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We present a real implemented "eye-in-hand" test-bed system for sensor-based collision-free motion planning for articulated robot arms. The system consists of a PUMA 560 with a triangulation based area-scan laser range finder (the eye) mounted on its wrist. The framework for our planning approach was presented in Yu and Gupta (1998). It is inspired by motion planning research and incrementally builds a roadmap that represents the connectivity of the free configuration space, as it senses the physical environment. We present some experimental results with our sensor-based planner running on this real test-bed. The robot is started in completely unknown and cluttered environments. Typically, the planner is able to reach (planning as it senses) the goal configuration in about 7-25 scans (depending on the scene complexity), while avoiding collisions with the obstacles throughout.

We propose a novel and global algorithm to solving the point-to-point inverse kinematics problem for redundant manipulators. Given an initial configuration of the robot, the problem is to find a reachable (path-connected) configuration that corresponds to a desired position and orientation of the end-effector. Our approach was inspired by recent motion planning research and explicitly takes into account constraints due to joint limits, self-collisions and static obstacles in the environment. The problem is posed as an optimization problem. Central to solving this optimization problem is a novel representation, the kinematic roadmap of a manipulator. The kinematic roadmap captures the connectivity of the connected component of the free configuration space of the manipulator in a finite graph like structure. The point-to-point inverse kinematics problem is then solved (with a local planner) using this roadmap. In this paper, we provide completeness results for our algorithm.

Our sequential approach is a framework for developing practical motion planners for manipulators with many degrees-of-freedom (DOFs). The essence of this approach is to exploit the serial structure of manipulator arms and decompose the m-dimensional problem of planning collision-free motions for an n-link manipulator into a sequence of smaller m-dimensional subproblems, each of which corresponds to planning the motion of a subgroup of m-1 links along a given path. In this paper, we present an efficient bitmap-based implementation of the sequential framework. This bitmap-based implementation is more efficient and robust than a previously reported visibility graph-based implementation; and it utilizes a novel and more efficient backtracking mechanism. Our implementations are in C running on a SUN Sparc 10. We have conducted extensive experiments for planar arms with up to 8 degrees of freedom among randomly placed obstacles. The experiments show that the bitmap-based implementation of the sequential framework with the novel backtracking mechanism is very efficient. The average run time for a six degree of freedom manipulator in quite cluttered environments are around seven minutes. The planner succeeds for 100% of the examples in our simulations with small backtracking levels (2 for 4 DOF arm, 3 for 6 and 8 DOF arms). >

A sequential framework that allows planners for manipulator arms with many degrees of freedom to be developed is addressed. The essence of this framework is to exploit the serial structure of manipulator arms and decompose the n-dimensional problem of planning collision-free motions for an n-link manipulator into a sequency of smaller m-dimensional subproblems, each of which corresponds to planning the motion of a subgroup of m-1 links. Extensive experimental results within the sequential framework are presented for a variety of manipulators. A main goal of these simulations (1) to show the effectiveness of the sequential approach with the backtracking mechanism, and (2) to quantify the improvement of the backtracking mechanism and the trade-off between the number of backtrackings and the execution time of the planner. The experiments show that the sequential framework with the backtracking mechanism is quite efficient for manipulator arms with many degrees of freedom.

Proposes an approach-"Blind Man's" approach-to shape description in which tactile information is sensed from the fingertips of a dexterous hand. Using this contact information, we investigate two complementary methods for curvature estimation. The first method is based on rolling one finger to estimate curvature at a point on the surface. We use Montana's equations for estimating curvature at a point using simulations and analyze the sensitivity of the approach to noise. The second method uses multiple fingers to slide along a surface while sensing contact points and surface normals. We present a method to extract the shape properties of a patch obtained by fitting a B-spline surface to this multi-fingered sweep across the surface of the object. The method enables us to extract higher level shape information based on the curvature properties of patch.

