The ability to remotely assess vital signs using radar systems may potentialize the healthcare systems, since it does not require any direct interaction with the subject. Nonetheless, these systems present inherent challenges that could compromise the accuracy of the vital signs parameters. For instance, there is a lack of resolution on the cardiac signal, since the radar only detects the chest micro-displacement. Low cardiac resolution prevents the exact localization of signal peaks, compromising the heart rate variability (HRV) assessment. In this work, we use a customized bandpass filter (BPF) obtained through adaptive filtering, applied to the electrocardiography (ECG) signal to generate the corresponding synthetic radar signal. This provides an easy way to extract a cardiac radar signal model, free of issues that arise from random body motion (RBM) or from an eventual decrease in signals quality, which are inherent issues of long-term acquisitions. This model was further used to verify if the signal resolution provided by lower carrier radars is suitable to determine the HRV parameters accurately.

Real-time frequency agility is one of the key limitations of current all-digital transmitters (ADTs). In this paper, to address this problem, an ADT based on direct-RF generation is proposed and implemented in a field-programmable gate array (FPGA). To achieve this, the pulse encoding is performed after the digital upconversion, which presents challenges in the pulse encoder implementation. However, the proposed design considerably improves the frequency agility when compared with current state-of-the-art approaches. Two different pulse encoders were designed in this paper, one is based on pulsewidth modulation (PWM) and the other on delta-sigma modulation (ΔΣM). These units are implemented with high parallelization to achieve the required equivalent sampling rates. The proposed design enables the implementation of all-digital RF transmitters in FPGA with a widely tunable carrier frequency. In this paper, a variation from 0.1 up to 6 GHz of carrier frequency, with a maximum frequency resolution of 1.5625 MHz, is demonstrated. Measurement results in terms of signal-to-noise ratio (SNR) and error-vector magnitude are presented and discussed. In the case of the PWM, maximum SNRs of 39 and 36 dB were obtained for a 5 and 10 MBd of symbol rates (SRs). In the case of ΔΣM, maximum SNRs of 38 and 35 dB were obtained for 20 and 40 MBd of the SR.

The bio-radar system can measure vital signals accurately, by using the Doppler effect principle, which relates the received signal properties to the distance change between the radar antennas and the subject chest-wall. These systems have countless applications, from short range detection to assist in rescue missions, to long-term applications as for the continuous sleeping monitoring. Once the main applications of these systems intend to monitor subjects during long periods of time and under noisy environments, it is impossible to guarantee the patient immobilization, hence its random motion, as well as other clutter sources, will interfere in the acquired signals. Therefore, the signal processing algorithms developed for these applications have been facing several challenges regarding the random motion detection and mitigation. In this paper, an extended review on the already implemented methods is done, considering continuous wave radars. Several sources of random motion are considered, along with different approaches to compensate the distortions caused by them.

Cardiopulmonary activity measured through contactless means is a hot topic within the research community. The Doppler radar is an approach often used to acquire vital signs in real time and to further estimate their rates, in a remote way and without requiring direct contact with subjects. Many solutions have been proposed in the literature, using different transceivers and operation modes. Nonetheless, all different strategies have a common goal: enhance the system efficiency, reduce the manufacturing cost, and minimize the overall size of the system. Antennas are a key component for these systems since they can influence the radar robustness directly. Therefore, antennas must be designed with care, facing several trade-offs to meet all the system requirements. In this sense, it is necessary to define the proper guidelines that need to be followed in the antenna design. In this manuscript, an extensive review on different antenna designs for non-contact vital signals measurements is presented. It is intended to point out and quantify which parameters are crucial for the optimal radar operation, for non-contact vital signs’ acquisition.

This paper presents a new all-digital transceiver architecture fully integrated into a single field-programmable gate array chip. Both the radio frequency (RF) receiver and the transmitter were entirely implemented using a digital datapath from the baseband up to the RF stage without the use of conventional analog-to-digital converter, digital-to-analog converter, or analog mixer. The transmitter chain uses delta-sigma modulation and digital upconversion to produce a two-level RF output signal. The receiver uses a high-speed comparator and pulsewidth modulation to convert the RF signal into a single-bit data stream, which is digitally filtered and then downconverted. Both the transmitter and the receiver are agile with flexible carrier frequency, bandwidth, and modulation capabilities. The transceiver error vector magnitude and the signal-to-noise ratio figures of merit were analyzed in a point-to-point transmission to evaluate the transmitter's performance. The results show the feasibility of this approach as a more flexible alternative to common radio architectures.

For an efficient exploitation of the RF spectrum, very sophisticated analog-to-digital front-ends for modern cognitive-/software-defined radios featuring high sampling rate and dynamic range are required to properly handle broadband frequency-sparse signals. For this purpose, a receiver solution based on a mixed-analog/digital-domain channelizer can be advantageous, with added benefits regarding system reconfigurability and parallelization of multiband signal processing. Here, a novel receiver architecture using this approach for the commented application is described, with a special focus on the IF hybrid filter bank as its core element. The analog part of the hybrid filter bank is a 50-100-MHz eight-channel analog multiplexer inspired in the human hearing system. The associated digital block can be co-synthesized as a discrete-time filter bank to invert the action of the IF analog channelizer. As a benefit, hardware imperfections inherent to the analog circuitry can be easily counteracted at the digital level. Furthermore, such a channelization enables low-cost analog-to-digital converters to be utilized for the sampling of the signal sub-bands to be later digitally processed for the overall signal reconstruction. For validation, measured and simulated results of a proof-of-concept prototype for the analog channelizer are shown. Besides, the inversion of the measured transfer functions of this multiplexing device by means of the application of the co-designed digital filter bank is demonstrated. An experiment is also carried out showing the reconstruction of a band-limited noise signal with the developed hybrid filter bank.