Carlos Perez-Vidal
Universidad Miguel Hernández de Elche
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Publication
Featured researches published by Carlos Perez-Vidal.
IEEE Transactions on Robotics | 2005
Nicolas Garcia-Aracil; Ezio Malis; Rafael Aracil-Santonja; Carlos Perez-Vidal
In the recent past, the visibility problem in vision-based control has been widely investigated. The proposed solutions generally have a common goal: to always keep the object in the cameras field of view during the visual servoing. Contrary to this solution, we propose a new approach based on the concept of allowing the changes of visibility in image features during the control task. To this aim, the camera invariant visual-servoing approach has been redefined in order to take into account the changes of visibility in image features. A new smooth task function using weighted features is presented, and a continuous control law is obtained starting from it by imposing its exponential decrease to zero. Furthermore, the local stability analysis of the invariant visual-servoing approach with weighted features is presented. Finally, this promising way of dealing with the visibility issue has been successfully tested with an eye-in-hand robotic system.
Medical & Biological Engineering & Computing | 2011
Ricardo Morales; Francisco J. Badesa; Nicolas Garcia-Aracil; José María Sabater; Carlos Perez-Vidal
The aim of rehabilitation robotic area is to research on the application of robotic devices to therapeutic procedures. The goal is to achieve the best possible motor, cognitive and functional recovery for people with impairments following various diseases. Pneumatic actuators are attractive for robotic rehabilitation applications because they are lightweight, powerful, and compliant, but their control has historically been difficult, limiting their use. This article first reviews the current state-of-art in rehabilitation robotic devices with pneumatic actuation systems reporting main features and control issues of each therapeutic device. Then, a new pneumatic rehabilitation robot for proprioceptive neuromuscular facilitation therapies and for relearning daily living skills: like taking a glass, drinking, and placing object on shelves is described as a case study and compared with the current pneumatic rehabilitation devices.
Robotics and Autonomous Systems | 2012
Eduardo Iáñez; Andrés íbeda; José Maria Azorín; Carlos Perez-Vidal
This paper describes an assistive robot application that combines a portable wireless interface based on electrooculography (EOG) and Radiofrequency Identification (RFID) technology. This assistive application is aimed at handicapped users who suffer from a severe motor disability. To that end, a realistic application has been designed. It consists of an environment in which users can bring a glass and a water bottle closer with only the help of their eye movement using a real robot arm. RFID will be used as a support to the EOG interface in a shared control architecture by storing information of the objects in tags placed on the scene. Five volunteers tested the assistive robot application. The results obtained show that all of them were able to finish the tests in a suitable time and the results improved with practice and training. This proves that the assistive robot application can be a feasible way to help handicapped users.
systems man and cybernetics | 2012
Francisco J. Badesa; Ricardo Morales; Nicolas Garcia-Aracil; José María Sabater; Carlos Perez-Vidal; Eduardo Fernández
The paper presents the developing of a new robotic system for the administration of a highly sophisticated therapy to stroke patients. This therapy is able to maximize patient motivation and involvement in the therapy and continuously assess the progress of the recovery from the functional viewpoint. Current robotic rehabilitation systems do not include patient information on the control loop. The main novelty of the presented approach is to close patient in the loop and use multisensory data (such as pulse, skin conductance, skin temperature, position, velocity, etc.) to adaptively and dynamically change complexity of the therapy and real-time displays of a virtual reality system in accordance with specific patient requirements. First, an analysis of subjects physiological responses to different tasks is presented with the objective to select the best candidate of physiological signals to estimate the patient physiological state during the execution of a virtual rehabilitation task. Then, the design of a prototype of multimodal robotic platform is defined and developed to validate the scientific value of the proposed approach.
Advanced Robotics | 2009
Carlos Perez-Vidal; Luis Gracia; Nicolas Garcia; Enric Cervera
This research develops a control scheme for visual servoing that explicitly takes into account the delay introduced by image acquisition and processing. For this purpose, a predictor block, i.e., an estimator that predicts several samples ahead of time, is properly included in the scheme. The proposed approach is analytically analyzed in terms of dynamics and steady-state errors, and compared to previous approaches. Furthermore, several simulations are comparatively shown in order to illustrate the benefits and limitations of the proposed control scheme. Finally, some experimental results using a turntable and a 3-d.o.f. Cartesian robot are provided in order to validate the analytical and simulation results.