In this paper, we present a novel approach within the sequential framework to develop practical motion planners for many degrees of freedom (DOF) arms. In this approach, each of the sub-problem is solved by using numerical potential fields defined over bitmap-based representations of the 2-dimensional sub-spaces. Furthermore, an efficient backtracking mechanism based on a novel notion of virtual forbidden regions in these 2-dimensional subspaces is presented. This novel approach leads to much more efficient and robust motion planners than a previously reported visibility graph (in the 2-dimensional subspaces) based implementation. We have conducted extensive experiments for planar arms with up to 8-DOF among randomly placed obstacles. Although it is not complete, the planner never failed for the examples in hundreds of simulations, and very small backtracking levels were needed. We have implemented the planner for 3-dimensional workspaces and an illustrative example for a 7-DOF manipulator shows the promise of our approach. >

A motion planner is implemented that plans collision-free motions for a PUMA 560 manipulator arm among stationary obstacles. The basic idea behind the approach is a novel sequential search strategy that successively plans the motion of each link starting from the base link. The strategy results in one 1-dimensional (the first link is degenerate) and n-1 2-dimensional planning problems instead of one n-dimensional problem for an n-link manipulator arm. The search strategy leads to a fast and efficient algorithm and is especially suited for highly redundant arms. However, the penalty is that the strategy may miss certain paths. In the current implementation for the PUMA 560, only the first three links of the arm are considered. >

We propose an algorithm for sensorless reorientation of 3D convex polyhedral parts through a sequence of step devices. Part is assumed to arrive in an arbitrary orientation and is being translated forward (e.g., on a conveyor belt) at slow speed. After precomputing, our algorithm produces a sequence of O(n) distinct steps, where n is the number of faces in the polyhedral part. As the part passes (drops) through the steps, it successively changes orientation. At the output end, the part will be oriented (for most initial orientations) to a pose such that its center-of-mass is the lowest possible.

This paper describes a global motion planner for dextrous manipulation of 3D objects by a multifingered robotic hand. We focus on the reconfiguration problem: find a feasible quasi-static trajectory (motions and contact forces) that moves a hand-object system from an initial grasp to a final desired configuration of the object. The planner is designed as a two-level process: a global level that expands a tree of sub-goals in the configuration space of the object, and a local level that searches for feasible quasi-static trajectories of the entire manipulation system between adjacent sub-goals. A key feature of the planner is that it exploits the redundancy of the system by using, in a complementary way, different canonical manipulation modes and tackles the high dimensionality of the solution space (configuration and control spaces) by making use, instantaneously, of a random search over it. The planner is applied in simulation for achieving several nontrivial reconfiguration tasks for (piecewise-) smooth convex objects demonstrating the promise of our approach.

This paper re-examines a part orienting technique that orients polygonal shaped parts with a series of fences suspended above a conveyor belt. We examine the effect of uncertainty in the coefficient of friction as well as the typical size of the final assembly. The search technique in the original work although resolution complete, was inefficient, so we offer a heuristic search method that offers good performance. Several fence sequences generated by our algorithm were tested on real polygonal objects.

This paper examines a sensor based technique for determining the orientation of a polygon on a horizontal surface by pushing with a force/torque sensor equipped fence. Using an exploratory process, the resulting algorithm can determine the orientation, to symmetry, of the sub-class of polygons that are stable on all edges, in at most two pushes.

We present a general framework for sensor-based motion planning for an articulated robot arm with many degrees of freedom. We assume a sensor that measures distances in physical space (a range sensor). Inspired by recent work in classical motion planning, the crux of our framework is to represent the connectivity of the configuration space (C-space) with a graph structure, the roadmap. This roadmap is then incrementally built. We have performed some simulations that show the promise of our approach.

We present an algorithm for direct octree construction from range images. It uses a key property of most range sensors that all the voxels on sensed object surfaces are "visible" from the sensor. This enables us to define a projection map for range images. The projection map is used for efficiently checking if a given voxel is in the free region. Furthermore, this key property also reduces the number of faces to be checked for the nodes when constructing octrees. The algorithm is efficient in both memory space and run time, and is useful for sensor-based articulated robot motion planning, which is the main motivation for this work.

This paper addresses the motion planning problem for dextrous manipulation by an artificial multifingered hand. We focus on the task of re-orienting polyhedral objects and present a practical motion planner for achieving quasistatic manipulations by a four-fingered hand. The planner makes use of a simple manipulation strategy in which a single finger is moved and the other three are fixed. We describe how this scenario is exploited for reducing the space of trajectory solutions and used within a two-level incremental process to search for global re-orientation motions. The planner has been implemented and used for achieving several complex re-orientation tasks with frictional and frictionless contacts that show the practicality of our approach.

