José Maria Azorín

Visual evoked potential-based brain-machine interface applications to assist disabled people

This paper describes a brain-computer interface (BCI) based on electroencephalography (EEG) that has been developed to assist disabled people. The BCI uses the evoked potentials paradigm (through P300 and N2PC waves detection), registering the EEG signals with 16 electrodes over the scalp. Three applications have been developed using this BCI paradigm. The first application is an Internet browser that allows to access to Internet and to control a computer. The second application allows controlling a robotic arm in order to manipulate objects. The third application is a basic communication tool that allows severe disabled people to interact with other people using basic commands related to emotions and needs. All the applications are composed by visual interfaces that show different options related to the application. These options are pseudo-randomly flickering in a screen. In order to select a specific command, the user must focus on the desired option. The BCI is able to obtain the desired option by detecting the P300 and N2PC waves produced as an automatic response of the brain to attended visual stimuli and finally classifying these signals. Different experiments with volunteers have been carried out in order to validate the applications. The experimental results obtained as well as the improvement achieved by using both types of evoked potentials are shown in the paper.

Wireless and Portable EOG-Based Interface for Assisting Disabled People

This paper describes a new portable and wireless interface based on electrooculography (EOG) aimed at people with severe motor disorders. This interface allows us detecting the movement of the eyes measuring the potential between the cornea and the retina. The interface uses five electrodes placed around the eyes of the user in order to register this potential. A processing algorithm of the EOG signals has been developed in order to detect the movement of the eyes. This interface has many advantages in comparison to commercial devices. It is a cheap and small sized device with USB compatibility. It does not need power supply from the network as it works with batteries and USB supply. Several experiments have been done to test the electronics of the interface. A first set of experiments has been performed to obtain the movement of the eyes of the user processing the signals provided by the interface. In addition, the interface has been used to control a real robot arm. The accuracy and time taken have been measured showing that the user is capable of controlling the robot using only his/her eyes with satisfactory results.

Generalized control method by state convergence for teleoperation systems with time delay

In this paper a generalized design and control method for teleoperation systems with communication time delay is presented. The design method is based on the state space formulation and it allows to obtain the control parameters for any teleoperation system where the master and the slave manipulators would be represented by nth-order linear differential equations. Through state convergence between the master and the slave, the control system allows the slave to follow the master inspite of the time delay. The method is also able to establish the desired dynamics of this convergence and the dynamics of the slave manipulator. Experimental results are presented showing the validity of the proposed design and control method.

SVM-based Brain–Machine Interface for controlling a robot arm through four mental tasks

Abstract Human–Machine Interfaces can be very useful to improve the quality of life of physically impaired users. In this work, a non-invasive spontaneous Brain–Machine Interface (BMI) has been designed to control a robot arm through the mental activity of the users. This BMI uses the classification of four mental tasks in order to manage the movements of the robot. The high accuracy in the classification of these tasks (around 70%) allows a quick accomplishment of the experiment designed, even with the low signal-to-noise ratio of this kind of signals. The experiment consists of reaching four points in the workspace of an industrial robot in the established order. After a brief training, the volunteers are able to control the robot in a real time activity. The real time test shows that the system can be applied to do more complex activity such as pick and place tasks if a supplementary system is added. These interfaces are very adequate in the control of rehabilitation or assistance systems for people suffering from motor impairment.

Teleoperated parallel climbing robots in nuclear installations

Purpose – The aim of this paper is to present new robotic structures that can be suitable for inspection, maintenance and dismantling tasks in nuclear facilities.Design/methodology/approach – In the first part, two types of parallel robots capable to climb through structures are presented. The kinematics of the proposed platforms is reviewed, with emphasis on the analysis of the singularities. Next section shows the control architecture and the hardware setup of the developed system. Finally, the prototypes developed are showed and some conclusions are obtained.Findings – The slave robot is a parallel structure with the ability to climb over structures and with a very high load capacity. The master device is a parallel device with special characteristics that makes easier the teleoperation of the parallel slave robot.Originality/value – The paper presents a teleoperation system based on parallel platform with 6 degrees of freedom to overcome the classical difficulties of teleoperation in nuclear facilities.

