Modeling Robotic-Assisted Mechanical Thrombectomy Procedures with the CorPath GRX Robot: The Core-Flow Study.

BACKGROUND AND PURPOSE: Endovascular robotic devices may enable experienced neurointerventionalists to remotely perform endovascular thrombectomy. This study aimed to assess the feasibility, safety, and efficacy of robot-assisted endovascular thrombectomy compared with manual procedures by operators with varying levels of experience, using a 3D printed neurovascular model. MATERIALS AND METHODS: M1 MCA occlusions were simulated in a 3D printed neurovascular model, linked to a CorPath GRX robot in a biplane angiography suite. Four interventionalists performed manual endovascular thrombectomy (n = 45) and robot-assisted endovascular thrombectomy (n = 37) procedures. The outcomes included first-pass recanalization (TICI 2c-3), the number and size of generated distal emboli, and procedural length. RESULTS: A total of 82 experimental endovascular thrombectomies were conducted. A nonsignificant trend favoring the robot-assisted endovascular thrombectomy was observed in terms of final recanalization (89.2% versus manual endovascular thrombectomy, 71.1%; P = .083). There were no differences in total mean emboli count (16.54 [SD, 15.15] versus 15.16 [SD, 16.43]; P = .303). However, a higher mean count of emboli of > 1 mm was observed in the robot-assisted endovascular thrombectomy group (1.08 [SD, 1.00] versus 0.49 [SD, 0.84]; P = .001) compared with manual endovascular thrombectomy. The mean procedural length was longer in robot-assisted endovascular thrombectomy (6.43 [SD, 1.71] minutes versus 3.98 [SD, 1.84] minutes; P < .001). Among established neurointerventionalists, previous experience with robotic procedures did not influence recanalization (95.8% were considered experienced; 76.9% were considered novices; P = .225). CONCLUSIONS: In a 3D printed neurovascular model, robot-assisted endovascular thrombectomy has the potential to achieve recanalization rates comparable with those of manual endovascular thrombectomy within competitive procedural times. Optimization of the procedural setup is still required before implementation in clinical practice.

Announcement Signals and Automatic Braking Using Virtual Balises in Railway Transport Systems.

In rail transport, various automatic protection systems are available to ensure the safe operation of trains and to facilitate automation and optimization tasks. For this purpose, a set of physical balises is used, which are placed at fixed points along the railway track. Based on the information provided by these balises, different information is displayed to the driver, and control actions are generated. The use of physical balises located at fixed points does not allow for automatic protection actions on sections of track where they are not installed. This is a major drawback as in many cases, temporary automatic protection actions are necessary on sections of the railway line without balises due to various circumstances (work on the track, accidents, etc.). To solve this problem, this paper presents a solution called announcement signals and automatic braking using virtual balises (ASAB-VB). This proposal allows the incorporation of virtual balises at points on the track where it is necessary to temporarily perform automatic protection actions. For this purpose, the ASAB-VB system allows obtaining the train position in real-time and storing a digital map of the track that will be made by each train. This digital map includes geographic information about the balises (both physical and virtual ones) located on the track. At the same time, the train position is obtained by merging the information provided by a GNSS, an odometer, and an inertial system (gyro and accelerometers).

Self-Triggered Formation Control of Nonholonomic Robots.

In this paper, we report the design of an aperiodic remote formation controller applied to nonholonomic robots tracking nonlinear, trajectories using an external positioning sensor network. Our main objective is to reduce wireless communication with external sensors and robots while guaranteeing formation stability. Unlike most previous work in the field of aperiodic control, we design a self-triggered controller that only updates the control signal according to the variation of a Lyapunov function, without taking the measurement error into account. The controller is responsible for scheduling measurement requests to the sensor network and for computing and sending control signals to the robots. We design two triggering mechanisms: centralized, taking into account the formation state and decentralized, considering the individual state of each unit. We present a statistical analysis of simulation results, showing that our control solution significantly reduces the need for communication in comparison with periodic implementations, while preserving the desired tracking performance. To validate the proposal, we also perform experimental tests with robots remotely controlled by a mini PC through an IEEE 802.11g wireless network, in which robots pose is detected by a set of camera sensors connected to the same wireless network.