We propose an approach for investigating the shape properties of objects with curved surfaces using tactile sensing by a dexterous robot hand. Our proposed exploratory procedure (EP) uses multiple fingers to slide along a surface while sensing contact points and surface normals. Our approach incorporates the surface normal information into a B-spline surface fit of the data gathered from this EP. This additional surface normal information was found to improve the approximation of the surface. The shape properties of this B-spline surface are analyzed to recognize the shape of the object. A confidence estimate of the estimated shape is also calculated.

An emerging paradigm in solving the classical motion planning problem (among static obstacles) is to capture the connectivity of the configuration space using a finite (but possibly large) set of landmarks (or nodes) in it. In this paper, the authors extend this paradigm to manipulation planning problem, where the goal is to plan the motion of a robot so that it can move a given object from an initial configuration to a final configuration while avoiding collisions with the static obstacles in the environment. The authors' specific approach adapts Adraine's Clew Algorithm that has been shown effective for classical motion planning problem. In the authors' approach, landmarks are placed in lower dimensional submanifolds of the composite configuration space. These landmarks represent stable grasps that are reachable from the initial configuration. From each new landmark, the planner attempts to reach the goal configuration by executing a local planner, again in a lower (but different) dimensional submanifold of the composite configuration space. The authors have implemented this approach and present initial experiments with a simple 2-DOF planar arm among polygonal obstacles.

In this paper, we study the following motion planning problem for dexterous manipulation: devise a global plan that a dexterous hand can use to actively manipulate an object from a given initial orientation to a desired final orientation. We propose an approach that uses a local planner to search the orientation state space (S0(3)/spl times//spl Omega/) of the object by placing random landmarks in it. The local planner used in our implementation is a trajectory generator on SO(3) along with the finger tracking strategy proposed by Rus (1992). We report initial experiments that indicate the promise of our approach.

Presents an implementation of a path planner for a 7-DOF manipulator in 3-D environments. This implementation is based on a previously reported approach called the sequential framework to develop practical motion planners for many-DOF arms. The essence of the sequential framework is to exploit the serial structure of manipulator arms and decompose the n-dimensional problem of planning collision-free motions for an n-link manipulator into a sequence of smaller m-dimensional sub-problems (with backtracking), each of which corresponds to planning the motion of a sub-group of m-1 links along a given path. Each of the sub-problems (m=2) is solved by using numerical potential fields defined over bitmap-based representations of the 2-dimensional sub-spaces. Furthermore, an efficient backtracking mechanism based on a novel notion of virtual forbidden regions in these 2-dimensional sub-spaces is used. The author has implemented the above approach for a real 7-DOF manipulator in realistic 5-dimensional environments. Although it is not complete, the planner succeeded in several difficult examples with only a few levels (/spl les/2) of backtracking with run times ranging from ten minutes to an hour depending on the task difficulty.

We strive to obtain full spatial occupancy descriptions of the workspace from multiple range images acquired from different points of view. Such representations are highly suitable in path-planning applications, for charting a collision-free course through a workspace. We propose an algorithm, called peeling, which allows us to fuse range images into a voxel array and obtain a spatial occupancy model for use by a path planner. We also take a look at another method of range image fusion, called direct mapping, which combines the images into a voxel array but does not provide a proper spatial occupancy model. We present an overview of previous work in range image fusion and look at octrees and octree generation; our final model is an octree representation, for more efficient memory use. We are building a prototype system consisting of a technical Arts 100 AT laser range scanner mounted on a PUMA 560 robot arm, both controlled from an SGI workstation. Spatial occupancy models generated by this system are fed to an off-line path-planner.

We formally pose and explore some novel issues that arise for eye-sensor based motion planning for robots with non-trivial geometry/kinematics. The key issue is that while the sensor senses in physical space, the planning takes place in configuration space, and the two spaces are distinctly different for robots with nontrivial geometry/kinematics. This lends to some very interesting, fundamental yet novel issues. In particular, we introduce several novel notions: notion of s-reachability, notion of s-completeness that characterizes completeness for sensor-based planning algorithms, notion of explorability of configuration space, and notion of observability of physical space. We give sufficient conditions for a (discrete) eye-sensor based planner to be s-complete.

