper proposes using a non-contact sensor based on continuous wave (CW) radar at 24 GHz to measure vital signs. We associate these measurements with distinct temporal neural networks to analyze the signals to detect and extract heart and respiration rates as well as classify the physiological state of the driver. This approach offers robust performance in estimating the exact values of heart and respiration rates and in classifying the driver's physiological state. It is non-invasive and requires no physical contact with the driver, making it particularly practical and safe. The results presented in this paper, derived from the use of a 1D Convolutional Neural Network (1D-CNN), a Temporal Convolutional Network (TCN), a Recurrent Neural Network particularly the Bidirectional Long Short-Term Memory (Bi-LSTM), and a Convolutional Recurrent Neural Network (CRNN). Among these, the CRNN emerged as the most effective Deep Learning approach for vital signal analysis.
Fichier principal
Vignette du fichier
sensors-23-09457.pdf (1.37 Mo) Télécharger le fichier
Origine : Publication financée par une institution

Dates et versions

hal-04419992 , version 1 (26-01-2024)

Identifiants

Citer

Amal El Abbaoui, David Sodoyer, Fouzia Elbahhar. Contactless Heart and Respiration Rates Estimation and Classification of Driver Physiological States Using CW Radar and Temporal Neural Networks. Sensors, 2023, 23, ⟨10.3390/s23239457⟩. ⟨hal-04419992⟩
22 Consultations
7 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More