Predicting Difficult Laryngoscopy in Morbidly Obese Patients by Ultrasound of Distance from Skin to Epiglottis: A Prospective Observational Study

BackgroundIn morbidly obese patients, airway management is challenging since the incidence of difficult intubation is 3 times that in normal patient. Standard preoperative airway evaluation may help to indicate for probability of difficult laryngoscopy. Recent studies have used ultrasonography-measured distance from skin to epiglottis and pretracheal soft tissue at the level of vocal cords, and cut-points of 27.5 mm and 28 mm respectively, to predict difficult laryngoscopy. The purpose of this study is to use ultrasonography-measured distance from skin to epiglottis for predicting difficult laryngoscopy in morbidly obese Thai patients.MethodsThis prospective observational study was approved by the Ethics Committee of the Faculty of Medicine, Prince of Songkla University. Data were collected from January 2018 to August 2020. Eighty-eight morbidly obese patients (BMI ≥ 35 kg/m2) requiring general anesthesia with endotracheal intubation for elective surgery in Songklanagarind Hospital were enrolled. Preoperatively, anesthesiologists or nurse anesthetists who were not involved with intubating the patients evaluated and recorded measurements (body mass index, neck circumference, inter incisor gap, sternomental distance, thyromental distance, modified Mallampati scoring, upper lip bite test, and distance from skin to epiglottis by ultrasound. The laryngoscopic view was graded on the Cormack and Lehane scale. ResultsMean BMI of the eighty-eight patients was 45.3 ± 7.6 kg/m2. The incidence of difficult laryngoscopy was 14.8%. Univariate analysis for difficult laryngoscopy indicated differences in thyromental distance, sternomental distance and the distance from skin to epiglottis by ultrasonography. The median (IQR) of thyromental distance in difficult laryngoscopy was 6.5 (6.3, 8.0) cm compared with 7.5(7.0, 8.0) cm in easy laryngoscopy (p-value 0.03). The median (IQR) of sternomental distance in difficult laryngoscopy was 16.8 (15.2, 18.0) cm compared with 16.0 (14.5, 16.0) cm in easy laryngoscopy (p-value 0.05). The mean distance from skin to epiglottis was 12.2 ± 3.3 mm Mean of distance from skin to epiglottis in difficult laryngoscopy was 12.5 ± 3.3 mm compared with 10.6 ± 2.9 mm in easy laryngoscopy (p-value 0.05). Multivariate logistic regression indicated the following factors associated with difficult laryngoscopy: age more than 43 years (A), thyromental distance more than 68 mm(B) and the distance from skin to epiglottis more than 13 mm(C). The scores to predict difficult laryngoscopy was calculated as 8A+7B+6C. One point is given for A if age was more than 43 years old, 1 point is given for B if thyromental distance was less than 6.8 cm and 1 point is given for C if the distance from skin to epiglottis by ultrasonography was more than 13.0 cm. The maximum predicting score is 21, which indicates a probability of difficult laryngoscopy among our patients of 36.36%, odds 0.57, likelihood ratio 3.29 and area under the ROC curve of 0.78.ConclusionsAge, thyromental distance and ultrasonography for the distance from skin and epiglottis can predict difficult laryngoscopy among obese Thai patients. The predictive score indicates the probability of difficult laryngoscopy.

Analisis Performa Bluetooth pada Sistem Alarm Pengingat Barang yang Tertinggal dengan Smartphone Android

Someone sometimes forgets to put their belongings so that they leave them somewhere, it will pose a risk of losing their belongings. To solve this problem, a reminder is needed so that it is expected to minimize the risk of loss. This device implements point-to-point communication from the Bluetooth Low Energy AT-09 transmitter module with Arduino Nano and the receiver module with an Android smartphone. This reminder device will activate an alarm on the Android smartphone application when the two modules are more than 5 meters away. The measured distance is converted from the Received Signal Strength Indicator (RSSI) value received by the smartphone which is affected by obstructions, packet loss, and delay. Based on the test results, at a distance of 5 meters, the system can be connected and work properly, in unobstructed conditions (Line of Sight) or obstructed conditions (Non-Line of Sight). In the blocked condition, it has a packet loss of 1.1% to 4.4%, the received signal strength (RSSI) has decreased the value to a difference of -8 dBm, and the delay time is 2 seconds.

Study on Heat Sources of Horizontal Lathe Machine by Using Inverse Method

Thermal has significantly effect on high speed machine tools. When temperature growing up, it often causes processing errors and further reduces product quality. This paper aims to investigate magnitude of heat sources and temperature distribution in a horizontal lathe based on inverse method. In present thermal model, there is not only consideration of spindle but also analyzing relative structures. Simulated and experimental temperatures are used as input data to predict heat sources and temperature field. Effects of speed, number measured points, measurement errors and measured distance on predicted results are analyzed. Results indicate that this inverse method can accurately estimate the heat sources based on two measured temperatures at front and rear outer rings. The trend of estimated heat sources is then compared to measured load rate. Results herein are useful information for designing horizontal lathe spindle and reducing thermal errors.

Temperature Acquisition System for Real Time Application of First Velocity Correction by EDM (Electronic Distance Measurement)

The first velocity correction is used to correct the measured distance affected by the velocity variation of the electromagnetic wave propagation in a medium. This correction depends on the refractive index of the propagation medium and reference refractive index. The influence of the temperature in the medium refractive index is critical; some estimates establish that variation 1°C causes 1ppm of error in distances. In the measuring processes with total stations, the temperature is usually collected at only one point, for example, in the position where the measuring instrument is setup. However, the wave propagates in a medium of non-constant temperature, where the extremes of the line can present variations and thus this measurement in only one point could be non-representative. In this context, it was developed a low-cost real-time temperature acquisition system. This system provides the temperature values in different locations allowing their monitoring through the time. Experiments realized during the geodetic monitoring of a dam, show variations up to 8°C among geodetic points on the dam and around it. An analysis was development to evaluate the influence of temperature variations on monitoring distances and geodetic coordinate of a 2d network with different approaches (temperature modeling). The results shows different values for distances (1.0 mm) and coordinates (0.5 mm) depending of the approach choose.

