Improving Telemetry use in the Acute Assessment Unit.

BACKGROUND AND AIMS: Despite published guidelines, telemetry use is inappropriate in 25-43% of cases. This impacts patient safety and telemetry effectiveness. QI methodology was used to review telemetry in a hospital acute medical unit with the aim of reducing inappropriate use and addressing alarm fatigue. METHODS: A 'Telemetry Indication Form' was created. Eight weeks of baseline data was collated before introducing the 'Indication Form'. Four plan-do-study-act cycles were conducted. At each cycle, data was analysed using statistical process control charts. RESULTS: Inappropriate telemetry use significantly reduced from 32% to 4%. Total telemetry use also fell. Unfortunately, interventions to address alarm rates did not result in significant reduction in false alarms. CONCLUSIONS: A 'Telemetry Indication Form' has significant potential to improve patient safety through reducing inappropriate use.

Attention 3D central difference convolutional dense network for hyperspectral image classification.

Hyperspectral Images (HSI) classification is a challenging task due to a large number of spatial-spectral bands of images with high inter-similarity, extra variability classes, and complex region relationships, including overlapping and nested regions. Classification becomes a complex problem in remote sensing images like HSIs. Convolutional Neural Networks (CNNs) have gained popularity in addressing this challenge by focusing on HSI data classification. However, the performance of 2D-CNN methods heavily relies on spatial information, while 3D-CNN methods offer an alternative approach by considering both spectral and spatial information. Nonetheless, the computational complexity of 3D-CNN methods increases significantly due to the large capacity size and spectral dimensions. These methods also face difficulties in manipulating information from local intrinsic detailed patterns of feature maps and low-rank frequency feature tuning. To overcome these challenges and improve HSI classification performance, we propose an innovative approach called the Attention 3D Central Difference Convolutional Dense Network (3D-CDC Attention DenseNet). Our 3D-CDC method leverages the manipulation of local intrinsic detailed patterns in the spatial-spectral features maps, utilizing pixel-wise concatenation and spatial attention mechanism within a dense strategy to incorporate low-rank frequency features and guide the feature tuning. Experimental results on benchmark datasets such as Pavia University, Houston 2018, and Indian Pines demonstrate the superiority of our method compared to other HSI classification methods, including state-of-the-art techniques. The proposed method achieved 97.93% overall accuracy on the Houston-2018, 99.89% on Pavia University, and 99.38% on the Indian Pines dataset with the 25 × 25 window size.

A systematic review of the use of in-vehicle telematics in monitoring driving behaviours.

BACKGROUND: Road traffic deaths are increasing globally, and preventable driving behaviours are a significant cause of these deaths. In-vehicle telematics has been seen as technology that can improve driving behaviour. The technology has been adopted by many insurance companies to track the behaviours of their consumers. This systematic review presents a summary of the ways that in-vehicle telematics has been modelled and analysed. METHODOLOGY: Electronic searches were conducted on Scopus and Web of Science. Studies were only included if they had a sample size of 10 or more participants, collected their data over at least multiple days, and were published during or after 2010. 45 relevant papers were included in the review. 27 of these articles received a rating of "good" in the quality assessment. RESULTS: We found a divide in the literature regarding the use of in-vehicle telematics. Some articles were interested in the utility of in-vehicle telematics for insurance purposes, while others were interested in determining the influence that in-vehicle telematics has on driving behaviour. Machine learning analyses were the most common forms of analysis seen throughout the review, being especially common in articles with insurance-based outcomes. Acceleration, braking, and speed were the most common variables identified in the review. CONCLUSION: We recommend that future studies provide the demographical information of their sample so that the influence of in-vehicle telematics on the driving behaviours of different groups can be understood. It is also recommended that future studies use multi-level models to account for the hierarchical structure of the telematics data. This hierarchical structure refers to the individual trips for each driver.

STIRUnet: SwinTransformer and inverted residual convolution embedding in unet for Sea-Land segmentation.

Extraction of coastline from optical remote sensing images is of paramount importance for coastal zone management, erosion monitoring, and intelligent ocean construction. However, nearshore marine environment complexity presents a challenge when capturing small-scale and detailed information regarding coastlines. Furthermore, the presence of numerous tidal flats, suspended sediments, and coastal biological communities exacerbates the reduction in segmentation accuracy, which is particularly noticeable in medium-high-resolution remote sensing image segmentation tasks. Most previous related studies, based primarily on convolutional neural networks (CNNs) or traditional feature extraction methods, faced challenges in detailed pixel-level refinement and lacked comprehensive understanding of the studied images. Therefore, we proposed a new U-shaped deep learning model (STIRUnet) that combines the excellent global modeling ability of SwinTransformer with an improved CNN using an inverted residual module. The proposed method has the capability of global supervised feature learning and layer-by-layer feature extraction, and we conducted sea-land segmentation experiments using GF-HNCD and BSD remote sensing image datasets to validate the performance of the proposed model. The results indicate the following: 1) suspended sediments and coastal biological communities are major contributors to coastline blurring, and 2) the recovery of minute features (e.g., narrow watercourses and microscale artificial structures) effectively enhances edge details and leads to more realistic segmentation outcomes. The findings of this study are highly important in relation of accurate extraction of sea-land information in complex marine environments, and they offer novel insights regarding mixed-pixel identification.

