Vital signs (e.g., heart and respiratory rate) are indicative for health status assessment. Efforts have been made to extract vital signs using radio frequency (RF) techniques (e.g., Wi-Fi, FMCW, UWB), which offer a non-touch solution for continuous and ubiquitous monitoring without users’ cooperative efforts. While RF-based vital signs monitoring is user-friendly, its robustness faces two challenges. On the one hand, the RF signal is modulated by the periodic chest wall displacement due to heartbeat and breathing in a nonlinear manner. It is inherently hard to identify the fundamental heart and respiratory rates (HR and RR) in the presence of higher order harmonics of them and intermodulation between HR and RR, especially when they have overlapping frequency bands. On the other hand, the inadvertent body movements may disturb and distort the RF signal, overwhelming the vital signals, thus inhibiting the parameter estimation of the physiological movement (i.e., heartbeat and breathing). In this paper, we propose DeepVS, a deep learning approach that addresses the aforementioned challenges from the non-linearity and inadvertent movements for robust RF-based vital signs sensing in a unified manner. DeepVS combines 1D CNN and
attention models to exploit local features and temporal correlations. Moreover, it leverages a two-stream scheme to integrate features from both time and frequency domains. Additionally, DeepVS unifies the estimation of HR and RR with a multi-head structure, which only adds limited extra overhead (<1%) to the existing model, compared to doubling the overhead using two separate models for HR and RR respectively. Our experiments demonstrate that DeepVS achieves 80-percentile HR/RR errors of 7.4/4.9 beat/breaths per
minute (bpm) on a challenging dataset, as compared to 11.8/7.3 bpm of a non-learning solution. Besides, an ablation study has been conducted to quantify the effectiveness of DeepVS.
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Measurement Study of FMCW Radar Configurations for Non-contact Vital Signs Monitoring
Non-contact vital signs monitoring (NCVSM) with radio frequency (RF) is attracting increasing attention due to its non-invasive nature. Recent advances in COTS radar technologies accelerate the development of RF-based solutions. While researchers have implemented and demonstrated the feasibility of NCVSM with diverse radar hardware, most efforts have been focused on devising algorithms to extract vital signs, with limited understanding about the effects of radar configurations. The deficiency in such understanding hinders the design of software defined radar (SDR) optimally customized for NCVSM. In this work, we first hypothesize the effects of FMCW radar configurations using signal-to-interference-plus-noise ratio (SINR) based signal modeling, then we conduct extensive experiments with a COTS FMCW radar, TinyRad, to understand how various parameters impact NCVSM performance compared to a medical device. We find that a larger bandwidth or higher transmitting power in general improves vital sign estimation accuracy; however, coherent processing of consecutive chirps (time diversity) or multiple receiving antennas (space diversity) does not improve the performance. Observations on the baseband (BB) signal show that coherent processing contributes to a higher amplitude but similar phase patterns, whose periodic changes are the key in extracting vital signs.
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- Award ID(s):
- 1951880
- NSF-PAR ID:
- 10356450
- Date Published:
- Journal Name:
- IEEE Radar Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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SUMMARY Infrasound sensors are deployed in a variety of spatial configurations and scales for geophysical monitoring, including networks of single sensors and networks of multisensor infrasound arrays. Infrasound signal detection strategies exploiting these data commonly make use of intersensor correlation and coherence (array processing, multichannel correlation); network-based tracking of signal features (e.g. reverse time migration); or a combination of these such as backazimuth cross-bearings for multiple arrays. Single-sensor trace-based denoising techniques offer significant potential to improve all of these various infrasound data processing strategies, but have not previously been investigated in detail. Single-sensor denoising represents a pre-processing step that could reduce the effects of ambient infrasound and wind noise in infrasound signal association and location workflows. We systematically investigate the utility of a range of single-sensor denoising methods for infrasound data processing, including noise gating, non-negative matrix factorization, and data-adaptive Wiener filtering. For the data testbed, we use the relatively dense regional infrasound network in Alaska, which records a high rate of volcanic eruptions with signals varying in power, duration, and waveform and spectral character. We primarily use data from the 2016–2017 Bogoslof volcanic eruption, which included multiple explosions, and synthetics. The Bogoslof volcanic sequence provides an opportunity to investigate regional infrasound detection, association, and location for a set of real sources with varying source spectra subject to anisotropic atmospheric propagation and varying noise levels (both incoherent wind noise and coherent ambient infrasound, primarily microbaroms). We illustrate the advantages and disadvantages of the different denoising methods in categories such as event detection, waveform distortion, the need for manual data labelling, and computational cost. For all approaches, denoising generally performs better for signals with higher signal-to-noise ratios and with less spectral and temporal overlap between signals and noise. Microbaroms are the most globally pervasive and repetitive coherent ambient infrasound noise source, with such noise often referred to as clutter or interference. We find that denoising offers significant potential for microbarom clutter reduction. Single-channel denoising of microbaroms prior to standard array processing enhances both the quantity and bandwidth of detectable volcanic events. We find that reduction of incoherent wind noise is more challenging using the denoising methods we investigate; thus, station hardware (wind noise reduction systems) and site selection remain critical and cannot be replaced by currently available digital denoising methodologies. Overall, we find that adding single-channel denoising as a component in the processing workflow can benefit a variety of infrasound signal detection, association, and location schemes. The denoising methods can also isolate the noise itself, with utility in statistically characterizing ambient infrasound noise.
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Wireless systems which can simultaneously transmit and receive (STAR) are gaining significant academic and commercial interest due to their wide range of applications such as full-duplex (FD) wireless communication and FMCW radar. FD radios, where the transmitter (TX) and the receiver (RX) operate simultaneously at the same frequency, can potentially double the data rate at the physical layer and can provide many other advantages in the higher layers. The antenna interface of an FD radio is typically built using a multi-antenna system, or a single antenna through a bulky magnetic circulator or a lossy reciprocal hybrid. However, recent advances in CMOS-integrated circulators through spatio-temporal conductivity modulation have shown promise and potential to replace traditional bulky magnetic circulators. However, unlike magnetic circulators, CMOS-integrated non-magnetic circulators will introduce some nonlinear distortion and spurious tones arising from their clock circuitry. In this work, we present an FD radio using a highly linear CMOS integrable circulator, a frequency-flat RF canceler, and a USRP software-defined radio (SDR). At TX power level of +15 dBm, the implemented FD radio achieves a self-interference cancellation (SIC) of +55 dB from the circulator and RF canceler in the RF domain, and an overall SIC of +95 dB together with SIC in the digital domain. To analyze the non-linear phenomena of the CMOS circulator, we calculated the link level data-rate gain in an FD system with imperfect SIC and then extended this calculation to count the effect of TX-RX non-linearity of the circulator. In addition, we provide a qualitative discussion on the spurious tone responses of the circulator due to the clocking imperfections and non-linearity. Index Terms—Circulator, CMOS, conductivity modulation, full-duplex, non-reciprocity, self-interference cancellation.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/RadarConf2248738.2022.9764200
