Development of an Intuitive Interface with Haptic Enhancement for Robot-Assisted Endovascular Intervention.

Robot-assisted endovascular intervention has the potential to reduce radiation exposure to surgeons and enhance outcomes of interventions. However, the success and safety of endovascular interventions depend on surgeons' ability to accurately manipulate endovascular tools such as guidewire and catheter and perceive their safety when cannulating patient's vessels. Currently, the existing interventional robots lack a haptic system for accurate force feedback that surgeons can rely on.

Endovascular Tool Segmentation with Multi-lateral Branched Network during Robot-assisted Catheterization.

Robot-assisted catheterization is routinely carried out for intervention of cardiovascular diseases. Meanwhile, the success of endovascular tool navigation depends on visualization and tracking cues available in the robotic platform. Currently, real-time motion analytics are lacking, while poor illumination during fluoroscopy affects existing physics- and learning-based methods used for tool segmentation.

Guidewire Endpoint Detection Based on Pixel Adjacent Relation in Robot-assisted Cardiovascular Interventions.

Visualization of endovascular tools like guidewire and catheter is essential for procedural success of endovascular interventions. This requires tracking the tool pixels and motion during catheterization; however, detecting the endpoints of the endovascular tools is challenging due to their small size, thin appearance, and flexibility. As this still limit the performances of existing methods used for endovascular tool segmentation, predicting correct object location could provide ways forward.

Noninvasive Blood Glucose Monitoring Using Spatiotemporal ECG and PPG Feature Fusion and Weight-Based Choquet Integral Multimodel Approach.

change of blood glucose (BG) level stimulates the autonomic nervous system leading to variation in both human's electrocardiogram (ECG) and photoplethysmogram (PPG). In this article, we aimed to construct a novel multimodal framework based on ECG and PPG signal fusion to establish a universal BG monitoring model. This is proposed as a spatiotemporal decision fusion strategy that uses weight-based Choquet integral for BG monitoring.

Kinematics Constraint Modeling for Flexible Robots based on Deep Learning.

Application of flexible robotic systems and teleoperated control recently used in minimally invasive surgery have introduced paradigm shift in interventional surgery. While Prototypes of flexible robots have been proposed for surgical diagnostic and treatments, precise constraint control models are still needed for flexible pathway navigation. In this paper, a deep learning based kinematics model is proposed for motion control of flexible robots.

Automatic tool segmentation and tracking during robotic intravascular catheterization for cardiac interventions.

Background: Cardiovascular diseases resulting from aneurism, thrombosis, and atherosclerosis in the cardiovascular system are major causes of global mortality. Recent treatment methods have been based on catheterization of flexible endovascular tools with imaging guidance. While advances in robotic intravascular catheterization have led to modeling tool navigation approaches with data sensing and feedback, proper adaptation of image-based guidance for robotic navigation requires the development of sensitive segmentation and tracking models without specificity loss.

High-Resolution and High-Sensitivity Flexible Capacitive Pressure Sensors Enhanced by a Transferable Electrode Array and a Micropillar-PVDF Film.

Flexible pressure sensors have attracted increasing attention because they can mimic human skin to sense external pressure; however, for mimicking human skin, the sensing of a pressure point is far from sufficient. To realize fully biomimetic skins, it is crucial for flexible sensors to have high resolution and high sensitivity. We conducted simulations and experiments to determine the relationship between the sensor sensitivity and physical parameters, such as the effective relative permittivity and air ratio of the dielectric layer.

Printable, Highly Sensitive Flexible Temperature Sensors for Human Body Temperature Monitoring: A Review.

In recent years, the development and research of flexible sensors have gradually deepened, and the performance of wearable, flexible devices for monitoring body temperature has also improved. For the human body, body temperature changes reflect much information about human health, and abnormal body temperature changes usually indicate poor health. Although body temperature is independent of the environment, the body surface temperature is easily affected by the surrounding environment, bringing challenges to body temperature monitoring equipment.

Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems.

Success of the da Vinci surgical robot in the last decade has motivated the development of flexible access robots to assist clinical experts during single-port interventions of core intrabody organs. Prototypes of flexible robots have been proposed to enhance surgical tasks, such as suturing, tumor resection, and radiosurgery in human abdominal areas; nonetheless, precise constraint control models are still needed for flexible pathway navigation. In this paper, the design of a flexible snake-like robot is presented, along with the constraints model that was proposed for kinematics and dynamics control, motion trajectory planning, and obstacle avoidance during motion.