Troubleshooting Cochlear Implant Malfunction Using Neural Response Telemetry and Normal Saline.

Cochlear implantation has become a standard of care for a child diagnosed with bilateral profound sensorineural hearing loss with a structured surgical standard operating procedure. A 3-year-old boy with bilateral profound prelingual sensorineural deafness underwent a Med-EL Sonata Ti100 implant. We faced a peculiar situation intraoperatively after inserting the electrodes and closing the wound. The impedance recording indicated high ground path impedance with short-circuiting of few electrodes. As a bionic implant, its electronic components may at times malfunction both intraoperatively and/or postoperatively; therefore, neural response telemetry (NRT) was invented to check it. By using NRT and a few milliliters of normal saline, we were able to diagnose as well as rectify the malfunctioning of the implant.

[Options for home telemonitoring in heart failure patients]. / Opties voor thuismonitoring bij patiënten met hartfalen.

OBJECTIVE: To provide an overview of the effectiveness of various forms of home telemonitoring systems for heart failure and the potential role these systems may have in decreasing the burden on healthcare through reduction in heart failure hospitalizations. DESIGN: Meta-analysis of randomized and observational studies. METHODS: A meta-analysis of randomized and observational studies was carried out to assess the effect on mortality and heart failure-related hospitalizations, comparing standard heart failure care with the use of home monitoring systems. RESULTS: The pooled results from 92 studies demonstrate a reduction in the risk of both mortality and heart failure admissions. CONCLUSION: The results of this meta-analysis support the use of home telemonitoring systems. Determining which form of home telemonitoring is most suitable for which patient requires further research.

Deeply Implanted Conformal Antenna for Real-Time Bio-Telemetry Applications.

The design and experimental verification of a deeply implanted conformal printed antenna is presented. The hip implant acts as the ground plane for a coaxial-cable-fed trapezoidal radiator designed to transmit biological signals collected within the body by proper biosensors. The arrangement, consisting of a metallic (or equivalent) hip implant, bio-compatible gypsum-based dielectric, and conformal radiator, was tested when the hosting 3D-printed plastic bone was immersed in tissue-like liquid contained in a plastic bucket. The dimensions of the set-up are similar to a human leg. Matching and radiation characteristics are presented in the industrial, scientific, and medical (ISM) frequency band (2.4-2.5 GHz), showing the feasibility of the proposed arrangement.

Variación de la impedancia eléctrica a lo largo de cinco años postimplantación y relación con el umbral de confort máximo (MCL) en adultos portadores de implante coclear / Variation of electrical impedance over 5 years post-implantation and relationship with the maximum comfort level (MCL) in adults with cochlear implants

Introducción El umbral de confort máximo o maximum comfort level (MCL), umbral eléctrico o threshold level (THR) e impedancia eléctrica cambian en el postoperatorio del implante coclear durante meses hasta estabilizarse. El objetivo de este artículo es establecer la variación durante cinco años posquirúrgicos de la impedancia, y su relación con MCL en adultos implantados unilateralmente. Métodos Estudio retrospectivo a cinco años, con 78 pacientes adultos implantados con MED-EL en un hospital terciario desde el año 2000 hasta 2015. Se analizó la variación de impedancia, MCL y relación entre ellos, en electrodos basales (9-12), medios (5-8) y apicales (1-4), realizando análisis inferencial ANOVA de medidas repetidas con comparaciones entre tiempos consecutivos, corregidas con criterio Bonferroni. Resultados Treinta y tres hombres (42,3%) y 45 mujeres (57,7%), con edad media 52,7 ± 14,6 años. Se consideró «estabilidad» el momento del seguimiento sin diferencias estadísticamente significativas entre una visita y la siguiente. Los cambios en la impedancia en electrodos medios dejaron de ser estadísticamente significativos a los tres meses, y en apicales a los seis meses, con valores medios de 5,84 y 6,43 kohms. MCL se estabilizó a los dos años en electrodos basales y apicales, y a los tres años en medios, con valores medios de 24,9, 22,7 y 25,6 qu. Hubo correlación entre MCL e impedancia en electrodos medios hasta 3 meses y en apicales hasta un año. Conclusiones La impedancia eléctrica desciende significativamente en electrodos medios y apicales hasta tres y seis meses. El MCL aumenta significativamente hasta dos años. La impedancia se relaciona con MCL hasta seis meses. (AU)

