Development and evaluation of hand-held robotic technology for safe and successful peripheral intravenous catheterization on pediatric patients

Peripheral IntraVenous Catheterization (PIVC) is often required in hospitals to fulfil urgent needs of blood sampling or fluid/medication administration. Despite of the importance of a high success rate, the conventional PIVC operation suffers from low insertion accuracy especially on young pediatric patients. On average, each pediatric patient is submitted to 2.1 attempts before venous access is obtained, with around 50% failure for the first attempt. The risks of such multiple attempts can be severe and life-threatening as they can cause serious extravasation injuries. Given the levels of precision and controllability needed for PIVC, robotic systems show a good potential to effectively assist the operation and improve its success rate. Therefore, this study aims to provide such robotic assistance by focusing on the most challenging and error-prone parts of the operation. In order to understand the difficulties of a pediatric PIVC, a survey investigation is conducted with specialists at the beginning of this research. The feedbacks from this survey indicates an urgent need of a hand-held robot to assist in the catheter insertion control to precisely access the target vein. To achieve the above goal, a novel venipuncture detection system based on sensing the electrical impedance of the contacting tissue at the needle tip has been proposed and developed. Then several ex-vivo and in-vivo experiments were conducted to assess this detection system. Experimental results show that this system can be highly effective to detect venipuncture. Subsequently, based on this venipuncture detection system, four different handheld robots have been developed to provide different levels of autonomy and assistance while executing a PIVC insertion: 1. SVEI, short for \u2018Smart Venous Enter Indicator\u2019, is the simplest device without actuation. The user needs to do the whole PIVC operation, and this device only provides an indication of venipuncture by lighting up an LED. 5 2. SAID, short for \u2018Semi-Autonomous Intravenous access Device\u2019, integrates a motor to control the catheter insertion. The user is required to hold the device still and target it to a vein site. He/She then activates the device. The device inserts the catheter automatically and stops it when venipuncture is detected. 3. SDOP, short for \u2018Smart hand-held Device for Over-puncture Prevention\u2019, integrates a latch-based disengage mechanism to prevent over-puncture during PIVC. The user can keep the conventional way of operation and do the insertion manually. At the moment of venipuncture, the device automatically activates the disengage mechanism to stop further advancement of the catheter. 4. CathBot represents \u2018hand-held roBot for peripheral intravenous Catheterization\u2019. The device uses a crank-slider mechanism and a solenoid actuator to convert the complicated intravenous catheterization motion to a simple linear forward motion. The user just needs to push the device\u2019s handle forwards and the device completes the whole PIVC insertion procedure automatically. All the devices were characterized to ensure they can satisfy the design specifications. Then a series of comparative experiments were conducted to assess each of them. In the first experiment, 25 na\uefve subjects were invited to perform 10 trials of PIVC on a realistic baby arm phantom. The subjects were divided into 5 groups, and each group was asked to do the PIVC with one device only (SVEI, SAID, SDOP, CathBot and regular iv catheter). The experimental results show that all devices can provide the needed assistance to significantly facilitate and improve the success rates compared to the conventional method. People who have no experience of PIVC operation before can achieve considerably high success rates in robot-assisted PIVC (86% with SVEI, 80% with SAID, 78% with SDOP and 84% with CathBot) compared to the control group (12%) who used a regular iv catheter. Also, all 5 subjects using SVEI, 3 out of 5 subjects using SAID, 2 out of 5 subjects using SDOP and 4 out of 5 subjects using CathBot were able to successfully catheterize the baby arm phantom on their first attempt, while no subjects in the control group succeeded in their first attempts. Since SVEI showed the best results, it was selected for the second round of evaluation. In the second experiment, clinicians including both PIVC experts and general clinicians were invited to perform PIVC on a realistic baby arm phantom with 3 trials using SVEI and 3 trials in the conventional way. The results demonstrate that SVEI can bring great benefits to both specialists and general clinicians. The average success rates were found to be significantly improved from 48.3% to 71.7% when SVEI was used. The experimental results reveal that all experts achieved better or equal results with SVEI compared to the conventional method, and 9 out of 12 non-experts also had better or equal performance when SVEI was used. Finally, subjective feedback acquired through post-trial questionnaires showed that all devices were highly rated in terms of usability. Overall, the results of this doctoral research support continued investment in the technology to bring the handheld robotic devices closer to clinical us

