Browsing by Author "Zabaleta, Haritz"
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Item Absolute position calculation for a desktop mobile rehabilitation robot based on three optical mouse sensors(2011) Zabaleta, Haritz; Valencia, David; Perry, Joel; Veneman, Jan; Keller, Thierry; Tecnalia Research & InnovationArmAssist is a wireless robot for after stroke upper limb rehabilitation. In this paper, we describe a method based on artificial landmark navigation system. The navigation system is only based in three optical mouse sensors. This enables to build a cheap but reliable position sensor. Two of the sensors are the data source for odometry calculations, and the third optical mouse sensor takes very low resolution pictures of a custom designed mat. These pictures are processed by an optical symbol recognition algorithm which will estimate the orientation of the robot and recognize the landmarks placed on the mat. The data fusion strategy is described to detect the misclassifications of the landmarks in order to fuse only the reliable information. The orientation given by the OSR algorithm is used to improve significantly the odometry and the recognition of the landmarks is used to reference the odometry to a absolute coordinate systemItem Development of computer games for assessment and training in post-stroke arm telerehabilitation(2012) Rodriguez-De-Pablo, Cristina; Perry, Joel C.; Cavallaro, Francesca I.; Zabaleta, Haritz; Keller, Thierry; Tecnalia Research & InnovationStroke is the leading cause of long term disability among adults in industrialized nations. The majority of these disabilities include deficiencies in arm function, which can make independent living very difficult. Research shows that better results in rehabilitation are obtained when patients receive more intensive therapy. However this intensive therapy is currently too expensive to be provided by the public health system, and at home few patients perform the repetitive exercises recommended by their therapists. Computer games can provide an affordable, enjoyable, and effective way to intensify treatment, while keeping the patient as well as their therapists informed about their progress. This paper presents the study, design, implementation and user-testing of a set of computer games for at-home assessment and training of upper-limb motor impairment after stroke.Item A foot drop compensation device based on surface multi-field functional electrical stimulation—Usability study in a clinical environment(2019) Imatz-Ojanguren, Eukene; Sánchez-Márquez, Gema; Asiain-Aristu, Jose Ramón; Cueto-Mendo, Joxean; Jaunarena-Goicoechea, Edurne; Zabaleta, Haritz; Keller, Thierry; Tecnalia Research & InnovationFunctional electrical stimulation applies electrical pulses to the peripheral nerves to artificially achieve a sensory/motor function. When applied for the compensation of foot drop it provides both assistive and therapeutic effects. Multi-field electrodes have shown great potential but may increase the complexity of these systems. Usability aspects should be checked to ensure their success in clinical environments. We developed the Fesia Walk device, based on a surface multi-field electrode and an automatic calibration algorithm, and carried out a usability study to check the feasibility of integrating this device in therapeutic programs in clinical environments. The study included 4 therapists and 10 acquired brain injury subjects (8 stroke and 2 traumatic brain injury).Item Usability study of a device for compensation of foot drop based on FES and surface multi-field electrodes in a clinical environment(2017-07) Imatz-Ojanguren, Eukene; Sánchez-Márquez, Gema; Asiain-Aristu, Jose Ramón; Cueto-Mendo, Joxean; Jaunarena-Goicoechea, Edurne; Zabaleta, Haritz; Keller, Thierry; Tecnalia Research & InnovationFunctional Electrical Stimulation (FES) has shown successful assistive and rehabilitation effects in people affected by foot drop dysfunction caused by neurological disorders [1]. Still, FES-based foot drop devices are not present in regular therapy programs of many countries due to barriers caused by technological, usability or reliability issues [2]. FES devices based on surface multi-field electrodes bring new broader stimulation possibilities and features like compensation of eversion/inversion and thus, potentially increase the configuration options. In this study, the satisfaction and usability aspects of a multi-field based FES device were analyzed in a clinical environment. Method The FES device used in this study was the Fesia Walk device for compensation of foot drop, which is based on a multi-field surface electrode and an inertial sensor for gait phase detection. 10 acquired brain injury subjects in chronic stage and 4 therapists participated in the study. The therapists received a two-hour training session prior to the therapy sessions. Every subject was assigned to one therapist and received 3 sessions of habituation and 6 sessions of over ground walking with the Fesia Walk during three weeks. Both therapists and users were evaluated with the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST). Additionally, the therapists were evaluated with the System Usability Scale (SUS). An individual interview was carried out with each of the participants. Results The device received good scores in both the QUEST and SUS scales, with mean scores of 4.14 out of 5 and 85.6 out of 100 respectively. Furthermore, most users and all therapists showed interest to continue using the device after the study. Discussion and conclusions This usability study indicated that it is possible to include surface multi-field based FES devices for the compensation of foot drop in practical therapeutic programs and that they can be used as regular tools by therapists in clinical environments.Item Uso de redes neuro-borrosas RFNN para la aproximación del comportamiento de una neuroprótesis de antebrazo en pacientes con daño cerebral(2015-09) Imatz-Ojanguren, Eukene; Irigoyen Gordo, Eloy; Valencia Blanco, David; Zabaleta, Haritz; Keller, Thierry; Tecnalia Research & InnovationLas neuroprótesis son sistemas basados en la técnica de estimulación eléctrica funcional que provocan contracciones musculares mediante la excitación artificial de nervios periféricos, y son utilizadas para sustituir funciones motrices/sensoriales en aplicaciones tanto asistivas como terapéuticas. Este trabajo presenta la posibilidad de utilizar redes neuro-borrosas recurrentes para obtener modelos capaces de extraer las características principales del resultado de la aplicación de una neuroprótesis de miembro superior en distintos pacientes. Se ha entrenado una Recurrent Fuzzy Neural Network (RFNN) con datos reales obtenidos de pacientes crónicos de daño cerebral adquirido. Se han analizado distintas estrategias y estructuras y los resultados preliminares muestran la capacidad de estas redes de aprender las características principales de distintos sujetos y de proporcionar información fácilmente interpretable.