Design, modeling and control of a minimally invasive surgical platform

Minimally invasive single-site surgery has been shown to reduce the invasiveness of surgery by requiring only one incision to access the abdominal cavity. However, this technique presents the surgeon with unique challenges and requires the development of new robotic platforms and surgical tools. To address these challenges, a 20 mm trocar is designed to guide the serial insertion and assembly of three individual 3D printed, 8 mm, 5+1 degree-of-freedom (DOF) manipulator tools and a standard 8 mm laparoscopic camera through a single port. Each dexterous manipulator is remotely driven by 12 actuation tendons and is composed of rigid links joined by hybrid flexure hinges. For ensuring large transition of the vision scope, a holding frame of the trocar is introduced. The holding frame consists 3 degree-of-freedom (DOF) rotating which enable a pivot point where the incision goes through, and one additional DOF that controls the incision depth. Haptic devices are applied for translating the dexterity of the human arm to both the internal operating field and the external positioning frame

GABNet: global attention block for retinal OCT disease classification

IntroductionThe retina represents a critical ocular structure. Of the various ophthalmic afflictions, retinal pathologies have garnered considerable scientific interest, owing to their elevated prevalence and propensity to induce blindness. Among clinical evaluation techniques employed in ophthalmology, optical coherence tomography (OCT) is the most commonly utilized, as it permits non-invasive, rapid acquisition of high-resolution, cross-sectional images of the retina. Timely detection and intervention can significantly abate the risk of blindness and effectively mitigate the national incidence rate of visual impairments.MethodsThis study introduces a novel, efficient global attention block (GAB) for feed forward convolutional neural networks (CNNs). The GAB generates an attention map along three dimensions (height, width, and channel) for any intermediate feature map, which it then uses to compute adaptive feature weights by multiplying it with the input feature map. This GAB is a versatile module that can seamlessly integrate with any CNN, significantly improving its classification performance. Based on the GAB, we propose a lightweight classification network model, GABNet, which we develop on a UCSD general retinal OCT dataset comprising 108,312 OCT images from 4686 patients, including choroidal neovascularization (CNV), diabetic macular edema (DME), drusen, and normal cases.ResultsNotably, our approach improves the classification accuracy by 3.7% over the EfficientNetV2B3 network model. We further employ gradient-weighted class activation mapping (Grad-CAM) to highlight regions of interest on retinal OCT images for each class, enabling doctors to easily interpret model predictions and improve their efficiency in evaluating relevant models.DiscussionWith the increasing use and application of OCT technology in the clinical diagnosis of retinal images, our approach offers an additional diagnostic tool to enhance the diagnostic efficiency of clinical OCT retinal images

Low-Cost UVBot Using SLAM to Mitigate the Spread of Noroviruses in Occupational Spaces

Noroviruses (NoVs) cause over 90% of non-bacterial gastroenteritis outbreaks in adults and children in developed countries. Therefore, there is a need for approaches to mitigate the transmission of noroviruses in workplaces to reduce their substantial health burden. We developed and validated a low-cost, autonomous robot called the UVBot to disinfect occupational spaces using ultraviolet (UV) lamps. The total cost of the UVBOT is less than USD 1000, which is much lower than existing commercial robots that cost as much as USD 35,000. The user-friendly desktop application allows users to control the robot remotely, check the disinfection map, and add virtual walls to the map. A 2D LiDAR and a simultaneous localization and mapping (SLAM) algorithm was used to generate a map of the space being disinfected. Tulane virus (TV), a human norovirus surrogate, was used to validate the UVBot’s effectiveness. TV was deposited on a painted drywall and exposed to UV radiation at different doses. A 3-log (99.9%) reduction of TV infectivity was achieved at a UV dose of 45 mJ/cm2. We further calculated the sanitizing speed as 3.5 cm/s and the efficient sanitizing distance reached up to 40 cm from the UV bulb. The design, software, and environment test data are available to the public so that any organization with minimal engineering capabilities can reproduce the UVBot system