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Publicación Acceso Abierto Passive exercise adaptation for ankle rehabilitation based on learning control framework(MDPI AG, 2020-09-01) Abu Dakka, F.J.; Valera, A.; Escalera, J.A.; Abderrahim, M.; Page, A.; Mata, V.; Ministerio de Economía y Competitividad (MINECO)Ankle injuries are among the most common injuries in sport and daily life. However, for their recovery, it is important for patients to perform rehabilitation exercises. These exercises are usually done with a therapist’s guidance to help strengthen the patient’s ankle joint and restore its range of motion. However, in order to share the load with therapists so that they can offer assistance to more patients, and to provide an efficient and safe way for patients to perform ankle rehabilitation exercises, we propose a framework that integrates learning techniques with a 3-PRS parallel robot, acting together as an ankle rehabilitation device. In this paper, we propose to use passive rehabilitation exercises for dorsiflexion/plantar flexion and inversion/eversion ankle movements. The therapist is needed in the first stage to design the exercise with the patient by teaching the robot intuitively through learning from demonstration. We then propose a learning control scheme based on dynamic movement primitives and iterative learning control, which takes the designed exercise trajectory as a demonstration (an input) together with the recorded forces in order to reproduce the exercise with the patient for a number of repetitions defined by the therapist. During the execution, our approach monitors the sensed forces and adapts the trajectory by adding the necessary offsets to the original trajectory to reduce its range without modifying the original trajectory and subsequently reducing the measured forces. After a predefined number of repetitions, the algorithm restores the range gradually, until the patient is able to perform the originally designed exercise. We validate the proposed framework with both real experiments and simulation using a Simulink model of the rehabilitation parallel robot that has been developed in our lab.Publicación Acceso Abierto Label-free optical biosensing using low-cost electrospun polymeric nanofibers(MDPI Ag, 2020-12) Martínez Pérez, P.; Ponce Alcántara, S.; Murillo, Nieves; Pérez Márquez, A.; Maudes, J.; González López, L.; Gil García, M.; Lorenzo Lozano, P.; García Rupérez, J.; Peraile, Inés; Generalitat Valenciana (GVA); Ministerio de Economía y Competitividad (MINECO); Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737Polymeric nanofiber matrices are promising structures to develop biosensing devices due to their easy and affordable large-scale fabrication and their high surface-to-volume ratio. In this work, the suitability of a polyamide 6 nanofiber matrix for the development of a label-free and real-time Fabry–Pérot cavity-based optical biosensor was studied. For such aim, in-flow biofunctionalization of nanofibers with antibodies, bound through a protein A/G layer, and specific biodetection of 10 µg/mL bovine serum albumin (BSA) were carried out. Both processes were successfully monitored via reflectivity measurements in real-time without labels and their reproducibility was demonstrated when different polymeric nanofiber matrices from the same electrospinning batch were employed as transducers. These results demonstrate not only the suitability of correctly biofunctionalized polyamide 6 nanofiber matrices to be employed for real-time and label-free specific biodetection purposes, but also the potential of electrospinning technique to create affordable and easy-to-fabricate at large scale optical transducers with a reproducible performance.