Introduction The maximum comfort level (MCL), threshold level (THR) and electrical impedance change in the postoperative period of the cochlear implant for months until they stabilize. The objective of this article is to establish the variation during 5 post-surgical years of impedance, and its relationship with MCL in unilaterally implanted adults. Methods Retrospective study over 5 years, with 78 adult patients implanted with MED-EL in a tertiary hospital from the year 2000 to 2015. The variation in impedance, MCL and the relationship between them were analyzed in basal (9-12), medial (5-8) and apical electrodes (1-4), performing an inferential ANOVA analysis of repeated measures with comparisons between consecutive times, corrected with Bonferroni criteria. Results 33 men (42.3%) and 45 women (57.7%), with a mean age of 52.7 ± 14.6 years. “Stability” was considered the time of follow-up without statistically significant differences between one visit and the next. Changes in impedance in medial electrodes ceased to be statistically significant at 3 months, and in apicals at 6 months, with mean values of 5.84 and 6.43 kohms. MCL stabilized at 2 years in basal and apical electrodes, and at 3 years in medial, with mean values of 24.9, 22.7, and 25.6 qu. There was a correlation between MCL and impedance in medium electrodes up to 3 months and in apical ones up to one year. Conclusions Electrical impedance drops significantly in medial and apical electrodes up to 3 and 6 months. MCL increases significantly up to two years. Impedance is related to MCL up to 6 months. (AU)

Telemetry-Based Haptic Rendering for Racing Game Experience Improvement.

Many recent games, such as racing and flight games, open their game telemetry data to users by storing them in the local memory. Such telemetry data can provide useful information for haptic rendering, and this advantage has been exploited by the industry. This approach applies to any applications that export telemetry data in run time. The haptic rendering module operates as a separate process that accesses the telemetry data in parallel with the application. It is simple, efficient, and modular while retaining the application intact. We examine the approach's viability for user experience improvement by developing three telemetry-based haptic rendering algorithms for car racing games. They express the car engine response, collisions with external objects, and the road surface texture, respectively. Building a haptics-enabled driving platform, we conducted a user study comparing gaming experiences between our telemetry-based algorithms and conventional sound-to-tactile conversion algorithms. The results showed that the telemetry-based effects elicited better experiences than the sound-based effects.

Remote Multi-Person Heart Rate Monitoring with Smart Speakers: Overcoming Separation Constraint.

Heart rate is a key vital sign that can be used to understand an individual's health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present an approach that can minimize interference and thereby enable simultaneous heart rate monitoring of multiple individuals in close proximity using a commonly available smart speaker prototype. Our user study, conducted under various real-life scenarios, demonstrates the system's accuracy in sensing two users' heart rates when they are seated next to each other with a median error of 0.66 beats per minute (bpm). Moreover, the system can successfully monitor up to four people in close proximity.

TrackdAT, an acoustic telemetry metadata dataset to support aquatic animal tracking research.

Data on the movement and space use of aquatic animals are crucial to understand complex interactions among biotic and abiotic components of ecosystems and facilitate effective conservation and management. Acoustic telemetry (AT) is a leading method for studying the movement ecology of aquatic animals worldwide, yet the ability to efficiently access study information from AT research is currently lacking, limiting advancements in its application. Here, we describe TrackdAT, an open-source metadata dataset where AT research parameters are catalogued to provide scientists, managers, and other stakeholders with the ability to efficiently identify and evaluate existing peer-reviewed research. Extracted metadata encompasses key information about biological and technical aspects of research, providing a comprehensive summary of existing AT research. TrackdAT currently hosts information from 2,412 journal articles published from 1969 to 2022 spanning 614 species and 380,289 tagged animals. TrackdAT has the potential to enable regional and global mobilization of knowledge, increased opportunities for collaboration, greater stakeholder engagement, and optimization of future ecological research.

Road extraction through Yangwang-1 nighttime light data: A case study in Wenzhou, China.

The extraction of roadways from remote sensing imagery constitutes a pivotal task, with far-reaching implications across diverse domains such as urban planning, management of transportation systems, emergency response initiatives, and environmental monitoring endeavors. Satellite images captured during daytime have customarily served as the primary resource for this extraction process. However, the emergence of Nighttime Light (NTL) remote sensing data introduces an innovative dimension to this arena. The exploration of NTL data for road extraction remains in its nascent stage, and this study seeks to bridge this gap. We present a refined U-Net model (CA U-Net) integrated with Cross-Attention Mechanisms, meticulously designed to extract roads from Yangwang-1 NTL images. This model incorporates several enhancements, thereby improving its proficiency in identifying and delineating road networks. Through extensive experimentation conducted in the urban landscape of Wenzhou City, the model delivers highly accurate results, achieving an F1 score of 84.46%. These outcomes significantly surpass the performance benchmarks set by Support Vector Machines (SVM) and the Optimal Threshold (OT) method. This promising development paves the way towards maximizing the utility of NTL data for comprehensive mapping and analysis of road networks. Furthermore, the findings underscore the potential of utilizing Yangwang-1 data as a reliable source for road extraction and reaffirm the viability of deploying deep learning frameworks for road extraction tasks utilizing NTL data.

