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Consumer-grade range cameras such as the Kinect sensor have the potential to be used in mapping applications where accuracy requirements are less strict. To realize this potential insight into the geometric quality of the data acquired by the sensor is essential. In this paper we discuss the calibration of the Kinect sensor, and provide an analysis of the accuracy and resolution of its depth data. Based on a mathematical model of depth measurement from disparity a theoretical error analysis is presented, which provides an insight into the factors influencing the accuracy of the data. Experimental results show that the random error of depth measurement increases with increasing distance to the sensor, and ranges from a few millimeters up to about 4 cm at the maximum range of the sensor. The quality of the data is also found to be influenced by the low resolution of the depth measurements.

This paper presents the novel design of a printed, low-cost, dual-port, and dual-polarized slot antenna for microwave biomedical radars. The butterfly shape of the radiating element, with orthogonally positioned arms, enables simultaneous radiation of both vertically and horizontally polarized waves. The antenna is intended for full-duplex in-band applications using two mutually isolated antenna ports, with the CPW port on the same side of the substrate as the slot antenna and the microstrip port positioned orthogonally on the other side of the substrate. Those two ports can be used as transmit and receive ports in a radar transceiver, with a port isolation of 25 dB. Thanks to the bow-tie shape of the slots and an additional coupling region between the butterfly arms, there is more flexibility in simultaneous optimization of the resonant frequency and input impedance at both ports, avoiding the need for a complicated matching network that introduces the attenuation and increases antenna dimensions. The advantage of this design is demonstrated through the modeling of an eight-element dual-port linear array with an extremely simple feed network for high-gain biosensing applications. To validate the simulation results, prototypes of the proposed antenna were fabricated and tested. The measured operating band of the antennas spans from 2.35 GHz to 2.55 GHz, with reflection coefficients of less than—10 dB, a maximum gain of 8.5 dBi, and a front-to-back gain ratio that is greater than 15 dB, which is comparable with other published single dual-port slot antennas. This is the simplest proposed dual-port, dual-polarization antenna that enables straightforward scaling to other frequency bands.

Autonomous vehicles are regarded as future transport mechanisms that drive the vehicles without the need of drivers. The photonic-based radar technology is a promising candidate for delivering attractive applications to autonomous vehicles such as self-parking assistance, navigation, recognition of traffic environment, etc. Alternatively, microwave radars are not able to meet the demand of next-generation autonomous vehicles due to its limited bandwidth availability. Moreover, the performance of microwave radars is limited by atmospheric fluctuation which causes severe attenuation at higher frequencies. In this work, we have developed coherent-based frequency-modulated photonic radar to detect target locations with longer distance. Furthermore, the performance of the proposed photonic radar is investigated under the impact of various atmospheric weather conditions, particularly fog and rain. The reported results show the achievement of significant signal to noise ratio (SNR) and received power of reflected echoes from the target for the proposed photonic radar under the influence of bad weather conditions. Moreover, a conventional radar is designed to establish the effectiveness of the proposed photonic radar by considering similar parameters such as frequency and sweep time.

A new modulation scheme for frequency-modulated continuous-wave (FMCW) radars with millimeter-level target motion detection capability is presented. The proposed radar scheme is free from the synchronization constraint and exhibits low sensitivity to internal parasitic mutual coupling, thus significantly reducing its design complexity without worsening its performance in terms of accuracy and operating ranges. Alternatively to canonical FMCW radars, which exploit chirp signals with triangular or sawtooth-like frequency variation, a radar based on a sinusoidal frequency modulation, which does not require specific synchronization procedures to achieve accurate motion detection even at a short distance from the radar, was developed. Both numerical and experimental results, performed with a 24 GHz radar, have shown the suitability of the proposed modulation scheme for monitoring very small target movements, consistent with those typically exhibited by the human thorax during basic vital activities (heartbeat and respiration). This makes the proposed radar scheme a suitable solution for contactless heart and breath rate monitoring.

We discovered that impulse-radio ultra-wideband (IR-UWB) radar could recognize cardiac motions in a non-contact fashion. Therefore, we measured the heart rate (HR) and rhythms using an IR-UWB radar sensor and evaluated the validity and reliability of the measurements in comparison to electrocardiography. The heart beats were measured in 6 healthy volunteers (18 samples) with normal sinus rhythm (NSR) and 16 patients (36 samples) with atrial fibrillation (AF) using both an IR-UWB radar sensor and electrocardiography simultaneously. The participants hold their breath for 20 seconds during the data acquisition. In subjects with NSR, there was excellent agreement of HR (intraclass correlation coefficient [ICC] 0.856), average R-R interval (ICC 0.997) and individual R-R intervals between the two methods (ICC 0.803). In subjects with AF, HR (ICC 0.871) and average R-R interval (ICC 0.925) from the radar sensor also agreed well with those from electrocardiography, though there was a small disagreement in the individual R-R intervals between the two methods (ICC 0.697). The rhythms computed by the signal-processing algorithm showed good agreement between the two methods (Cohen’s Kappa 0.922). The IR-UWB radar sensor is precise and accurate for assessing HR and rhythms in a non-contact fashion.

