The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain–machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton—without any weight or balance support—for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation).
Curricula designed in the context of the European Higher Education Area need to be based on both domain-specific and professional competencies. Whereas universities have had extensive experience in developing students' domain-specific competencies, fostering professional competencies poses a new challenge we need to face. This paper presents a model to globally develop professional competencies in a STEM degree program, and assesses the results of its implementation after four years. The model is based on the use of competency maps, in which each competency is defined in terms of competency units. Each competency unit is described by their expected learning outcomes at three domain levels. This model allows careful analysis, revision and iteration for an effective integration of professional competencies in domain-specific subjects. A global competency map is also designed, including all the professional-competency learning outcomes to be achieved throughout the degree. This map becomes a useful tool for curriculum designers and coordinators. The results were obtained from four sources: 1) students' grades (classes graduated from 2013 to 2016, the first four years from the new Bachelor's Degree in Informatics Engineering at the Barcelona School of Informatics); 2) students' surveys (answered by students when they finished the degree); 3) the government employment survey, where former students evaluate the satisfaction of the received training in the light of their work experience; and 4) the Everis Foundation University-Enterprise Ranking, answered by over 2000 employers evaluating their satisfaction regarding their employees' university training, where the Barcelona School of Informatics scores first in the national ranking. The results show that competency maps are a good tool for developing professional competencies in a STEM degree.
Wearable robots are expected to expand the use of robotics in rehabilitation since they can widen the assistance application context. An important aspect of a rehabilitation therapy, in terms of lower extremity assistance, is balance control. In this article, we propose and evaluate an adaptive control strategy for robotic rehabilitation therapies to guarantee static stability using a wearable robot. Postural balance control can be implemented either acting on the hip, on the ankle joint or on both, depending on the kind of perturbation acting on the subject: internal or external. Internal perturbations can be produced by any voluntary movement of the body, such as bending the trunk. External perturbations, in the form of an impact force, are applied by the exoskeleton without any prior notice to observe the proactive response of the subject. We have used a 6 degree of freedom planar lower limb exoskeleton, H1, to perform this analysis. The developed control strategy has been designed to provide the necessary assistance, related to balance recovery and postural stability, under the ‘‘Assist-as-needed’’ paradigm. The interaction forces\ud between orthosis and subject are monitored, as they play a relevant role in the definition of assistive and resistive movements to be applied to the joints. The proposed method has been tested with 5 healthy subjects in presence of internal and external disturbances. The results demonstrate that knowing the stability limit of each subject, in combination with a therapeutically selected scaling factor, the proposed\ud adaptive control helps in providing an effective assistance in therapy. This method is efficient in handling the individual and combined effect of external perturbations acting on any joint movements.Peer ReviewedPostprint (author’s final draft
Abstract-An assistive rehabilitation strategy for a lowerlimb wearable robot is proposed and evaluated. The control strategy monitors the human-orthosis interaction torques and modifies the orthosis operation mode depending on its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints stiffness in function of these interaction torques and to the deviation from the desired trajectory. A walking pattern, an average of recorded gaits, is used as reference input. The human-orthosis interaction torques are used to define the time instant when robot assistance is needed and its degree. The objective of this work is to demonstrate the feasibility of ensuring a dynamic stability by means of an efficient real-time stiffness adaptation for multiple joints and simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from Spinal cord injury and Stroke.
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