Luis D. Lledó

A Comparative Analysis of 2D and 3D Tasks for Virtual Reality Therapies Based on Robotic-Assisted Neurorehabilitation for Post-stroke Patients

Post-stroke neurorehabilitation based on virtual therapies are performed completing repetitive exercises shown in visual electronic devices, whose content represents imaginary or daily life tasks. Currently, there are two ways of visualization of these task. 3D virtual environments are used to get a three dimensional space that represents the real world with a high level of detail, whose realism is determinated by the resolucion and fidelity of the objects of the task. Furthermore, 2D virtual environments are used to represent the tasks with a low degree of realism using techniques of bidimensional graphics. However, the type of visualization can influence the quality of perception of the task, affecting the patients sensorimotor performance. The purpose of this paper was to evaluate if there were differences in patterns of kinematic movements when post-stroke patients performed a reach task viewing a virtual therapeutic game with two different type of visualization of virtual environment: 2D and 3D. Nine post-stroke patients have participated in the study receiving a virtual therapy assisted by PUPArm rehabilitation robot. Horizontal movements of the upper limb were performed to complete the aim of the tasks, which consist in reaching peripheral or perspective targets depending on the virtual environment shown. Various parameter types such as the maximum speed, reaction time, path length, or initial movement are analyzed from the data acquired objectively by the robotic device to evaluate the influence of the task visualization. At the end of the study, a usability survey was provided to each patient to analysis his/her satisfaction level. For all patients, the movement trajectories were enhanced when they completed the therapy. This fact suggests that patients motor recovery was increased. Despite of the similarity in majority of the kinematic parameters, differences in reaction time and path length were higher using the 3D task. Regarding the success rates were very similar. In conclusion, the using of 2D environments in virtual therapy may be a more appropriate and comfortable way to perform tasks for upper limb rehabilitation of post-stroke patients, in terms of accuracy in order to effectuate optimal kinematic trajectories.

Hand exoskeleton for rehabilitation therapies with integrated optical force sensor

This article presents the design of a hand exoskeleton that features its modularity and the possibility of integrating a force sensor in its frame. The modularity is achieved by dividing the exoskeleton in separate units, each one driving a finger or pair of them. These units or “finger modules” have a single degree of freedom and may be easily attached or removed from the robot frame and human fingers by snap-in fixations. As for the force sensing capability, the device relies on a novel force sensor that uses optical elements to amplify and measure small elastic deformations in the robot structure. This sensor can be fully integrated as a structural element of the finger module. The proposed technology has been validated in two experimental sessions. A first study was performed in a clinical environment in order to check whether the hand exoskeleton (without the integrated force sensor) can successfully move an impaired hand in a “Mirror Therapy” environment. A second study was carried with healthy subjects to check the technical feasibility of using the integrated force sensor as a human–machine interface.

Auto-adaptative Robot-aided Therapy based in 3D Virtual Tasks controlled by a Supervised and Dynamic Neuro-Fuzzy System

This paper presents an application formed by a classification method based on the architecture of ART neural network (Adaptive Resonance Theory) and the Fuzzy Set Theory to classify physiological reactions in order to automatically and dynamically adapt a robot-assisted rehabilitation therapy to the patient needs, using a three-dimensional task in a virtual reality system. Firstly, the mathematical and structural model of the neuro-fuzzy classification method is described together with the signal and training data acquisition. Then, the virtual designed task with physics behavior and its development procedure are explained. Finally, the general architecture of the experimentation for the auto-adaptive therapy is presented using the classification method with the virtual reality exercise.

Design and Development of a Pneumatic Robot for Neurorehabilitation Therapies

This paper presents a new robotic system for upper limb rehabilitation. It is designed to assist the upper limb in therapies for both sitting and supine position, helping patients to carry out the required movements when they could not perform them. In the first part of the paper, the mechanical design and the development of the first prototype is exposed in detail. In the second part, new control strategy that modify the behavior of the rehabilitation robot according to different potential and force fields has been presented. Then, some experimental results of the performance of the implemented control with healthy subjects are reported.

Estimation of Human Arm Joints Using Two Wireless Sensors in Robotic Rehabilitation Tasks.

