241 research outputs found

    One year follow up of spinal cord injury patients using a reciprocating gait orthosis: Preliminary results

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    One year follow up of spinal cord injury patients using a reciprocating gait orthosis: preliminary report. Scivoletto G, Petrelli A, Lucente LD, Giannantoni A, Fuoco U, D'Ambrosio F, Filippini V. Source Spinal Cord Unit, I.R.C.C.S., S. Lucia, via Ardeatina 306, 00179 - Rome, Italy. Abstract OBJECTIVE: To examine the influence of social, physical and psychological factors in determining the usage/non usage of reciprocating gait orthosis (RGO) in spinal cord injury (SCI) patients. DESIGN: Prospective clinical trial. SETTING: A large rehabilitation hospital in Rome, Italy. PARTICIPANTS: Twenty four SCI patients of traumatic aetiology (all fulfilling the criteria to prescribe the device). Methods: Social, physical and neurological examination according to ASIA standards; psychological enquiry by means of the Eysenck Personality Questionnaire (EPQ) and the scale for self rating anxiety and depression of the Cognitive Behavioural Assessment. RESULTS: After 1 year follow up 11 (46%) of our patients no longer used the RGO. There was no statistically significant difference between patients who used the RGO and those who rejected the orthosis with regard to social and physical data. There was a significant difference (P=0.005 at the end of training and P=0.003 at 1 year follow up) with regard to functional ambulation level. With regard to psychological enquiry RGO-non users showed a higher frequency of values over the mean in the E scale (extroversion) of the EPQ than RGO-users (P=0.05). CONCLUSIONS: None of the identified parameters were useful to predict the use/rejection of the orthosis. Although they need to be confirmed, our psychological data suggest that extensive psychological testing could be useful to sharpen the ability to predict

    Restoring tactile awareness through the rubber hand illusion in cervical spinal cord injury

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    BACKGROUND Bodily sensations are an important component of corporeal awareness. Spinal cord injury can leave affected body parts insentient and unmoving, leading to specific disturbances in the mental representation of one's own body and the sense of self. OBJECTIVE Here, we explored how illusions induced by multisensory stimulation influence immediate sensory signals and tactile awareness in patients with spinal cord injuries. METHODS The rubber hand illusion paradigm was applied to 2 patients with chronic and complete spinal cord injury of the sixth cervical spine, with severe somatosensory impairments in 2 of 5 fingers. RESULTS Both patients experienced a strong illusion of ownership of the rubber hand during synchronous, but not asynchronous, stroking. They also, spontaneously reported basic tactile sensations in their previously numb fingers. Tactile awareness from seeing the rubber hand was enhanced by progressively increasing the stimulation duration. CONCLUSIONS Multisensory illusions directly and specifically modulate the reemergence of sensory memories and enhance tactile sensation, despite (or as a result of) prior deafferentation. When sensory inputs are lost, and are later illusorily regained, the brain updates a coherent body image even several years after the body has become permanently unable to feel. This particular example of neural plasticity represents a significant opportunity to strengthen the sense of the self and the feelings of embodiment in patients with spinal cord injury

    Robust Image Stitching and Reconstruction of Rolling Stocks Using a Novel Kalman Filter With a Multiple-Hypothesis Measurement Model

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    This work introduces a novel algorithm for the reconstruction of rolling stocks from a sequence of images. The research aims at producing an accurate and wide image model that can be used as a Digital Twin (DT) for diagnosis, fault prediction, maintenance, and other monitoring operations. When observing large surfaces with nearly constant textures, metallic reflections, and repetitive patterns, motion estimation algorithms based on whole image error minimization and feature pairing with Random Sampling and Consensus (RANSAC) or Least Median of Squares (LMedS) fail to provide appropriate associations. To overcome such an issue, we propose a custom Kalman Filter (KF) modified by adding multiple input-noise sources represented as a Gaussian mixture distribution (GM), and specific algorithms to select appropriate data and variance to use for state prediction and correction. The proposed algorithm has been tested on images of train vessels, having a high number of windows, and large metallic paintings with constant or repetitive patterns. The approach here presented showed to be robust in the presence of high environmental disturbances and a reduced number of features. A large set of rolling stocks has been collected during a six months campaign. The set was employed to demonstrate the validity of the proposed algorithm by comparing the reconstructed twin versus known data. The system showed an overall accuracy in length estimation above 99%
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