Lingyun Ren

Non-invasive detection of cardiac and respiratory rates from stepped frequency continuous wave radar measurements using the state space method

In this paper, we discuss the design of a stepped frequency continuous wave (SFCW) radar, which transmits long duration pulses with higher average power and much narrower instantaneous bandwidth than UWB waveforms, to facilitate comparable signal resolution. FFT spectrograms, typically used in the extraction of vital signs from radar measurements, produce several spurious peaks at harmonics and intermodulation frequencies of respiration and heart rates, thereby increasing the uncertainty of these estimates, especially the heart rate. We apply a signal processing algorithm based on the state-space method for the extraction of cardiac and respiration rates from the data measured on a human subject using SFCW radar. Results show that accurate estimates of vital signs (heart rate <; 1.2% in static mode and <; 5.7% in motion) can be obtained without producing inter-modulation products that plague signal resolution in FFT spectrograms.

Noncontact Multiple Heartbeats Detection and Subject Localization Using UWB Impulse Doppler Radar

In this letter, a phase-based algorithm based on a logarithmic method, applicable to UWB radars and suitable to real-time monitoring, is proposed to detect the phase variations of reflected pulses caused by the tiny cardiac motions. Compared with conventional FFT vital signs detection method, this algorithm demonstrates advantage in respiration harmonics suppression and avoidance of intermodulation between respiration and heartbeat signals. Furthermore, it is experimentally shown that UWB Doppler radar is capable of multiple heartbeats detection and subject identification/localization.

Noncontact heartbeat detection using UWB impulse doppler radar

Ultra-wide band (UWB) pulse Doppler radars provide range-time-frequency information which enables the target localization and vital sign monitoring of a subject. One challenge for UWB radar systems is accurately detecting the heartbeat of a subject, i.e. recording the small displacements of thorax caused by heartbeat due to its poor S/N ratio. Given that the phase-based algorithms are more robust against noise in heartbeat detection so it could lead to better demodulation of micro displacements. In this paper, two algorithms based on complex signal demodulation and arctangent method are extended here to UWB radars to detect the phase variation of reflected pulses caused by cardiac motions, results will be presented.

UWB MicroDoppler Radar for human Gait analysis, tracking more than one person, and vital sign detection of moving persons

Pulse Doppler radars using UWB technology are becoming very popular for their wide range of capabilities and applications. UWB waveforms are used for imaging in indoor environments, target localization and classification behind walls, and evaluating micro-Doppler signatures. UWB pulse Doppler radars provide range-time-frequency representation that provides both highly accurate range and micro-Doppler information. This representation is used for detailed human gait analysis, tracking more than one subject even behind walls, and respiration rate detection even for moving subjects. That can be very useful for remotely health monitoring. In this study we experimentally investigate applying UWB to tracking more than one human subject as well as detection of respiration rate of a moving person.

Phase-Based Methods for Heart Rate Detection Using UWB Impulse Doppler Radar

Ultra-wideband (UWB) pulse Doppler radars can be used for noncontact vital signs monitoring of more than one subject. However, their detected signals typically have low signal-to-noise ratio (SNR) causing significant heart rate (HR) detection errors, as the spurious harmonics of respiration signals and mixed products of respiration and heartbeat signals (that can be relatively higher than heartbeat signals) corrupt conventional fast Fourier transform spectrograms. In this paper, we extend the complex signal demodulation (CSD) and arctangent demodulation (AD) techniques previously used for accurately detecting the phase variations of reflected signals of continuous wave radars to UWB pulse radars as well. These detection techniques reduce the impact of the interfering harmonic signals, thus improving the SNR of the detected vital sign signals. To further enhance the accuracy of the HR estimation, a recently developed state-space method has been successfully combined with CSD and AD techniques and over 10 dB improvements in SNR is demonstrated. The implementation of these various detection techniques has been experimentally investigated and full error and SNR analysis of the HR detection are presented.

