Publications by authors named "F Di Rienzo"

Low vitamin D (VD) has been associated with poor clinical course in several neurological diseases. Supplementation has been suggested to improve outcomes. Severe acquired brain injury (sABI) subjects have low VD levels and disabling conditions requiring rehabilitation.

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The effectiveness of motor imagery (MI) training on sports performance is now well-documented. Recently, it has been proposed that a single session of MI combined with low frequency sound (LFS) might enhance muscle activation. However, the neural mechanisms underlying this effect remain unknown.

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Auditory beats stimulation (ABS) has received increased attention for its potential to modulate neural oscillations through a phenomenon described as brain entrainment (i.e synchronization of brain's electrocortical activity to external stimuli at a specific frequency). Recently, a new form of ABS has emerged, inspired by isochronic tones stimulation (IT).

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Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices' performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices.

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Article Synopsis
  • Limb movement direction can be predicted from local field potentials in the motor cortex during both planning and execution phases of movement.
  • A study used machine learning on intracranial EEG data from epilepsy patients performing a motor task, revealing that low-frequency power is crucial for predicting movement direction during planning, while higher frequencies and low-frequency phase play a significant role during execution.
  • The research also found that Phase-Amplitude Coupling was consistently modulated across different movement directions and achieved over 80% accuracy in distinguishing intended hand movements using multivariate classification techniques.
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