Inter-comparison and evaluation of Arctic sea ice type products

oai:publications.copernicus.org:tc102910Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. However, systematic inter-comparison and analysis for SITY products are lacking. This study analysed eight daily SITY products from five retrieval approaches covering the winters of 1999–2019, including purely radiometer-based (C3S-SITY), scatterometer-based (KNMI-SITY and IFREMER-SITY) and combined ones (OSISAF-SITY and Zhang-SITY). These SITY products were inter-compared against a weekly sea ice age product (i.e. NSIDC-SIA – National Snow and Ice Data Center sea ice age) and evaluated with five synthetic aperture radar (SAR) images. The average Arctic multiyear ice (MYI) extent difference between the SITY products and NSIDC-SIA varies from -1.32×106 to 0.49×106 km2. Among them, KNMI-SITY and Zhang-SITY in the QuikSCAT (QSCAT) period (2002–2009) agree best with NSIDC-SIA and perform the best, with the smallest bias of -0.001×106 km2 in first-year ice (FYI) extent and -0.02×106 km2 in MYI extent. In the Advanced Scatterometer (ASCAT) period (2007–2019), KNMI-SITY tends to overestimate MYI (especially in early winter), whereas Zhang-SITY and IFREMER-SITY tend to underestimate MYI. C3S-SITY performs well in some early winter cases but exhibits large temporal variabilities like OSISAF-SITY. Factors that could impact performances of the SITY products are analysed and summarized. (1) The Ku-band scatterometer generally performs better than the C-band scatterometer for SITY discrimination, while the latter sometimes identifies FYI more accurately, especially when surface scattering dominates the backscatter signature. (2) A simple combination of scatterometer and radiometer data is not always beneficial without further rules of priority. (3) The representativeness of training data and efficiency of classification are crucial for SITY classification. Spatial and temporal variation in characteristic training datasets should be well accounted for in the SITY method. (4) Post-processing corrections play important roles and should be considered with caution.</p

Resolving Fine-Scale Surface Features on Polar Sea Ice: A First Assessment of UAS Photogrammetry Without Ground Control

Mapping landfast sea ice at a fine spatial scale is not only meaningful for geophysical study, but is also of benefit for providing information about human activities upon it. The combination of unmanned aerial systems (UAS) with structure from motion (SfM) methods have already revolutionized the current close-range Earth observation paradigm. To test their feasibility in characterizing the properties and dynamics of fast ice, three flights were carried out in the 2016–2017 austral summer during the 33rd Chinese National Antarctic Expedition (CHINARE), focusing on the area of the Prydz Bay in East Antarctica. Three-dimensional models and orthomosaics from three sorties were constructed from a total of 205 photos using Agisoft PhotoScan software. Logistical challenges presented by the terrain precluded the deployment of a dedicated ground control network; however, it was still possible to indirectly assess the performance of the photogrammetric products through an analysis of the statistics of the matching network, bundle adjustment, and Monte-Carlo simulation. Our results show that the matching networks are quite strong, given a sufficient number of feature points (mostly > 20,000) or valid matches (mostly > 1000). The largest contribution to the total error using our direct georeferencing approach is attributed to inaccuracies in the onboard position and orientation system (POS) records, especially in the vehicle height and yaw angle. On one hand, the 3D precision map reveals that planimetric precision is usually about one-third of the vertical estimate (typically 20 cm in the network centre). On the other hand, shape-only errors account for less than 5% for the X and Y dimensions and 20% for the Z dimension. To further illustrate the UAS’s capability, six representative surface features are selected and interpreted by sea ice experts. Finally, we offer pragmatic suggestions and guidelines for planning future UAS-SfM surveys without the use of ground control. The work represents a pioneering attempt to comprehensively assess UAS-SfM survey capability in fast ice environments, and could serve as a reference for future improvements

Prevalence of A2143G mutation of H. pylori-23S rRNA in Chinese subjects with and without clarithromycin use history