Sensors | 2012
Ricardo Morales; Francisco J. Badesa; Nicolas Garcia-Aracil; Carlos Perez-Vidal; José María Sabater
This paper presents a microdevice for monitoring, control and management of electric loads at home. The key idea is to compact the electronic design as much as possible in order to install it inside a Schuko socket. Moreover, the electronic Schuko socket (electronic microdevice + Schuko socket) has the feature of communicating with a central unit and with other microdevices over the existing powerlines. Using the existing power lines, the proposed device can be installed in new buildings or in old ones. The main use of this device is to monitor, control and manage electric loads to save energy and prevent accidents produced by different kind of devices (e.g., iron) used in domestic tasks. The developed smart device is based on a single phase multifunction energy meter manufactured by Analog Devices (ADE7753) to measure the consumption of electrical energy and then to transmit it using a serial interface. To provide current measurement information to the ADE7753, an ultra flat SMD open loop integrated circuit current transducer based on the Hall effect principle manufactured by Lem (FHS-40P/SP600) has been used. Moreover, each smart device has a PL-3120 smart transceiver manufactured by LonWorks to execute the users program, to communicate with the ADE7753 via serial interface and to transmit information to the central unit via powerline communication. Experimental results show the exactitude of the measurements made using the developed smart device.
Robotics and Autonomous Systems | 2015
Enrique Hortal; Eduardo Iáñez; Andrés Úbeda; Carlos Perez-Vidal; José Maria Azorín
This paper presents a multimodal Human-Machine Interface system that combines an Electrooculography Interface and a Brain-Machine Interface. This multimodal interface has been used to control a robotic arm to perform pick and place tasks in a three dimensional environment. Five volunteers were asked to pick two boxes and place them in different positions. The results prove the feasibility of the system in the performance of pick and place tasks. By using the multimodal interface, all the volunteers (even naive users) were able to successfully move two objects within a satisfactory period of time with the help of the robotic arm. A multimodal HMI to perform pick and place tasks with a robotic arm is presented.The EOG interface is applied to control planar movements and to operate the gripper.The BMI is used to control the height of the gripper through two mental tasks.The system had been tested by five healthy subjects.The results prove the feasibility of the system in the performance of these tasks.
Biomedical Engineering: Applications, Basis and Communications | 2014
Franciso J. Badesa; Ana Llinares; Ricardo Morales; Nicolas Garcia-Aracil; José María Sabater; Carlos Perez-Vidal
Cerebrovascular accident or stroke in aging population is the primary cause of disability and the second leading cause of death in many countries, including Spain. Arm impairment is common and the recovery is partly dependent on the intensity and frequency of rehabilitation intervention. However, physical therapy resources are often limited, so methods of supplementing traditional physiotherapy, such as robot assisted therapy, are essential. This paper describes design, development and control aspects of a planar robot driven by pneumatic swivel modules for upper-limb rehabilitation of post-stroke patients. Moreover, first experimental results with one post-stroke patient are presented to show the benefits of using the proposed system.
PLOS ONE | 2015
Andrés Úbeda; Enrique Hortal; Eduardo Iáñez; Carlos Perez-Vidal; José Maria Azorín
The past decades have seen the rapid development of upper limb kinematics decoding techniques by performing intracortical recordings of brain signals. However, the use of non-invasive approaches to perform similar decoding procedures is still in its early stages. Recent studies show that there is a correlation between electroencephalographic (EEG) signals and hand-reaching kinematic parameters. From these studies, it could be concluded that the accuracy of upper limb kinematics decoding depends, at least partially, on the characteristics of the performed movement. In this paper, we have studied upper limb movements with different speeds and trajectories in a controlled environment to analyze the influence of movement variability in the decoding performance. To that end, low frequency components of the EEG signals have been decoded with linear models to obtain the position of the volunteer’s hand during performed trajectories grasping the end effector of a planar manipulandum. The results confirm that it is possible to obtain kinematic information from low frequency EEG signals and show that decoding performance is significantly influenced by movement variability and tracking accuracy as continuous and slower movements improve the accuracy of the decoder. This is a key factor that should be taken into account in future experimental designs.
PLOS ONE | 2013
Eduardo Iáñez; José Maria Azorín; Carlos Perez-Vidal
This paper describes a human-computer interface based on electro-oculography (EOG) that allows interaction with a computer using eye movement. The EOG registers the movement of the eye by measuring, through electrodes, the difference of potential between the cornea and the retina. A new pair of EOG glasses have been designed to improve the users comfort and to remove the manual procedure of placing the EOG electrodes around the users eye. The interface, which includes the EOG electrodes, uses a new processing algorithm that is able to detect the gaze direction and the blink of the eyes from the EOG signals. The system reliably enabled subjects to control the movement of a dot on a video screen.