Determination of S-containing drug metabolites from in vitro and in vivo metabolism studies by using LC-ICP/MS.

Recently, liquid chromatography coupled to inductively coupled plasma mass spectrometry (LC-ICP/MS) has been introduced to deal with some applications in the field of pharmaceutical, biomedical, and clinical analysis. In the case of drug research, the number of drugs and their metabolites containing detectable elements is quite limited. In this paper, LC-ICP/MS has been demonstrated to be suitable for the determination of S-containing drugs and their metabolites. In order to minimize the interference of polyatomic oxygen (m/z 32), the indirect detection of S, by means of the SO(+) ion (m/z 48), was optimized. For quantification purposes, it has been encountered that the percentage of organic solvent in the mobile phase strongly affects the sensitivity. Here, corrective strategies based on calibration curves established at different solvent concentrations (solvent-zone quantification) and post-column gradient compensation have been proposed to circumvent sensitivity variations. Results obtained have shown that suitable calibration models have been built for any compound regardless of the solvent percentage at which it is eluted from the chromatographic column. To prove the applicability of this methodology, the metabolism of ethacrynic acid and tiotropium bromide has been studied in vitro and in vivo. In the first case, ethacrynic acid does not contain S in its structure, however, the major route of metabolism for this compound consists of the formation of glutathione adduct and its further degradation. In the second case, tiotropium bromide contains two S atoms in its structure.

Multi-camera sensor system for 3D segmentation and localization of multiple mobile robots.

This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space using a multi-camera sensor system. The set of calibrated and synchronized cameras are placed in fixed positions within the environment (intelligent space). The proposed algorithm for motion segmentation and 3D localization is based on the minimization of an objective function. This function includes information from all the cameras, and it does not rely on previous knowledge or invasive landmarks on board the robots. The proposed objective function depends on three groups of variables: the segmentation boundaries, the motion parameters and the depth. For the objective function minimization, we use a greedy iterative algorithm with three steps that, after initialization of segmentation boundaries and depth, are repeated until convergence.

Localization of mobile robots using odometry and an external vision sensor.

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.

GPCA vs. PCA in recognition and 3-D localization of ultrasound reflectors.

In this paper, a new method of classification and localization of reflectors, using the time-of-flight (TOF) data obtained from ultrasonic transducers, is presented. The method of classification and localization is based on Generalized Principal Component Analysis (GPCA) applied to the TOF values obtained from a sensor that contains four ultrasound emitters and 16 receivers. Since PCA works with vectorized representations of TOF, it does not take into account the spatial locality of receivers. The GPCA works with two-dimensional representations of TOF, taking into account information on the spatial position of the receivers. This report includes a detailed description of the method of classification and localization and the results of achieved tests with three types of reflectors in 3-D environments: planes, edges, and corners. The results in terms of processing time, classification and localization were very satisfactory for the reflectors located in the range of 50-350 cm.

Stereo vision tracking of multiple objects in complex indoor environments.

This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

Class separation improvements in pixel classification using colour injection.

This paper presents an improvement in the colour image segmentation in the Hue Saturation (HS) sub-space. The authors propose to inject (add) a colour vector in the Red Green Blue (RGB) space to increase the class separation in the HS plane. The goal of the work is the development of an algorithm to obtain the optimal colour vector for injection that maximizes the separation between the classes in the HS plane. The chromatic Chrominace-1 Chrominance-2 sub-space (of the Luminance Chrominace-1 Chrominance-2 (YC(1)C(2)) space) is used to obtain the optimal vector to add. The proposal is applied on each frame of a colour image sequence in real-time. It has been tested in applications with reduced contrast between the colours of the background and the object, and particularly when the size of the object is very small in comparison with the size of the captured scene. Numerous tests have confirmed that this proposal improves the segmentation process, considerably reducing the effects of the variation of the light intensity of the scene. Several tests have been made in skin segmentation in applications for sign language recognition via computer vision, where an accurate segmentation of hands and face is required.