<p>Abstract</p> <p>Background</p> <p>A2143G mutation of <it>23S rRNA </it>gene of <it>H. pylori </it>results in clarithromycin (CLR) resistance. To investigate the prevalence of the CLR resistance-related A2143G mutation of the <it>H. pylori</it>-specific <it>23S rRNA </it>gene in Chinese subjects with and without CLR use history, 307 subjects received the treatment with amoxicillin and omeprazole (OA) and 310 subjects received a placebo in 1995, and 153 subjects received a triple therapy with OA and CLR (OAC) in 2000. DNA was extracted from fasting gastric juice at the end of the intervention trial in 2003. <it>H. pylori </it>infection was determined by <it>H. pylori</it>-specific <it>23S rRNA </it>PCR, ELISA, and¹³C-urea breath test assays. Mutations of the <it>23S rRNA </it>gene were detected by RFLP assays.</p> <p>Results</p> <p>The presence of <it>23S rRNA </it>due to <it>H. pylori </it>infection in the OA group remained lower than that in the placebo group 7.3 yrs after OA-therapy [51.1% (157/307) vs. 83.9% (260/310), p = 0.0000]. In the OAC group, the <it>23S rRNA </it>detection rate was 26.8% (41/153) three yrs after OAC-treatment. The A2143G mutation rate among the <it>23S rRNA</it>-positive subjects in the OAC group [31.7% (13/41)] was significantly higher than that in the OA group [10.2% (16/157)] and the placebo group [13.8% (36/260)]. The frequency of the AAGGG → CTTCA (2222–2226) and AACC → GAAG (2081–2084) sequence alterations in the OAC group was also significantly higher than those in the OA group and the placebo group.</p> <p>Conclusion</p> <p>Primary prevalence of the A2143G mutation was 10~14% among Chinese population without history of CLR therapy. Administration of CLR to eliminate <it>H. pylori </it>infection increased the prevalence of the A2143G mutation in Chinese subjects (32%) significantly.</p

Robot-Assisted Electrical Impedance Scanning system for 2D Electrical Impedance Tomography tissue inspection

The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant clinical benefits. Nevertheless, most EIT technologies are based on a fixed multiple-electrodes probe which limits the sensing flexibility and capability significantly. In this study, we present a method for acquiring the EIT measurements during a RAMIS procedure using two already existing robotic forceps as electrodes. The robot controls the forceps tips to a series of predefined positions for injecting excitation current and measuring electric potentials. Given the relative positions of electrodes and the measured electric potentials, the spatial distribution of electrical conductivity in a section view can be reconstructed. Realistic experiments are designed and conducted to simulate two tasks: subsurface abnormal tissue detection and surgical margin localization. According to the reconstructed images, the system is demonstrated to display the location of the abnormal tissue and the contrast of the tissues' conductivity with an accuracy suitable for clinical applications

Robot Assisted Electrical Impedance Tomography System for Minimally Invasive Surgery

This study presents the development of a robot assisted electrical impedance scanning system able to reconstruct Electrical Impedance Tomography (EIT) during surgical inspection. This system can be directly applied on most existing minimally invasive surgical robots without introducing additional sensor probes to the operating site or modifying the existing surgical tools. By positioning two robotic forceps as electrodes to several positions on the tissue surface and performing electrical measurements, the system is able to obtain electrical information and use them for reconstructing the conductivity distribution using the EIT algorithm. This paper describes the system construction, sensing pattern and reconstruction algorithm in detail. In addition, the developed system is optimized using finite element simulation and evaluated through two realistic experiments. The generated EIT images are able to show the location of the non-homogeneous structure from the surrounding tissue effectively. These results demonstrate the great potential of the proposed system to assist surgeons in detecting subsurface target area of interest

Monitoring ice flow velocity of Petermann glacier combined with Sentinel-1 and −2 imagery

