Co-adaptive control strategies in assistive Brain-Machine Interfaces

A large number of people with severe motor disabilities cannot access any of the available control inputs of current assistive products, which typically rely on residual motor functions. These patients are therefore unable to fully benefit from existent assistive technologies, including communication interfaces and assistive robotics. In this context, electroencephalography-based Brain-Machine Interfaces (BMIs) offer a potential non-invasive solution to exploit a non-muscular channel for communication and control of assistive robotic devices, such as a wheelchair, a telepresence robot, or a neuroprosthesis. Still, non-invasive BMIs currently suffer from limitations, such as lack of precision, robustness and comfort, which prevent their practical implementation in assistive technologies. The goal of this PhD research is to produce scientific and technical developments to advance the state of the art of assistive interfaces and service robotics based on BMI paradigms. Two main research paths to the design of effective control strategies were considered in this project. The first one is the design of hybrid systems, based on the combination of the BMI together with gaze control, which is a long-lasting motor function in many paralyzed patients. Such approach allows to increase the degrees of freedom available for the control. The second approach consists in the inclusion of adaptive techniques into the BMI design. This allows to transform robotic tools and devices into active assistants able to co-evolve with the user, and learn new rules of behavior to solve tasks, rather than passively executing external commands. Following these strategies, the contributions of this work can be categorized based on the typology of mental signal exploited for the control. These include: 1) the use of active signals for the development and implementation of hybrid eyetracking and BMI control policies, for both communication and control of robotic systems; 2) the exploitation of passive mental processes to increase the adaptability of an autonomous controller to the user\u2019s intention and psychophysiological state, in a reinforcement learning framework; 3) the integration of brain active and passive control signals, to achieve adaptation within the BMI architecture at the level of feature extraction and classification

The mineralization of commercial organic fertilizers at 8°C temperature

In organic production only organic fertilizers and soil conditioners can be used to supply the soil with nitrogen. The mineralization of these products is slow and so there can be problems with the supply of nitrogen, when the demand of the plants is high. The supply of nitrogen from organic products depends on the speed of their mineralization which is primarily influenced by the composition and formulation of their raw material. In apple production in the Alps-region especially during spring problems with nitrogen supply are common. In that period, the weather conditions are sometimes bad, the temperature in the soil is low and mineralization starts slowly - apple trees demand more nitrogen than the soil can deliver. To compensate the demand of the apple tree organic growers can not use mineral fertilizers but only organic fertilizers and soil conditioners whose mineralization rate is often unknown. There is a strong need in organic fruit production to receive more information about the behaviour of fertilizers in the soil especially concerning their N-release under different conditions. To acquire that information, incubation experiments under controlled conditions (temperature, type of soil, humidity of the soil) were carried out in the laboratory to determine the mineralization-rate of different organic fertilizers and soil conditioners which are available in our region

Estudio comparativo de diferentes algoritmos de clustering para la estimación de grupos de evaluados que comparten debilidades conceptuales similares /

En esta investigación se busca hacer uso de algoritmos de clustering para agrupar evaluados que compartan debilidades conceptuales similares, y posteriormente, con base en los resultados, criterios de validación, pruebas estadísticas y análisis del comportamiento de los casos atípicos, determinar cuál es el mejor algoritmo. En este estudio comparativo es importante el análisis de casos atípicos pues representan el problema que será abordado.Incluye referencias bibliográfica

Cardiac Progenitor Cells from Stem Cells: Learning from Genetics and Biomaterials

Cardiac Progenitor Cells (CPCs) show great potential as a cell resource for restoring cardiac function in patients affected by heart disease or heart failure. CPCs are proliferative and committed to cardiac fate, capable of generating cells of all the cardiac lineages. These cells offer a significant shift in paradigm over the use of human induced pluripotent stem cell (iPSC)-derived cardiomyocytes owing to the latter's inability to recapitulate mature features of a native myocardium, limiting their translational applications. The iPSCs and direct reprogramming of somatic cells have been attempted to produce CPCs and, in this process, a variety of chemical and/or genetic factors have been evaluated for their ability to generate, expand, and maintain CPCs in vitro. However, the precise stoichiometry and spatiotemporal activity of these factors and the genetic interplay during embryonic CPC development remain challenging to reproduce in culture, in terms of efficiency, numbers, and translational potential. Recent advances in biomaterials to mimic the native cardiac microenvironment have shown promise to influence CPC regenerative functions, while being capable of integrating with host tissue. This review highlights recent developments and limitations in the generation and use of CPCs from stem cells, and the trends that influence the direction of research to promote better application of CPCs

Clinical assessment of the TechArm system on visually impaired and blind children during uni- and multi-sensory perception tasks

We developed the TechArm system as a novel technological tool intended for visual rehabilitation settings. The system is designed to provide a quantitative assessment of the stage of development of perceptual and functional skills that are normally vision-dependent, and to be integrated in customized training protocols. Indeed, the system can provide uni- and multisensory stimulation, allowing visually impaired people to train their capability of correctly interpreting non-visual cues from the environment. Importantly, the TechArm is suitable to be used by very young children, when the rehabilitative potential is maximal. In the present work, we validated the TechArm system on a pediatric population of low-vision, blind, and sighted children. In particular, four TechArm units were used to deliver uni- (audio or tactile) or multi-sensory stimulation (audio-tactile) on the participant's arm, and subject was asked to evaluate the number of active units. Results showed no significant difference among groups (normal or impaired vision). Overall, we observed the best performance in tactile condition, while auditory accuracy was around chance level. Also, we found that the audio-tactile condition is better than the audio condition alone, suggesting that multisensory stimulation is beneficial when perceptual accuracy and precision are low. Interestingly, we observed that for low-vision children the accuracy in audio condition improved proportionally to the severity of the visual impairment. Our findings confirmed the TechArm system's effectiveness in assessing perceptual competencies in sighted and visually impaired children, and its potential to be used to develop personalized rehabilitation programs for people with visual and sensory impairments