We consider the view planning problem where the sensor, a range scanner, is mounted on a robot mechanism with non-trivial geometry and kinematics. The robot+sensor system is required to explore the environment (obstacle/free space). We present a novel information theoretical approach in which the sensing action is viewed as reducing ignorance of the planning space, the C-space of the robot. The concept of C-space entropy is introduced as a measure of this ignorance. The next view in the planning process is determined by maximizing the expected reduction of C-space entropy, called maximal entropy reduction (MER) criterion. A computational tool to implement MER is the notion of information gain density function. Experimental results with a real PUMA robot with a wrist-mounted range scanner and a simulated robot show the effectiveness of the MER criterion in efficient exploration of environments for motion planning problems.

A 6-month-old infant was referred for cardiac evaluation in view of respiratory distress of 1-month duration. Chest X-ray revealed the presence of cardiomegaly with features differential plethora with the right lung field showing higher vascularity and grade II pulmonary venous hypertension as compared to the left lung field which showed grade I pulmonary venous hypertension suggestive of partially obstructed flow of the right pulmonary venous system (figure 1). Transthoracic echocardiography showed a dilated right atrium and right ventricle, a large non-restrictive ostium secundum atrial septal defect of size around 1 cm with a right-to-left shunt and severe pulmonary arterial hypertension (figure 2A). Detailed echocardiographic evaluation revealed increased flow velocities in the superior and inferior vena cava with a pulmonary venous confluence draining to the superior vena cava (SVC; figure …

A 64-year-old man with chronic atrial fibrillation was referred to our hospital for resection of a biopsy-proven adenocarcinoma of the right lung. A preoperative coronary angiogram demonstrated large, tortuous collateral vessels arising from the proximal right (Figure 1) and left circumflex (Figure 2 …

Atherosclerotic vertebral artery (VA) stenosis is a significant cause of vertebrobasilar ischemia. However, vertebral artery stenting (VAS) has not received the detailed scientific study that has been accorded to carotid artery stenting (CAS). In their series, Jenkins et al. ([1][1]) show excellent

Eisenmenger’s syndrome is a complex multisystem disease which occurs as a consequence of large left to right shunt affecting the pulmonary vasculature causing suprasystemic pulmonary artery pressures and subsequent right to left shunt. Usually Eisenmenger's syndrome is characterised by coronary artery dilation but coronary artery disease and occurrence of acute coronary syndrome is a rare association seldom described in literature. We present the case of a 33-year-old man who presented with an anterior wall ST elevation mycocardial infarction and was thrombolysed. The occurrence of acute coronary event in a case of Eisenmenger’s syndrome is a rare event and needs to be discussed and kept in mind by physicians and cardiologists who deal with such cases so that a high index of suspicion may be developed and emergent management may be possible.

Future wireless networks are envisioned to be all IP and capable of running real time applications like VoIP. IEEE 802.16 and IEEE 802.11 based networks popularly known as Wimax and Wifi are already being widely used for internet and other services. The combined Wimax/Wifi scenario can be ideal public-private partnership solution for distributing VoIP-based telephony solutions in villages using Wimax-based private backbone operator and Wifi community network for end distribution. Internet bandwidth is still a scarce resource and should be used optimally from both the user as well as backbone service provider’s point of view. Game theory can be effectively used for optimising service for both the parties in combined Wimax/Wifi scenarios. The results indicate that the utilities for both user and backbone service provider can be improved with cooperation between both parties. Third party broker agent realises cooperation between the two entities for an optimal solution. Using this approach, it is possible to obtain an optimal VoIP solution, which is beneficial for both user and backbone service provider.

Aggressive clinical and public health interventions have resulted in significant reduction in coronary artery disease (CAD) worldwide. However, South Asian immigrants (SAIs) exhibit the higher prevalence of CAD and its risk factors as compared with other ethnic populations. The objective of the current study is to assess the prevalence of metabolic syndrome (MS), its association with high density Lipoprotein (HDL) function, Apo lipoprotein A-I (APOA1) gene polymorphisms, and sub-clinical CAD using common carotid intima-media thickness (CCA-IMT) as a surrogate marker. A community-based cross-sectional study was conducted on SAIs aged 35-65 years. Dysfunctional/pro-inflammatory (Dys-HDL) was determined using novel cell free assay and HDL inflammatory index. Six intronic APOA1 gene polymorphisms were analyzed by DNA sequencing. According to the International Diabetes Federation definition, MS prevalence was 29.7% in SAIs without CAD and 26% had HDL inflammatory index ≥ 1 suggesting pro-inflammatory Dys-HDL. Six novel APOA1 single nucleotide polymorphisms (SNPs) were analyzed with logistic regression, three SNPs (G2, G3, and G5) were found to be significantly associated with MS (p = 0.039, p = 0.038, p = 0.054). On multi-variate analysis, MS was significantly associated with BMI > 23 (P = 0.005), Apo-A-I levels (p = 0.01), and Lp [a] (p < 0.0001). SAIs are known to be at a disproportionately high risk for CAD that may be attributed to a high burden for MS. There is need to explore and understand non-traditional risk factors with special focus on Dys-HDL, knowing that SAIs have low HDL levels. Large prospective studies are needed to further strengthen current study results.