This paper presents a novel kinematic reconstruction of the human arm chain with five degrees of freedom and the estimation of the shoulder location during rehabilitation therapy assisted by end-effector robotic devices. This algorithm is based on the pseudoinverse of the Jacobian through the acceleration of the upper arm, measured using an accelerometer, and the orientation of the shoulder, estimated with a magnetic angular rate and gravity (MARG) device. The results show a high accuracy in terms of arm joints and shoulder movement with respect to the real arm measured through an optoelectronic system. Furthermore, the range of motion (ROM) of 50 healthy subjects is studied from two different trials, one trying to avoid shoulder movements and the second one forcing them. Moreover, the shoulder movement in the second trial is also estimated accurately. Besides the fact that the posture of the patient can be corrected during the exercise, the therapist could use the presented algorithm as an objective assessment tool. In conclusion, the joints’ estimation enables a better adjustment of the therapy, taking into account the needs of the patient, and consequently, the arm motion improves faster.

Multimodal robotic system for upper-limb rehabilitation in physical environment

This article researches the feasibility of use of a multimodal robotic system for upper-limb neurorehabilitation therapies in physical environments, interacting with real objects. This system consists of an end-effector upper-limb rehabilitation robot, a hand exoskeleton, a gaze tracking system, an object tracking system, and electromyographic measuring units. For this purpose, the system architecture is stated, explaining the detailed functions of each subsystem as well as the interaction among them. Finally, an experimental scenario is designed to test the system with healthy subjects in order to check whether the system is suitable for future experiments with patients.

Supervised and dynamic neuro-fuzzy systems to classify physiological responses in robot-assisted neurorehabilitation.

This paper presents the application of an Adaptive Resonance Theory (ART) based on neural networks combined with Fuzzy Logic systems to classify physiological reactions of subjects performing robot-assisted rehabilitation therapies. First, the theoretical background of a neuro-fuzzy classifier called S-dFasArt is presented. Then, the methodology and experimental protocols to perform a robot-assisted neurorehabilitation task are described. Our results show that the combination of the dynamic nature of S-dFasArt classifier with a supervisory module are very robust and suggest that this methodology could be very useful to take into account emotional states in robot-assisted environments and help to enhance and better understand human-robot interactions.

Implementation of 3D visualization aplications based on physical-haptics principles to perform rehabilitation tasks

Nowadays, There are a lot of tools and procedures for the development of computer applications for teaching, entertainment, telecommunications, marketing, design and other more. This paper present a implementation method for developing applications based on virtual reality and procedures physical-haptics, in order to perform rehabilitation tasks, describing the used software tools. The first one is Ogre3D which is used as rendering graphics engine to add realistic 3D visualization features. Then, the physical engine NVIDIA PhysX is used to incorporate accurate physics simulation and to implement collision detection between objects in the virtual environment. The third one is OpenHaptics which is used to generate a force feedback in the haptic device Sensable Phantom. Using the developed applications, the users immersion sense in the virtual environment is increased and improved, since the user can manipulate virtual objects with realistic physical behaviour. Finally, two examples of implementation in a rehabilitation environment are shown to demonstrate the main features of the developed tool.

Development of a robotic device for post-stroke home tele-rehabilitation:

This work deals with the complex mechanical design task of converting a large pneumatic rehabilitation robot into an electric and compact system for in-home post-stroke therapies without losing performance. It presents the new HomeRehab robot that supports rehabilitation therapies in three dimensions with an adaptive controller that optimizes patient recovery. A preliminary usability test is also conducted to show that its performance resembles that found in RoboTherapist 2D commercial system designed for hospitals. The mechanical design of a novel and smart two-dimensional force sensor at the end-effector is also described.

Integration of heterogeneous robotic systems in a surgical scenario

This paper defines what the authors named Modular Operating Room, as a heterogeneous system with different subsystems and devices that should interact between them in a surgical scenario. This is an evolution of the concept of Intelligent Operating Room, that has led us to large and expensive OR. The paper uses ROS to define a new package that manages the communications between different devices that can appear in a surgical scenario, in such a way that the real surgical scenario can be made with any combination of these devices. One simplified application consisting on the automatic insertion of an endoscopic camera on a trocar is shown as an example of integration.