Preterm infants' limb-pose estimation from depth images using convolutional neural networks

Preterm infants' limb-pose estimation is a crucial but challenging task, which may improve patients' care and facilitate clinicians in infant's movements monitoring. Work in the literature either provides approaches to whole-body segmentation and tracking, which, however, has poor clinical value, or retrieve a posteriori limb pose from limb segmentation, increasing computational costs and introducing inaccuracy sources. In this paper, we address the problem of limb-pose estimation under a different point of view. We proposed a 2D fully-convolutional neural network for roughly detecting limb joints and joint connections, followed by a regression convolutional neural network for accurate joint and joint-connection position estimation. Joints from the same limb are then connected with a maximum bipartite matching approach. Our analysis does not require any prior modeling of infants' body structure, neither any manual interventions. For developing and testing the proposed approach, we built a dataset of four videos (video length = 90 s) recorded with a depth sensor in a neonatal intensive care unit (NICU) during the actual clinical practice, achieving median root mean square distance [pixels] of 10.790 (right arm), 10.542 (left arm), 8.294 (right leg), 11.270 (left leg) with respect to the ground-truth limb pose. The idea of estimating limb pose directly from depth images may represent a future paradigm for addressing the problem of preterm-infants' movement monitoring and offer all possible support to clinicians in NICUs

Are supramodality and cross-modal plasticity the yin and yang of brain development? From blindness to rehabilitation

Research in blind individuals has primarily focused for a long time on the brain plastic reorganization that occurs in early visual areas. Only more recently, scientists have developed innovative strategies to understand to what extent vision is truly a mandatory prerequisite for the brain’s fine morphological architecture to develop and function. As a whole, the studies conducted to date in sighted and congenitally blind individuals have provided ample evidence that several ‘visual’ cortical areas develop independently from visual experience and do process information content regardless of the sensory modality through which a particular stimulus is conveyed: a property named supramodality. At the same time, lack of vision leads to a structural and functional reorganization within 'visual' brain areas, a phenomenon known as cross-modal plasticity. Cross-modal recruitment of the occipital cortex in visually deprived individuals represents an adaptative compensatory mechanism that mediates processing of non-visual inputs. Supramodality and cross-modal plasticity appear to be the 'yin and yang' of brain development: supramodal is what takes place despite the lack of vision, whereas cross-modal is what happens because of lack of vision. Here we provide a critical overview of the research in this field and discuss the implications that these novel findings have for the development of educative/rehabilitation approaches and sensory substitution devices in sensory-impaired individuals

The babyPose dataset

none5noThe database here described contains data relevant to preterm infants' movement acquired in neonatal intensive care units (NICUs). The data consists of 16 depth videos recorded during the actual clinical practice. Each video consists of 1000 frames (i.e., 100s). The dataset was acquired at the NICU of the Salesi Hospital, Ancona (Italy). Each frame was annotated with the limb-joint location. Twelve joints were annotated, i.e., left and right shoul- der, elbow, wrist, hip, knee and ankle. The database is freely accessible at http://doi.org/10.5281/zenodo.3891404. This dataset represents a unique resource for artificial intelligence researchers that want to develop algorithms to provide healthcare professionals working in NICUs with decision support. Hence, the babyPose dataset is the first annotated dataset of depth images relevant to preterm infants' movement analysis.openMigliorelli L.; Moccia S.; Pietrini R.; Carnielli V.P.; Frontoni E.Migliorelli, L.; Moccia, S.; Pietrini, R.; Carnielli, V. P.; Frontoni, E

On the observed distributions of black hole masses and Eddington ratios from radiation pressure corrected virial indicators

