Changes in Pediatric Trauma During the COVID-19 Pandemic; Does the Pandemic Have an Effect on the Severity of Traumas?

Aim:Traumas are the most common cause of mortality and morbidity in children. Coronavirus disease-2019 (COVID-19) was shown to affect pediatric mental health, child neglect, and the occurrence of traumatic injuries. This study aimed to characterize pediatric trauma cases presenting to our institution before and after the pandemic began.Materials and Methods:Patients with trauma who were admitted to our emergency department between March, 2019 and March, 2021 were included. The patients were classified into two groups as before and after the pandemic began (March, 2020). Trauma characteristics, the severity of the injury, and prognosis were assessed. The patients’ injury severity scores (ISS) and pediatric trauma scores (PTS) were noted.Results:A total of 1,718 patients were included in this study. The number of pediatric trauma admissions dropped from 1,039 to 679 after the pandemic started. There was no difference between these groups in terms of age (p=0.874) or gender (p=0.106). There was a significant decrease in the number of traumatic injuries (p<0.001) especially during the first shutdown period (April, May, and June, 2020. Additionally, there was a significant increase in terms of foreign body aspiration (p=0.001) and pedestrian injuries (p=0.016). Although a significant increase was noted in the ISS of the patients (p<0.001), no differences were found between the PTSs (p=0.075) or multi-organ injuries (p=1.000). Also, no significant differences were observed regarding mortality (p=0.650), household accidents (p=0.600), trauma type (p=0.533), the need for transfusion (p=0.166), surgery (p=0.077) or mechanical ventilation (p=0.464) between the two groups.Conclusion:The COVID-19 pandemic altered social patterns, leading to a decrease in pediatric traumas. This decrease was most prominent during the shutdown period. The variables showing severe trauma, such as the need for surgery, did not change despite a significant increase in ISS. This was attributed to a decrease in admissions for minor trauma

A Sub-6 GHz Vital Signs Sensor Using Software Defined Radios

Recently, there has been high demand for contactless devices for monitoring vital signs, therefore developing a low-cost contactless breathing sensor would have a great benefit for many patients and healthcare workers. In this paper, we propose a contactless sub-6 GHz breathing sensor with an implementation using a low-cost universal software radio peripheral (USRP) B205-mini device. A detailed performance analysis of the proposed system with different sensor algorithms is presented. The proposed system estimates the channel phase shift and detects the presence of low frequency oscillations in the estimated phase shift. Compared to 24 or 77 GHz FMCW-radar-based systems using distance measurements, the proposed system is simpler, can be built using more economical RF components, and requires lower sampling frequencies. Another key advantage of the proposed system is that even a very narrow unused frequency band is enough for the operation of the sensor. When operated at frequencies shared by other devices, the proposed system can turn off the transmitter at randomly selected intervals to detect the presence of other transmission activities, and can then switch to a different operating frequency. We provide both Python- and Octave/MATLAB-based implementations, which are available in a public GitHub repository

A Novel Nonlinearity Correction Algorithm for FMCW Radar Systems for Optimal Range Accuracy and Improved Multitarget Detection Capability

Frequency-modulated continuous wave (FMCW) radars are an important class of radar systems, and they are quite popular because of their simpler architecture and lower cost. A fundamental problem in FMCW radars is the nonlinearity of the voltage-controlled oscillator (VCO), which results in a range of measurement errors, problems in multitarget detection, and degradation in synthetic aperture radar (SAR) images. In this paper, we first introduce a novel upsampling theory, then propose new algorithms to improve range accuracy and multitarget detection capability. These improvements are demonstrated both by simulations and actual lab experiments on a 2.4 GHz radar system. There are several techniques reported in the literature for VCO nonlinearity correction, but what makes the proposed approach different is that we focus on real-time processing on low-cost hardware and optimize the design subject to this constraint. We first developed an optimal upsampling theory which is based on almost-causal finite impulse response (FIR) filters. Compared to the sinc-based noncausal interpolation-based upsamplers, the proposed approach is based on using interpolation filters with few number of coefficients. Furthermore, interpolators are trained for a specific class of signals rather than a highly general signal set. Therefore, the proposed approach can be implemented on lower-cost hardware and perform quite well compared to more expensive systems

On the computation of suboptimal Hinfinity controllers for unstable infinite dimensional systems

Toker, Onur; Ozbay, Hitay. (1992). On the computation of suboptimal Hinfinity controllers for unstable infinite dimensional systems. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/2242

Computation of ℓ2[0, h] induced norms

This paper studies computation of ℓ2[0, h] induced norms of finite-dimensional linear systems. The problem under study plays an important role in several H∞ control problems pertaining to linear time-delay and sampled-data systems. We provide new characterizations of the ℓ2[0, h] induced norm, and based upon the new characterizations we propose an effective algorithm for its computation

Polar format statistical image processing based fiber optic pressure sensors

ABSTRACT This paper presents detailed study on the development of a fiber optic sensor system to design a pressure sensor with different sensor configurations. The sensor used in the experiments is based on modal power distribution (MPD) technique. MPD technique is spatial modulation of the modal power in multimode fibers. Stress measurements and CCD camera based techniques were investigated in this research. Differently from earlier MPD works, all of the data gathered from CCD camera are used instead of using some part of the data, the ring shaped pictures taken from the CCD camera converted to polar coordinates, and so stripe shaped pictures are obtained. Four different features are calculated from these converted pictures. R component of the center of mass in the polar form is the first feature. It is calculated because it was expected to decrease monotonically with respect to increasing applied pressure. Second and third features are ring thickness in polar form with taking brightness of each pixel into account and ring thickness in polar form without taking brightness of each pixel into account. These features are calculated to analyze the effect of each pixel&apos;s brightness. It was expected for these two features that there will not be a big margin between them. Fourth feature is the ratio between third feature and first feature. A MATLAB code is written to correlate these features and applied force to the sensor. Various experiments conducted to analyze this correlation. Pictures are taken from CCD camera with 1 kg steps and from the written MATLAB code, graphics of each feature versus the applied force are generated. Experimental results showed that, the sensitivity of the proposed sensor is much higher than sensors that uses only some part of the collected data in earlier MPD studies. Furthermore, results are almost exactly the same that what was expected for the four proposed features. Results also showed that converting pictures to the polar form increases the sensitivity and reliability