Dany Obeid

Touch-less heartbeat detection and cardiopulmonary modeling

This paper presents a contact-less heartbeat detection system and a cardiopulmonary modeling. Using a vector network analyzer, our proposed microwave system shows the ability of detecting the heartbeat signal at different frequencies, as well as at different output power levels. Based on parameters extracted from real measurements, a model representing the heartbeat and the respiration signals is presented. Different processing techniques are used in order to separate the heartbeat and the respiration signals. For different signal to noise ratios, wavelet filters show higher accuracy over classic filters in determining both the heartbeat rate and the heart rate variability.

Touch-less heartbeat detection and measurement-based cardiopulmonary modeling

This paper presents a system for touch-less heartbeat detection and a cardiopulmonary signal modeling approach. Using a vector network analyzer, a microwave system is tested for the detection of the heartbeat signal at a distance of 1 m from a person. The proposed system shows the ability of detecting the heartbeat signals with the possibility of tuning both frequency and power. Measurements are performed at 2.4, 5.8, 10, 16, and 60 GHz, as well as at different power levels between 0 and −27 dBm. Based on measurements performed for both respiration and heart beatings, a model of the measured signals representing the cardiopulmonary activity is presented. The heartbeat rate and the heart rate variability are extracted from the modeling signal using wavelet and classic filters, for SNR between 0 and −20 dB.

A tunable-frequency system for touch-less heartbeat detection and HRV extraction

This paper presents a practical study for heartbeat detection at 1 m distance. Our microwave system, based on a vector network analyzer, is used at 2.4 GHz, 5.8 GHz, 10 GHz, 16 GHz, and 60 GHz. Heart Rate Variability is extracted from the time domain variation of the phase of S21 for both the original and the smoothed signal, and its standard deviation is calculated.

Contact-less measurement system for cardiopulmonary activity

This paper presents a wireless cardiopulmonary activity measurement system. This system generates a continuous wave toward a persons chest set at a distance of 1 m, then reflected to the system. Using a vector network analyzer, the phase of S21 is computed. The phase variation of S21 contains information about cardiopulmonary activity. Several processing techniques are used to separate heartbeat signal from cardiorespiratory signal either in frequency or in temporal domain. The measurements were performed simultaneously with a PC-based electrocardiogram to validate the heartbeat rate detection techniques. In conclusion, processing techniques used in this paper give accurate results.

ECG vs. single-antenna system for heartbeat activity detection

This paper presents a single antenna Doppler system for contact-less heartbeat monitoring. The proposed system, based on using a vector network analyzer, is tested at 16 GHz frequency for different transmitted power levels between 0 and -25 dBm. Both heartbeat rate and heart rate variability are extracted from the signals obtained with the Doppler system and compared to simultaneous ECG signals.

Advances in microwave systems for medical applications

A new system for contact-less heartbeat detection is proposed. Operating at 2.4, 5.8, 10, 16, and 60 GHz, our system shows the possibility to detect the heartbeat rate at a distance of 1 m from the person. The heart rate variability is extracted as well. Originating from experimental measurements, a model presenting the cardiopulmonary activities is proposed. Separating the heartbeat signal from the respiration signal is done using different methods and for several SNR values.

Position-Free Vital Sign Monitoring: Measurements and Processing

As traditional electrodes are perturbing for patients in critical cases such as for burn victims or newborn infants, and even to detect life sign under rubble, a contactless monitoring system for the life signs is a necessity. The aim of this chapter is to present a complete process used in detecting cardiopulmonary activities. This includes a microwave Doppler radar system that detects the body wall motion and signal processing techniques in order to extract the heartbeat rate. Measurements are performed at different positions simultaneously with a PC-based electrocardiogram (ECG). For a distance of 1 m between the subject and the antennas, measurements are performed for breathing subject at four positions: front, back, left, and right. Discrete wavelet transform is used to extract the heartbeat signal from the cardiopulmonary signal. The proposed system and signal processing techniques show high accuracy in detecting the cardiopulmonary signals and extracting the heartbeat rate.