Phase Stability under Thermal Drifts in Photodiode-Conditioning Transimpedance Amplifiers for Distance Metrology

Transimpedance amplifiers (TIA) are widely used for front-end signal conditioning in many optical distance measuring applications in which high accuracy is often required. Small effects due to the real characteristics of the components and the parasitic elements in the circuit board may cause the error to rise to unacceptable levels. In this work we study these effects on the TIA delay time error and deduce analytic expressions, taking into account the trade-off between the uncertainties caused by the delay time instability and by the signal-to-noise ratio. A specific continuous-wave phase-shift case study is shown to illustrate the analysis, and further compared with real measurements. General strategies and conclusions, useful for designers of this kind of system, are extracted too. The study and results show that the delay time thermal stability is a key determinant factor in the measured distance accuracy and, without an adequate design, moderate temperature variations of the TIA can cause extremely high measurement errors.

Deep Learning-Based Concrete Surface Damage Monitoring Method Using Structured Lights and Depth Camera

Due to the increase in aging structures and the decrease in construction workforce, there is an increasing interest in automating structural damage monitoring. Surface damage on concrete structures, such as cracks, delamination, and rebar exposure, is one of the important parameters that can be used to estimate the condition of the structure. In this paper, deep learning-based detection and quantification of structural damage using structured lights and a depth camera is proposed. The proposed monitoring system is composed of four lasers and a depth camera. The lasers are projected on the surface of the structures, and the camera captures images of the structures while measuring distance. By calculating an image homography, the captured images are calibrated when the structure and sensing system are not in parallel. The Faster RCNN (Region-based Convolutional Neural Network) with Inception Resnet v2 architecture is used to detect three types of surface damage: (i) cracks; (ii) delamination; and (iii) rebar exposure. The detected damage is quantified by calculating the positions of the projected laser beams with the measured distance. The experimental results show that structural damage was detected with an F1 score of 0.83 and a median value of the quantified relative error of less than 5%.

Distance Measurements in UWB-Radio Localization Systems Corrected with a Feedforward Neural Network Model

An ultra-wideband (UWB) localization system is an alternative in a GPS-denied environment. However, a distance measurement with UWB modules using a two-way communication protocol induces an orientation-dependent error. Previous research studied this error by looking at parameters such as the received power and the channel response signal. In this paper, the neural network (NN) method for correcting the orientation-induced distance error without the need to calculate the signal strength, obtain the channel response or know any parameters of the antenna and the UWB modules is presented. The NN method utilizes only the measured distance and the tag orientation, and implements an NN model obtained by machine learning, using measurements at different distances and orientations of the two UWB modules. The verification of the experimental setup with 12 anchors and a tag shows that with the proposed NN method, 5 cm better root mean square error values (RMSEs) are obtained for the measured distance between the anchors and the tag compared to the calibration method that did not include orientation information. With the least-square estimator, 14 cm RMSE in 3D is obtained with the NN model corrected distances, with a 9 cm improvement compared to when raw distances are used. The method produces better results without the need to obtain the UWB module’s diagnostics parameters that are required to calculate the received signal strength or channel response, and in this way maintain the minimum packet size for the ranging protocol.

Sand and social distancing: A UAS study of Galveston, TX, beach attendance during COVID-19

As the COVID-19 pandemic spread in early 2020, Galveston, Texas, suspended beach access from 29 March 2020 through 1 May 2020. This action was designed to reduce the number of visitors to the island and to reduce nonsocially distanced interactions. After the 1 May 2020 reopening mandated by the Texas governor, numerous individuals, largely from the Houston area, drove to Galveston to use the beaches. At that time, TV coverage of the large crowds left the impression that there was little to no adherence to the reopening guidelines put forward by the state and city. In order to gauge the effectiveness/observance of the reopening guidelines by Galveston’s beachgoers, a headcount and analysis of the measured distance between individual beachgoers was completed on 23 May 2020 using Unmanned Aircraft Systems (UAS) photography and Geographic Information System (GIS) measurement techniques. By June, the number of positive COVID-19 cases was rapidly increasing in the Houston area. Despite minimal use of masks and little adherence to social distancing, there was sufficient space on the beach to handle the crowds provided beachgoers had adhered to social distancing guidelines. Two issues were identified: limited access points creating chokepoints when moving from the Seawall to the beach, and the pervasive use of shade devices (i.e. umbrellas, pop-up tents and canopies) that act as congregation spots.

Replicating Light-Off Startle Responses in Drosophila melanogaster

We present a highly reproducible method for investigating the startle flight responses of wild type Drosophila melanogaster to light-off stimuli, using the automated Zantiks MWP unit. The built-in, live video-tracking of the Zantiks unit measured distance travelled between frames for 24 flies after light-off stimuli, whilst providing video-recordings of each startle. Using light-off stimuli which elicited peak startling, we found evidence for habituation of the startle response after only a few consecutive trials. Distance travelled on startle trials was reduced when a prepulse stimulus of shorter duration was introduced before the light-off stimulus, providing behavioural evidence for prepulse inhibition (PPI). Deficits in habituation and PPI are linked to various psychiatric disorders and our method holds great potential for use alongside genetic and pharmacological manipulations. Here, we demonstrate the capability of this highly automated, high throughput technology to streamline behavioural research on Drosophila, using a replicable, controlled environment.