Estimation of Cardiopulmonary Parameters From Ultra Wideband Radar Measurements Using the State Space Method

Ultra wideband (UWB) Doppler radar has many biomedical applications, including remote diagnosis of cardiovascular disease, triage and real-time personnel tracking in rescue missions. It uses narrow pulses to probe the human body and detect tiny cardiopulmonary movements by spectral analysis of the backscattered electromagnetic (EM) field. With the help of super-resolution spectral algorithms, UWB radar is capable of increased accuracy for estimating vital signs such as heart and respiration rates in adverse signal-to-noise conditions. A major challenge for biomedical radar systems is detecting the heartbeat of a subject with high accuracy, because of minute thorax motion (less than 0.5 mm) caused by the heartbeat. The problem becomes compounded by EM clutter and noise in the environment. In this paper, we introduce a new algorithm based on the state space method (SSM) for the extraction of cardiac and respiration rates from UWB radar measurements. SSM produces range-dependent system poles that can be classified parametrically with spectral peaks at the cardiac and respiratory frequencies. It is shown that SSM produces accurate estimates of the vital signs without producing harmonics and inter-modulation products that plague signal resolution in widely used FFT spectrograms.

Comparison Study of Noncontact Vital Signs Detection Using a Doppler Stepped-Frequency Continuous-Wave Radar and Camera-Based Imaging Photoplethysmography

In this paper, we compare the performance of radar and optical (camera based) techniques in detecting vital signs such as respiratory rate (RR), heart rate (HR), and blood oxygen saturation (SpO2). Specifically, we investigate the application of ultrawideband stepped-frequency continuous-wave radar and imaging photoplethysmography (iPPG) techniques to measure vital signs. The radar performance can be enhanced by using phase information of backscattered signal instead of its amplitude. On the other hand, the iPPG system can be enhanced by using more than one camera and utilizing very selective narrowband filters coupled with good illumination. In either system, use of advanced signal processing is required to improve accuracy. Generally, HR and RR can be accurately read by either microwave radar or optical techniques with 500 lx illumination level to have < ±2% error up to 2 m distance between the subject and the system, but optical technique errors increase significantly to < ±15% for <200 lx. However, each system has its unique advantages as the radar can be used for seeing-through walls and optical technique is uniquely capable of measuring SpO2).

Overview of vital sign detection-simulation and measurements

Commercial EM software packages are not suitable to detect cardiac and respiratory motion of the chest cavity, crucial to vital sign detection, in the study of electromagnetic (EM) wave interaction with tissues using utilized phantom models. The tissue constitutive parameters are time dependent, and are strong function of the volume and physical composition of the tissue layers near the surface due to the associated physiological motion. In this paper, we consider a human body phantom model that includes physiological motion, and a state-space method to extract cardiac and respiration rates. The method is applied to simulated data as well as 3 GHz UWB radar measurements on a sedentary subject. It is shown that the state-space method accurately estimates vital signs without producing harmonics and inter-modulation products that plague signal resolution in commonly used auto-correlated FFT spectrograms relying on peak detection with errors less than 2%.

Comparison of UWB Doppler radar and camera based photoplethysmography in non-contact multiple heartbeats detection

RF and optical based photoplethysmography (PPG) have been recently developed for non-contact vital sign detection, due to their numerous advantages. In this paper, UWB radar, and camera-based monitoring are applied in vital sign detection and compared. In this paper, a mathematical signal model for the UWB Doppler radar, and another one for the camera-based photoplethysmography PPG are introduced. Vital signals have been recorded using both methods and compared. Capabilities and limitations of multiple subjects tracking have been demonstrated for multiple heartbeat detection. For validation, experimental results were compared to commercial contact sensors as well. Furthermore, the pros and cons of the Doppler radar and remote PPG in vital signs detection is discussed and summarized.

Investigation of vital signs monitoring errors due to subject's orientation, clothing and distance from a SFCW radar

In this paper, a stepped frequency continuous wave (SFCW) radar is utilized to investigate the effect of subject orientation, cloth, and location in detected vital sign accuracy. The accuracy of SFCW radar to detect cardiac rate is validated using a full-wave electromagnetic scattering model and compared to experimental results. Effect of subjects clothing, position (orientation), and range have been experimentally investigated and acceptable heart rate identification has been demonstrated.