Learning-based Parameter Estimation for Hysteresis Modeling in Robotic Catheterization.

In the last half decade, nearly 31% of annual global deaths are linked to cardiovascular diseases. Thus, robotic catheterizations are recently proposed for interventions of conditions such as aneurism or atherosclerosis formed along vascular paths leading to the heart. However, existence of mild to strong hysteresis while navigating unactuated catheters with the current robotic systems inhibits autonomous control for vascular surgery.

Signal Quality and Electrode-Skin Impedance Evaluation in the Context of Wearable Electroencephalographic Systems.

Recent advancement in technology has brought about increase in the application areas of wearable electroencephalographic devices. In that, new types of electrodes take place, and particular attention is needed to ensure the required quality of obtained signals. In this study, we evaluate electrode-skin impedance and signal quality for several kinds of electrodes when used in conditions typical for wearable devices.

Adaptation of Translated Frame-Based Approach for Forward Kinematics in a Radiosurgical Snake-Like Robot.

Snake-like robots are a typical serial-link manipulator newly adopted to assist human experts during medical procedures. Of the several prototypes that have been proposed for surgical repair of abdominal organs and delivery of radiation doses, only a very few attained FDA clearance and commercialization for clinical usage. This can be ascribed to complexities inherent with teleoperation of the redundant robots when controlled via single-ports or interactions with other organs both along the surgical path and the operation area.

A Novel Antibacterial Membrane Electrode Based on Bacterial Cellulose/Polyaniline/AgNO Composite for Bio-Potential Signal Monitoring.

We propose a flexible, dry, and antibacterial electrode with a low and stable skin electrode contact impedance for bio-potential signal monitoring. We fabricated a bacterial cellulose/polyaniline/AgNO nanocomposite membrane (BC/PANI/AgNO) and used it for bio-potential signal monitoring. The bacterial cellulose (BC) provides a 3-D nanoporous network structure, and it was used as a substrate material in the BC/PANI/AgNO nanocomposite membrane.

Deeply-learnt damped least-squares (DL-DLS) method for inverse kinematics of snake-like robots.

Recently, snake-like robots are proposed to assist experts during medical procedures on internal organs via natural orifices. Despite their well-spelt advantages, applications in radiosurgery is still hindered by absence of suitable designs required for spatial navigations within clustered and confined parts of human body, and inexistence of precise and fast inverse kinematics (IK) models. In this study, a deeply-learnt damped least squares method is proposed for solving IK of spatial snake-like robot.

Towards Characterization and Adaptive Compensation of Backlash in a Novel Robotic Catheter System for Cardiovascular Interventions.

Despite the success and prospects of the robotic catheter system for the cardiovascular access, loss of vision, and haptics have limited its global adoption. A direct implication is the great difficulty posed when trying to eliminate the backlash in catheters during vascular cannulations. As a result, physicians and patients end up been exposed to high radiation for a long period of time.

Co-contraction characteristics of lumbar muscles in patients with lumbar disc herniation during different types of movement.

Background: Muscular performance is an important factor for the mechanical stability of lumbar spine in humans, in which, the co-contraction of lumbar muscles plays a key role. We hypothesized that when executing different daily living motions, the performance of the lumbar muscle co-contraction stabilization mechanism varies between patients with lumbar disc herniation (LDH) and healthy controls. Hence, in this study, co-contraction performance of lumbar muscles between patients with LDH and healthy subjects was explored to check if there are significant differences between the two groups when performing four representative movements.

A Master-Slave control system with workspaces isomerism for teleoperation of a snake robot.

Snake robots can be used to assist experts during surgical operations on internal organs via natural orifices. However, real-time control of such robot in Mater Slave (MS) teleoperation is a major challenge. Inverse kinematics solution of snake robots has being a key challenge towards real time control especially if the robot is hyper-redundant.

Non-iterative geometric approach for inverse kinematics of redundant lead-module in a radiosurgical snake-like robot.

Background: Snake-like robot is an emerging form of serial-link manipulator with the morphologic design of biological snakes. The redundant robot can be used to assist medical experts in accessing internal organs with minimal or no invasion. Several snake-like robotic designs have been proposed for minimal invasive surgery, however, the few that were developed are yet to be fully explored for clinical procedures.