Synthetic Aperture Radar (SAR) images are commonly used to monitor glacier flow velocity at Greenland Ice Sheet (GrIS). However, offset-tracking with SAR imagery in summer usually show poor quality because the rapid ice surface freezing-melting cycles contaminating the surface backscattering characteristic, while optical images are less sensitive to this phenomenon. In this study, we combine Sentinel-1 and -2 images to create the glacier velocity time series for the Petermann glacier, located in the northern GrIS. Firstly, the offset-tracking technique is employed to acquire the initial deformation fields with SAR and optical sensors separately, each SAR and/or optical acquisition is tracked with its closest next three acquisitions. Next, after removing the bad matchings, the least squares method based on connected components is employed to calculate the time series of glacier velocity for Sentinel-1 and −2, separately. Finally, these two kinds of derived time series are integrated with a weighted least squares method, where weights are evaluated according to the estimated RMSEs in the last step. Error propagation analysis suggests RMSEs of the single pair of Sentinel-1 and −2 images offset-tracking are ∼ 0.22 m and ∼ 2.5 m for Petermann glaciers. Standard deviation of the difference between Sentinel-1 and Sentinel-2 measured velocity are ∼ 0.25 m/day. Compared with 6-day velocity fields product, NSIDC (National Snow and Ice Data Center) −0766, which is only derived with Sentinel-1observations, our results show good agreement and less defects in summer. The differences are ∼ 0.20 m/day in non-melting seasons and ∼ 0.34 m/day in summer. Longitudinal velocity differences growing in 2019 and 2020 at ∼ 20 Km up to the terminus are consistency with the crevasse expansion, indicating another calving event is approaching. This research finds that the fusion of Sentinel-1 and −2 offset-tracking results improves the completeness of the ice movement time series for polar glaciers

Incidence Angle Normalization of Dual-Polarized Sentinel-1 Backscatter Data on Greenland Ice Sheet

The backscatter coefficients of Synthetic Aperture Radar (SAR) images that observe the Greenland Ice Sheet (GrIS) are incidence angle dependent, which impedes subsequent applications, such as monitoring its surface melting. Therefore, backscatter intensities with varying incidence angles should be normalized. This study proposes an incidence angle normalization method for dual-polarized Sentinel-1 images for GrIS. A multiple linear regression model is trained using the ratio between the backscatter coefficient differences and the incidence angle differences of quasi-simultaneously observed ascending and descending image pairs. Regression factors include the geographical position and elevation. The precision evaluation to the ascending and descending images suggests better normalization results than the widely used cosine-square correction method for horizontal transmit and horizontal receive (HH) images and a slight improvement for horizontal transmit and vertical receive (HV) images. Another dataset of GrIS Sentinel-1 mosaics in four 6-day repeating periods in 2020 is also tested to evaluate the proposed method and yields similar results. For HH images, the proposed method performs better than the cosine-square method, reducing 0.34 dB RMSE on average. The overall accuracy of our proposed method is 0.77 and 0.75 dB for HH and HV images, respectively. The proposed incidence angle normalization method can benefit the application of wide-swath SAR images to the study of large-scale and long-period observation on GrIS

Antarctic Surface Ice Velocity Retrieval from MODIS-Based Mosaic of Antarctica (MOA)

The velocity of ice flow in the Antarctic is a crucial factor to determine ice discharge and thus future sea level rise. Feature tracking has been widely used in optical and radar imagery with fine resolution to retrieve flow parameters, although the primitive result may be contaminated by noise. In this paper, we present a series of modified post-processing steps, such as SNR thresholding by residual, complex Butterworth filters, and triple standard deviation truncation, to improve the performance of primitive results, and apply it to MODIS-based Mosaic of Antarctica (MOA) datasets. The final velocity field result displays the general flow pattern of the peripheral Antarctic. Seventy-eight out of 97 streamlines starting from seed points are smooth and continuous. The RMSE with 178 manually selected tie points is within 60 m&middot;a&minus;1. The systematic comparison with Making Earth System Data Records for Use in Research Environments (MEaSUREs) datasets in seven drainages shows that the results regarding high magnitude and large-scale ice shelf are highly reliable; absolute mean and median difference are less than 18 m&middot;a&minus;1, while the result of localized drainage suffered from too much tracking error. The relative differences from manually selected and random points are controlled within 8% when speed is beyond 500 m&middot;a&minus;1, but bias and uncertainty are pronounced when speed is lower than that. The result through our accuracy control strategy highlights that coarse remote-sensed images such as Moderate Resolution Imaging Spectrophotometer (MODIS) can still offer the capability for comprehensive and long-term continental ice sheet surface velocity mapping