The application of the virial theorem to the Broad Line Region of Active Galactic Nuclei allows Black Hole mass estimates for large samples of objects at all redshifts. In a recent paper we showed that ionizing radiation pressure onto BLR clouds affects virial BH mass estimates and we provided empirically calibrated corrections. More recently, a new test of the importance of radiation forces has been proposed: the MBH-sigma relation has been used to estimate MBH for a sample of type-2 AGN and virial relations (with and without radiation pressure) for a sample of type-1 AGN extracted from the same parent population. The observed L/LEdd distribution based on virial BH masses is in good agreement with that based on MBH-sigma only if radiation pressure effects are negligible, otherwise significant discrepancies are observed. In this paper we investigate the effects of intrinsic dispersions associated to the virial relations providing MBH, and we show that they explain the discrepancies between the observed L/LEdd distributions of type-1 and type-2 AGN. These discrepancies in the L/LEdd distributions are present regardless of the general importance of radiation forces, which must be negligible only for a small fraction of sources with large L/LEdd. Average radiation pressure corrections should then be applied in virial MBH estimators until their dependence on observed source physical properties has been fully calibrated. Finally, the comparison between MBH and L/LEdd distributions derived from sigma-based and virial estimators can constrain the variance of BLR physical properties in AGN.Comment: Astrophysical Journal Letters, in pres

EEG frequency-tagging demonstrates increased left hemispheric involvement and crossmodal plasticity for face processing in congenitally deaf signers

In humans, face-processing relies on a network of brain regions predominantly in the right occipito-temporal cortex. We tested congenitally deaf (CD) signers and matched hearing controls (HC) to investigate the experience dependence of the cortical organization of face processing. Specifically, we used EEG frequency-tagging to evaluate: (1) Face-Object Categorization, (2) Emotional Facial-Expression Discrimination and (3) Individual Face Discrimination. The EEG was recorded to visual stimuli presented at a rate of 6 Hz, with oddball stimuli at a rate of 1.2 Hz. In all three experiments and in both groups, significant face discriminative responses were found. Face-Object categorization was associated to a relative increased involvement of the left hemisphere in CD individuals compared to HC individuals. A similar trend was observed for Emotional Facial-Expression discrimination but not for Individual Face Discrimination. Source reconstruction suggested a greater activation of the auditory cortices in the CD group for Individual Face Discrimination. These findings suggest that the experience dependence of the relative contribution of the two hemispheres as well as crossmodal plasticity vary with different aspects of face processing

It's not all in your car: functional and structural correlates of exceptional driving skills in professional racers.

Driving is a complex behavior that requires the integration of multiple cognitive functions. While many studies have investigated brain activity related to driving simulation under distinct conditions, little is known about the brain morphological and functional architecture in professional competitive driving, which requires exceptional motor and navigational skills. Here, 11 professional racing-car drivers and 11 "naïve" volunteers underwent both structural and functional brain magnetic resonance imaging (MRI) scans. Subjects were presented with short movies depicting a Formula One car racing in four different official circuits. Brain activity was assessed in terms of regional response, using an Inter-Subject Correlation (ISC) approach, and regional interactions by mean of functional connectivity. In addition, voxel-based morphometry (VBM) was used to identify specific structural differences between the two groups and potential interactions with functional differences detected by the ISC analysis. Relative to non-experienced drivers, professional drivers showed a more consistent recruitment of motor control and spatial navigation devoted areas, including premotor/motor cortex, striatum, anterior, and posterior cingulate cortex and retrosplenial cortex, precuneus, middle temporal cortex, and parahippocampus. Moreover, some of these brain regions, including the retrosplenial cortex, also had an increased gray matter density in professional car drivers. Furthermore, the retrosplenial cortex, which has been previously associated with the storage of observer-independent spatial maps, revealed a specific correlation with the individual driver's success in official competitions. These findings indicate that the brain functional and structural organization in highly trained racing-car drivers differs from that of subjects with an ordinary driving experience, suggesting that specific anatomo-functional changes may subtend the attainment of exceptional driving performance

Implementation of the Damages Directive in England & Wales

The Dossier discusses the questions arising from the need to implement the EU Damages Directive 2014/104/EU in several European Member States. My contribution focuses on the need for implementation in England & Wales