Over the last 30 years, harmonic radars have been effective only in tracking insects flying at low altitude and over flat terrain. We developed an innovative harmonic radar, implementing the most advanced radar techniques, which covers a large field of view in elevation (with an angular aperture of about 24°) and can track insects up to a range of 500 m. We show all the components of this new harmonic radar and its first application, the tracking of Vespa velutina (yellow-legged Asian hornet). This is an invasive species which, although indigenous to South-East Asia, is spreading quickly to other regions of the world. Because of its fast diffusion and the serious threat it poses to both honeybee colonies and to humans, control measures are mandatory. When equipped with a small passive transponder, this radar system can track the flight trajectory of insects and locate nests to be destroyed. This tool has potential not only for monitoring V. velutina but also for tracking other larger insects and small size vertebrates.

This study introduces a novel seatbelt-integrated, non-invasive, beam-focusing metamaterial sensing system characterized by its thinness and flexibility. The system comprises a flexible transmitarray lens and an FMCW radar sensor, enabling the accurate detection and analysis of seatbelt usage and positioning through human tissue. The metasurface design remains effective even when subjected to different bending angles. Our system closely tracks heart rate and respiration, validated against standard reference methods, highlighting its potential for enhancing in-car healthcare monitoring. Experimental results demonstrate the system’s reliability in monitoring physiological signals within dynamic vehicular environments.

While full-night polysomnography is the gold standard for the diagnosis of obstructive sleep apnea, its limitations include a high cost and first-night effects. This study developed an algorithm for the detection of respiratory events based on impulse-radio ultra-wideband radar and verified its feasibility for the diagnosis of obstructive sleep apnea. A total of 94 subjects were enrolled in this study (23 controls and 24, 14, and 33 with mild, moderate, and severe obstructive sleep apnea, respectively). Abnormal breathing detected by impulse-radio ultra-wideband radar was defined as a drop in the peak radar signal by ≥30% from that in the pre-event baseline. We compared the abnormal breathing index obtained from impulse-radio ultra-wideband radar and apnea–hypopnea index (AHI) measured from polysomnography. There was an excellent agreement between the Abnormal Breathing Index and AHI (intraclass correlation coefficient = 0.927). The overall agreements of the impulse-radio ultra-wideband radar were 0.93 for Model 1 (AHI ≥ 5), 0.91 for Model 2 (AHI ≥ 15), and 1 for Model 3 (AHI ≥ 30). Impulse-radio ultra-wideband radar accurately detected respiratory events (apneas and hypopneas) during sleep without subject contact. Therefore, impulse-radio ultra-wideband radar may be used as a screening tool for obstructive sleep apnea.

This paper investigates the Frequency Modulation Continuous Wave (FMCW) radar sensor for multi-target displacement measurement in Structural Health Monitoring (SHM). The principle of three-dimensional (3-D) displacement measurement of civil infrastructures is analyzed. The requirements of high-accuracy displacement and multi-target identification for the measuring sensors are discussed. The fundamental measuring principle of FMCW radar is presented with rigorous mathematical formulas, and further the multiple-target displacement measurement is analyzed and simulated. In addition, a FMCW radar prototype is designed and fabricated based on an off-the-shelf radar frontend and data acquisition (DAQ) card, and the displacement error induced by phase asynchronism is analyzed. The conducted outdoor experiments verify the feasibility of this sensing method applied to multi-target displacement measurement, and experimental results show that three targets located at different distances can be distinguished simultaneously with millimeter level accuracy.

Study Objectives: The gold standard for diagnosing obstructive sleep apnea (OSA) is polysomnography (PSG). However, PSG is a time-consuming method with clinical limitations. This study aimed to create a wireless radar framework to screen the likelihood of 2 levels of OSA severity (ie, moderate-to-severe and severe OSA) in accordance with clinical practice standards. Methods: We conducted a prospective, simultaneous study using a wireless radar system and PSG in a Northern Taiwan sleep center, involving 196 patients. The wireless radar sleep monitor, incorporating hybrid models such as deep neural decision trees, estimated the respiratory disturbance index relative to the total sleep time established by PSG (RDI PSG_TST ), by analyzing continuous-wave signals indicative of breathing patterns. Analyses were performed to examine the correlation and agreement between the RDI PSG_TST and apnea-hypopnea index, results obtained through PSG. Cut-off thresholds for RDI PSG_TST were determined using Youden’s index, and multiclass classification was performed, after which the results were compared. Results: A strong correlation (ρ = 0.91) and agreement (average difference of 0.59 events/h) between apnea-hypopnea index and RDI PSG_TST were identified. In terms of the agreement between the 2 devices, the average difference between PSG-based apnea-hypopnea index and radar-based RDI PSG_TST was 0.59 events/h, and 187 out of 196 cases (95.41%) fell within the 95% confidence interval of differences. A moderate-to-severe OSA model achieved an accuracy of 90.3% (cut-off threshold for RDI PSG_TST : 19.2 events/h). A severe OSA model achieved an accuracy of 92.4% (cut-off threshold for RDI PSG_TST : 28.86 events/h). The mean accuracy of multiclass classification performance using these cut-off thresholds was 83.7%. Conclusions: The wireless-radar-based sleep monitoring device, with cut-off thresholds, can provide rapid OSA screening with acceptable accuracy and also alleviate the burden on PSG capacity. However, to independently apply this framework, the function of determining the radar-based total sleep time requires further optimizations and verification in future work. Citation: Lin S-Y, Tsai C-Y, Majumdar A, et al. Combining a wireless radar sleep monitoring device with deep machine learning techniques to assess obstructive sleep apnea severity. J Clin Sleep Med . 2024;20(8):1267–1277.