In [Gup90, GG92], we have presented a sequential framework that allows us to develop planners for manipulator arms with many degrees of freedom. The essence of this framework is to exploit the serial structure of manipulator arms and decompose the n- dimensional problem of planning collision-free motions for an n-link manipulator into a sequence of smaller m-dimensional sub-problems, each of which corresponds to planning the motion of a sub-group of m-1 links. In this paper, we present extensive experimental results within our sequential framework for a variety of manipulators with up to eight degree of freedom manipulators. Two main goals of these simulations are (1) to show the effectiveness of the sequential approach with the backtracking mechanism, and (2) to quantify the improvement of the backtracking mechanism and the trade-off between number of backtrackings and the execution time of the planner. Our experiments show that the sequential framework with the backtracking mechanism is quite efficient for manipulator arms with many degrees of freedom. For a given maximum backtracking level, the run time and memory requirements vary roughly linearly with the degrees of freedom. The planner succeeds for 91% of the examples in our simulations with a maximum backtracking level of 2. Typical run times for a six degree of freedom manipulator in quite cluttered environments are of the order of tens of minutes. Our sequential thus provides a framework within which practical motion planners for many degree of freedom manipulators can be developed.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The authors have implemented a motion planner based on a novel sequential strategy to plan collision-free motions for serial manipulator arms among 3D polyhedral obstacles. The basic idea is to successively plan the motion of each link starting from the base link. Suppose that the motion of links till link i (including link i) has been planned. This already determines the path of one end (the proximal end) of link i+1. The motion of link i+1 is now planned along this path by controlling the degree of freedom associated with it-a 2D motion planning problem. This strategy results in one 1D (for the first link) and n-1 2D planning problems instead of one n-D problem. This greatly reduces complexity and is especially suitable for highly redundant arms. However, it is incomplete. Experimental results are given. >

To facilitate experiments in bipedal walking, we have developed a method for fast autonomous recognition of footholds marked by a distinctive color. An image patch is taken to be part of a foot-hold if its color is within a specified region of red-green-blue space and the patch is sufficiently large. The method is suitable for continuous use while the machine is walking and is robust with respect to variations in ambient lighting.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Mann ki Baat or “talking about the mind” is the first of a series of productions aiming to address a range of mental health issues relevant to the Asian community. Dharmendra, a Bollywood star, presents the topic in Hindi, supported by English subtitles. The videotape is also available in Urdu

A 37-year-old white man with a long history of recurrent herpetic keratitis presented with a rapidly enlarging pigmented iris lesion. The primary diagnostic concern was that the lesion might be a malignant melanoma. A biopsy of the mass was done and proved it to be a granuloma with granulomatous arteritis and infarction of the iris. In a patient with a history of recurrent ocular inflammation, such a hypersensitivity granuloma should be considered in the differential diagnosis of iris melanoma.

In this thesis, we studied the problem of real-time motion planning of multiple agents and multiple formations in virtual environments and games. In many such applications, agents move around and their motion must be planned. We are especially interested in motion planning in Real-time Tactical (RTT) games because they offer a challenging problem setting due to the following aspects: multiple agents, real-time, dynamic obstacles, complex environments, coherence of the agents (e.g., formations), and inexpensive pre-processing. We use the (basic) continuum model (a real-time crowd simulation framework based on the Fast Marching Method (FMM)) extensively in this thesis, because it unifies global planning and local planning (e.g., collision avoidance). Since the basic model may fail to generate collision-free paths in certain constrained situation (e.g., when agents pass through narrow passages) due to deadlocks amongst the agents, we propose to use a principled and efficient AI technique for decision making and planning (i.e., Coordination Graph (CG)) to avoid such deadlocks in the narrow passages. Next, we present the adaptive multi-resolution continuum model to plan motion of multiple agents. It allows each agent to have its own goal compared to the basic model, where agents have to be grouped into a few groups, while retaining the advantages of the basic model. Finally, we present a flexible virtual structure approach to the multi-agent coordination problem. The approach conceives of agents in a formation as if they lie on an elastic shape, which is modeled using the Boundary Element Method (BEM). Due to the BEM's boundary-only nature, even a formation with a large number of agents can be deformed in real-time. This approach for formation control is then combined with the continuum model to plan motion of multiple formations in virtual environments. To the best of our knowledge, this motion planning algorithm for multiple formations is the first one that does not us