Temperate grassland vegetation restoration influenced by grazing exclusion and climate change.

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003-0.0319 year-1. The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration.

Characterization of intraocular pressure variability in conscious rats.

Elevation of mean intraocular pressure (IOP) has long been recognized as a leading risk factor for glaucoma. Less is known about the possible contribution of moment-to-moment variations in IOP to disease development and progression due to limitations of tonometry, the prevailing method of IOP measurement. Tonometry provides good estimates of mean IOP but not IOP variance. The aim of this study was to quantitatively characterize IOP variability via round-the-clock IOP telemetry in conscious unrestrained rats. The anterior chamber of one eye was implanted with a microcannula connected to a wireless backpack telemetry system, and IOP data were collected every 4 s for one week. The cannula was then repositioned under the conjunctiva, and control data were collected for an additional week. IOP statistics were computed in 30-min intervals over a 24-h period and averaged across days. All animals exhibited a diurnal variation in mean IOP, while deviations about the mean were independent of time of day. Correlation analysis of the deviations revealed transient and sustained components, which were respectively extracted from IOP records using an event detection algorithm. The amplitude and interval distributions of transient and sustained events were characterized, and their energy content was estimated based on outflow tissue resistance of rat eyes. Transient IOP events occurred ∼231 times per day and were typically ≤5 mmHg in amplitude and 2-8 min in duration, while sustained IOP events occurred ∼16 times per day and were typically ≤5 mmHg in amplitude and 20-60 min in duration. Both persisted but were greatly reduced in control recordings, implying minor contamination of IOP data by motion-induced telemetry noise. Sustained events were also often synchronous across implanted animals, indicating that they were driven by autonomic startle and stress responses or other physiological processes activated by sensory signals in the animal housing environment. Not surprisingly, the total daily fluidic energy applied to resistive outflow pathways was determined primarily by basal IOP level. Nevertheless, transient and sustained fluctuations collectively contributed 6% and diurnal fluctuations contributed 9% to daily IOP energy. It is therefore important to consider the cumulative impact of biomechanical stress that IOP fluctuations apply over time to ocular tissues.

Artificial light at night is a top predictor of bird migration stopover density.

As billions of nocturnal avian migrants traverse North America, twice a year they must contend with landscape changes driven by natural and anthropogenic forces, including the rapid growth of the artificial glow of the night sky. While airspaces facilitate migrant passage, terrestrial landscapes serve as essential areas to restore energy reserves and often act as refugia-making it critical to holistically identify stopover locations and understand drivers of use. Here, we leverage over 10 million remote sensing observations to develop seasonal contiguous United States layers of bird migrant stopover density. In over 70% of our models, we identify skyglow as a highly influential and consistently positive predictor of bird migration stopover density across the United States. This finding points to the potential of an expanding threat to avian migrants: peri-urban illuminated areas may act as ecological traps at macroscales that increase the mortality of birds during migration.

Don't worry, be happy: Habitat selection of Blanding's Turtles (Emydoidea blandingii) living in a reference condition in Georgian Bay.

Few areas within the Great Lakes basin are currently free from impact of human activities, and it is important to study these reference conditions for comparison with degraded sites in those regions. Here, we use radio telemetry to investigate habitat use, movement, and habitat selection of a population of the endangered (Federally in Canada) Blanding's turtle (Emydoidea blandingii, BLTU) inhabiting a mostly undisturbed archipelago located at the northern shore of Mnidoo gamii (Georgian Bay), Ontario over two active seasons (May to September 2021 and 2022). We found a mean home range of 16.21 ha for females (n = 7) and 15.10 ha for males (n = 7). Of the five habitat classes (Marsh, Open Water, Rock, Peatland, and Forest), females used all except Peatland during the nesting season, and both sexes used all five habitat classes throughout both active seasons in 2021 and 2022. Disproportionate habitat use was detected at the landscape scale but not at the home range scale which was consistent with the hypothesis that adult Blanding's turtles residing in relatively undisturbed sites with abundant habitat types use all habitat types according to their availability. We also observed the use of open, deep water by Blanding's Turtles as travel corridors for nesting and mating. Effective future conservation strategies should prioritize the protection and connectivity of relatively undisturbed wetlands, forests, and rock barrens in this region and use this study as a reference condition to compare BLTU habitat use and movement across disturbance gradients within Georgian Bay.