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Industry 4.0, smart homes, and the Internet of Things are boosting the employment of autonomous aerial vehicles in indoor environments, where localization is still challenging, especially in the case of close and cluttered areas. In this paper, we propose a Visual Inertial Odometry localization method based on fiducial markers. Our approach enables multi-rotor aerial vehicle navigation in indoor environments and tackles the most challenging aspects of image-based indoor localization. In particular, we focus on a proper and continuous pose estimation, working from take-off to landing, at several different flying altitudes. With this aim, we designed a map of fiducial markers that produces results that are both dense and heterogeneous. Narrowly placed tags lead to minimal information loss during rapid aerial movements while four different classes of marker size provide consistency when the camera zooms in or out according to the vehicle distance from the ground. We have validated our approach by comparing the output of the localization algorithm with the ground-truth information collected through an optoelectronic motion capture system, using two different platforms in different flying conditions. The results show that error mean and standard deviation can remain constantly lower than 0.11 m, so not degrading when the aerial vehicle increases its altitude and, therefore, strongly improving similar state-of-the-art solutions.
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Algoritmos , Movimiento , Altitud , Internet , Movimiento (Física)RESUMEN
The use of haptic devices in the rehabilitation of impaired limbs has become rather popular, given the proven effectiveness in promoting recovery. In a standard framework, such devices are used in rehabilitation centers, where patients interact with virtual tasks, presented on a screen. To track their sessions, kinematic/dynamic parameters or performance scores are recorded. However, as Internet access is now available at almost every home and in order to reduce the hospitalization time of the patient, the idea of doing rehabilitation at home is gaining wide consent. Medical care programs can be synchronized with the home rehabilitation device; patient data can be sent to the central server that could redirect to the therapist laptop (tele-healthcare). The controversial issue is that the recorded data do not actually represent the clinical conditions of the patients according to the medical assessment scales, forcing them to frequently undergo clinical tests at the hospital. To respond to this demand, we propose the use of a bilateral master/slave haptic system that could allow the clinician, who interacts with the master, to assess remotely and in real time the clinical conditions of the patient that uses the home rehabilitation device as the slave. In this paper, we describe a proof of concept to highlight the main issues of such an application, limited to one degree of freedom, and to the measure of the stiffness and range of motion of the hand.
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Tecnología de Sensores Remotos/métodos , Diseño de Equipo , Humanos , Rango del Movimiento Articular/fisiología , Telemedicina , Interfaz Usuario-ComputadorRESUMEN
Since its first experimental signatures, the so called "critical brain hypothesis" has been extensively studied. Yet, its actual foundations remain elusive. According to a widely accepted teleological reasoning, the brain would be poised to a critical state to optimize the mapping of the noisy and ever changing real-world inputs, thus suggesting that primary sensory cortical areas should be critical. We investigated whether a single barrel column of the somatosensory cortex of the anesthetized rat displays a critical behavior. Neuronal avalanches were recorded across all cortical layers in terms of both multi-unit activities and population local field potentials, and their behavior during spontaneous activity compared to the one evoked by a controlled single whisker deflection. By applying a maximum likelihood statistical method based on timeseries undersampling to fit the avalanches distributions, we show that neuronal avalanches are power law distributed for both multi-unit activities and local field potentials during spontaneous activity, with exponents that are spread along a scaling line. Instead, after the tactile stimulus, activity switches to a transient across-layers synchronization mode that appears to dominate the cortical representation of the single sensory input.
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Background. Haptic robots allow the exploitation of known motor learning mechanisms, representing a valuable option for motor treatment after stroke. The aim of this feasibility multicentre study was to test the clinical efficacy of a haptic prototype, for the recovery of hand function after stroke. Methods. A prospective pilot clinical trial was planned on 15 consecutive patients enrolled in 3 rehabilitation centre in Italy. All the framework features of the haptic robot (e.g., control loop, external communication, and graphic rendering for virtual reality) were implemented into a real-time MATLAB/Simulink environment, controlling a five-bar linkage able to provide forces up to 20 [N] at the end effector, used for finger and hand rehabilitation therapies. Clinical (i.e., Fugl-Meyer upper extremity scale; nine hold pegboard test) and kinematics (i.e., time; velocity; jerk metric; normalized jerk of standard movements) outcomes were assessed before and after treatment to detect changes in patients' motor performance. Reorganization of cortical activation was detected in one patient by fMRI. Results and Conclusions. All patients showed significant improvements in both clinical and kinematic outcomes. Additionally, fMRI results suggest that the proposed approach may promote a better cortical activation in the brain.