Publications by authors named "Maria Rubega"

Scoliosis is a three-dimensional spinal deformity characterized by a lateral deviation of at least 10° Cobb, categorized into idiopathic and non-idiopathic forms, caused by identifiable factors like congenital abnormalities, neuromuscular conditions, or genetic syndromes. This case report discusses a 15-year-old girl with growth delay and growth hormone (GH) deficiency who experienced rapid scoliosis progression. Initial evaluations were normal, and electroencephalography (EEG) showed nonspecific alterations, but further assessment revealed a MYH3 gene variant associated with scoliosis, short stature, and distinct facial features.

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Article Synopsis
  • Adolescent idiopathic scoliosis (AIS) is a common spinal deformity affecting around 4% of the global population, with research suggesting links to visual-spatial perception and sensory integration issues over the past 15 years.
  • A comprehensive review of 61 relevant studies revealed significant problems with standing balance in AIS patients, showing increased reliance on visual and proprioceptive cues, along with abnormal muscle activity and brain wave patterns.
  • Treatment with bracing appears to positively impact balance and gait in individuals with AIS, although the evidence is limited regarding other treatment options due to methodological inconsistencies in studies.
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Background: Adolescent idiopathic scoliosis (AIS) is the most common form of scoliosis. AIS is a three-dimensional morphological spinal deformity that affects approximately 1-3% of adolescents. Not all factors related to the etiology of AIS have yet been identified.

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Attentional biases toward body-related information increase body dissatisfaction. This can lead at-risk populations to develop psychopathologies. This phenomenon has not been extensively studied in girls affected by idiopathic scoliosis.

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Stroke recovery trajectories vary substantially. The need for tracking and prognostic biomarkers in stroke is utmost for prognostic and rehabilitative goals: electroencephalography (EEG) advanced signal analysis may provide useful tools toward this aim. EEG microstates quantify changes in configuration of neuronal generators of short-lasting periods of coordinated synchronized communication within large-scale brain networks: this feature is expected to be impaired in stroke.

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Robot-aided gait training (RAGT) plays a crucial role in providing high-dose and high-intensity task-oriented physical therapy. The human-robot interaction during RAGT remains technically challenging. To achieve this aim, it is necessary to quantify how RAGT impacts brain activity and motor learning.

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Pathophysiology of Adolescent Idiopathic Scoliosis (AIS) is not yet completely understood. This exploratory study aims to investigate two aspects neglected in clinical practice: a defective postural central nervous system control in AIS, and alterations of body schema due to scoliosis spinal deformities. We recorded EEG data and balance data in four different standing positions in 14 adolescents with AIS and in 14 controls.

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Stage 2 sleep spindles are considered useful biomarkers for the integrity of the central nervous system and for cognitive and memory skills. We investigated sleep spindles patterns in subjects after 12 months of their hospitalization in the intensive care unit (ICU) of the Padova Teaching Hospital due to COVID-19 between March and November 2020. Before the nap, participants (13 hospitalized in ICU - ICU; 9 hospitalized who received noninvasive ventilation - nonlCU; 9 age and sex-matched healthy controls - CTRL, i.

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Background: Brain-computer interfaces (BCIs) are systems capable of translating human brain patterns, measured through electroencephalography (EEG), into commands for an external device. Despite the great advances in machine learning solutions to enhance the performance of BCI decoders, the translational impact of this technology remains elusive. The reliability of BCIs is often unsatisfactory for end-users, limiting their application outside a laboratory environment.

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Severe acute respiratory syndrome coronavirus 2 is a worldwide public health issue. Almost 2 years into the pandemic, the persistence of symptoms after the acute phase is a well-recognized phenomenon. We conducted a scoping review to map cognitive domain impairments, their frequency, and associated psycho-affective disorders in people with a previous COVID-19 infection.

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Objective: To disentangle the pathophysiology of cognitive/affective impairment in Coronavirus Disease-2019 (COVID-19), we studied long-term cognitive and affective sequelae and sleep high-density electroencephalography (EEG) at 12-month follow-up in people with a previous hospital admission for acute COVID-19.

Methods: People discharged from an intensive care unit (ICU) and a sub-intensive ward (nonICU) between March and May 2020 were contacted between March and June 2021. Participants underwent cognitive, psychological, and sleep assessment.

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The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural connectivity (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors.

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The main objective of this study is to test the effect of thermal aquatic exercise on motor symptoms and quality of life in people with Parkinson's Disease (PD). Fourteen participants with diagnosis of idiopathic PD completed the whole rehabilitation session and evaluation protocol (Hoehn and Yahr in OFF state: 2-3; Mini Mental State Examination >24; stable pharmacological treatment in the 3 months prior participating in the study). Cognitive and motor status, functional abilities and quality of life were assessed at baseline and after an intensive rehabilitation program in thermal water (12 sessions of 45 min in a 1.

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The body sway during standing displays fractal properties that can possibly describe motion complexity. This study aimed to use the Higuchi's fractal dimension (HFD) and Tortuosity on lower back accelerations recorded on younger (< 35 y) and older adults (> 64 y). One wearable sensor was secured on participants lower back (i.

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Standing and concurrently performing a cognitive task is a very common situation in everyday life. It is associated with a higher risk of falling in the elderly. Here, we aim at evaluating the differences of the P300 evoked potential elicited by a visual oddball paradigm between healthy younger (< 35 y) and older (> 64 y) adults during a simultaneous postural task.

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Fast rhythms excess is a hallmark of Parkinson's Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls.

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Exoskeleton gait rehabilitation is an emerging area of research, with potential applications in the elderly and in people with central nervous system lesions, e.g., stroke, traumatic brain/spinal cord injury.

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Falls are the second most frequent cause of injury in the elderly. Physiological processes associated with aging affect the elderly's ability to respond to unexpected balance perturbations, leading to increased fall risk. Every year, approximately 30% of adults, 65 years and older, experiences at least one fall.

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Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals.

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Falls due to balance impairment are a major cause of injury and disability in the elderly. The study of neurophysiological correlates during static and dynamic balance tasks is an emerging area of research that could lead to novel rehabilitation strategies and reduce fall risk. This review aims to highlight key concepts and identify gaps in the current knowledge of balance control in the elderly that could be addressed by relying on surface electromyographic (EMG) and electroencephalographic (EEG) recordings.

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Previous literature has demonstrated that hypoglycemic events in patients with type 1 diabetes (T1D) are associated with measurable scalp electroencephalography (EEG) changes in power spectral density. In the present study, we used a dataset of 19-channel scalp EEG recordings in 34 patients with T1D who underwent a hyperinsulinemic-hypoglycemic clamp study. We found that hypoglycemic events are also characterized by EEG complexity changes that are quantifiable at the single-channel level through empirical conditional and permutation entropy and fractal dimension indices, i.

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Fibromyalgia syndrome (FMS) is a complex pain disorder, characterized by diffuse pain and cognitive disturbances. Abnormal cortical oscillatory activity may be a promising biomarker, encouraging non-invasive neurostimulation techniques as a treatment. We aimed to modulate abnormal slow cortical oscillations by delivering transcranial alternating current stimulation (tACS) and physiotherapy to reduce pain and cognitive symptoms.

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