We address the motion planning (MP) problem in real world robotic exploration and inspection tasks, where robot localization and mapping uncertainties have to be incorporated into the planned motions. The robot considered in this work is a mobile manipulator system, which combines the mobility of the base with the dexterousness of the manipulator. The first part of this work considers localization and mapping uncertainties in the motion planning problem. We propose RRT-SLAM, which uses a rapidly exploring random tree (RRT) in conjunction with a simulated particle based simultaneous localization and mapping (SLAM) algorithm to expand the tree. The simulated SLAM explicitly accounts for localization and mapping uncertainties in the planning stage. Moreover, the RRT itself is represented in the uncertainty-configuration space (UC-space), which is an augmented configuration space with an extra dimension of uncertainty. The collision probability along a planned path is explicitly calculated and is used to select a planned path. We further address the efficiency of the RRT-SLAM in the UC-space. We treat the issue from a data clustering point of view and propose a fractal dimension (FD) based checking criterion for efficient node generation, and demonstrate the positive results in simulations. The second part of this research addresses planning motions for the manipulator with the base staying stationary. Therefore, no sensor observation is available during the motion. We extend the probabilistic roadmap (PRM) algorithm to plan motions. Since the base pose of the manipulator is not precisely known due to the localization uncertainty, the path query of the roadmap becomes a constrained shortest path problem. We prove that this path query is an NP-hard problem, and propose an lazy path query algorithm that judiciously combines a k-shortest path algorithm with a labeling algorithm to achieve efficiency. The RRT-SLAM is tested on an actual PowerBot and the experimental results, File is printable.

In this thesis, motivated by robotic applications, the problem of view planning with combined view and travel costs (Traveling VPP) is addressed. It refers to planning a sequence of viewpoints to fully inspect the objects of interest and a path to realize these viewpoints, while minimizing the combined view and travel cost. Travel cost is the cumulative time and energy consumption due to the robot movements and thus is proportional to the total robot traveling distance. View cost corresponds to the image processing, image registration and geometric model construction after each view is taken and is proportional to the number of viewpoint planned. First, we assume that the viewpoints are given, the geometries of the object, and the graph encoding the robot paths are known. We give an LP based approximation algorithm. We show that the algorithmic approximation ratio is in the order of the frequency parameter, defined as the maximum number of viewpoints that see a single surface patch of the object. Together with the poly-logarithmic approximation ratio provided by an existing LP based randomized algorithm, the best known approximation ratio to Traveling VPP is the minimum of a constant times frequency and the poly-logarithmic of the input size, which matches the existing hardness result for the Group Steiner Tree problem. Then we introduce the Watchman Route Problem with Discrete View Cost (GWRP), which refers to planning a continuous robot tour inside a polygon and a number of discrete viewpoints on it with the minimum combined view and travel cost, such that every polygon boundary point is visible from at least one planned viewpoint. We propose a novel sampling method to reduce the problem to Traveling VPP with a bounded number of viewpoints. We show that the optimal cost of the GWRP is within a constant ratio of the optimal cost of the reduced Traveling VPP. Thus, we have an approximation algorithm to the GWRP. We implement our approximation algorithm for the GWRP

Recent studies using ATP III guidelines show that peripheral artery disease (PAD) patients have less optimal lipid control compared to those with coronary artery disease (CAD). Our study aimed to compare lipid management in patients with PAD, CAD and CAD with PAD by applying the new 2013 guidelines

Retrograde passage through a stenotic aortic valve (AV), with the purpose of measuring invasively the gradient across the AV, is not without risk. The utility of a 0.014” coronary pressure wire (CPW) for crossing severely stenotic AV has not been investigated. We examined the feasibility