Dynamic analysis for a teleoperation system with time delay

In this paper, the dynamic analysis for a teleoperation system with time delay is presented. The teleoperation system is controlled using a new design method through state convergence. This control method allows establishing the dynamics of the slave and the master-slave error. To perform the dynamic analysis, the influence of the slave and the error poles location in the dynamic behavior of the teleoperation system is studied. Also the robustness of the method control against slightly variations in the design parameters is analyzed.

Control of a 2 DoF robot using a Brain-Machine Interface

In this paper, a non-invasive spontaneous Brain-Machine Interface (BMI) is used to control the movement of a planar robot. To that end, two mental tasks are used to manage the visual interface that controls the robot. The robot used is a PupArm, a force-controlled planar robot designed by the nBio research group at the Miguel Hernández University of Elche (Spain). Two control strategies are compared: hierarchical and directional control. The experimental test (performed by four users) consists of reaching four targets. The errors and time used during the performance of the tests are compared in both control strategies (hierarchical and directional control). The advantages and disadvantages of each method are shown after the analysis of the results. The hierarchical control allows an accurate approaching to the goals but it is slower than using the directional control which, on the contrary, is less precise. The results show both strategies are useful to control this planar robot. In the future, by adding an extra device like a gripper, this BMI could be used in assistive applications such as grasping daily objects in a realistic environment. In order to compare the behavior of the system taking into account the opinion of the users, a NASA Tasks Load Index (TLX) questionnaire is filled out after two sessions are completed.

Assistive robot application based on an RFID control architecture and a wireless EOG interface

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.

Performance evaluation of spherical parallel platforms for humanoid robots

This paper presents a simple methodology for the quantitative and qualitative analysis of the performance of spherical parallel platforms. The quaternion formulation is used to represent the possible rotations, showing the workspace as a three-dimensional (3-D) solid object. The singularities of the platform intersect graphically with its workspace, allowing a graphical study of the mechanism kinematics. The performance criterion considered here has been the local dexterity of the manipulator. This methodology has been used to study and analyze three known orientation parallel platforms: 3- R RR, 3-U P U-wrist, and 2-U P S-1- R U. The objective of this study is to analyze the ability of these platforms to be utilized as mechanisms for the neck and shoulders of humanoid robots. Finally, the forces on actuators in some typical motions for neck and shoulder are plotted.

Using a brain-machine interface to control a hybrid upper limb exoskeleton during rehabilitation of patients with neurological conditions

BackgroundAs a consequence of the increase of cerebro-vascular accidents, the number of people suffering from motor disabilities is raising. Exoskeletons, Functional Electrical Stimulation (FES) devices and Brain-Machine Interfaces (BMIs) could be combined for rehabilitation purposes in order to improve therapy outcomes.MethodsIn this work, a system based on a hybrid upper limb exoskeleton is used for neurological rehabilitation. Reaching movements are supported by the passive exoskeleton ArmeoSpring and FES. The movement execution is triggered by an EEG-based BMI. The BMI uses two different methods to interact with the exoskeleton from the user’s brain activity. The first method relies on motor imagery tasks classification, whilst the second one is based on movement intention detection.ResultsThree healthy users and five patients with neurological conditions participated in the experiments to verify the usability of the system. Using the BMI based on motor imagery, healthy volunteers obtained an average accuracy of 82.9 ± 14.5 %, and patients obtained an accuracy of 65.3 ± 9.0 %, with a low False Positives rate (FP) (19.2 ± 10.4 % and 15.0 ± 8.4 %, respectively). On the other hand, by using the BMI based on detecting the arm movement intention, the average accuracy was 76.7 ± 13.2 % for healthy users and 71.6 ± 15.8 % for patients, with 28.7 ± 19.9 % and 21.2 ± 13.3 % of FP rate (healthy users and patients, respectively).ConclusionsThe accuracy of the results shows that the combined use of a hybrid upper limb exoskeleton and a BMI could be used for rehabilitation therapies. The advantage of this system is that the user is an active part of the rehabilitation procedure. The next step will be to verify what are the clinical benefits for the patients using this new rehabilitation procedure.