Validation of SuPerSense, a Sensorized Surface for the Evaluation of Posture Perception in Supine Position.

This study aimed to validate a sensorized version of a perceptive surface that may be used for the early assessment of misperception of body midline representation in subjects with right stroke, even when they are not yet able to stand in an upright posture. This device, called SuPerSense, allows testing of the load distribution of the body weight on the back in a supine position. The device was tested in 15 patients with stroke, 15 age-matched healthy subjects, and 15 young healthy adults, assessing three parameters analogous to those conventionally extracted by a baropodometric platform in a standing posture.

Mobile applications in otolaryngology for patients: An update.

Objective: Recently smartphones and tablets have spread in developed countries, and healthcare-related apps are growing incredibly in different specialties. The aim of this study is to provide an up-to-date review of the current OtoHNS (otolaryngology-head and neck surgery) apps developed for patients.

Methods: This mobile applications review was conducted in September 2017.

Depression disorder in patients with cerebellar damage: Awareness of the mood state.

Background: Although depressive symptoms are often reported to be comorbid with degenerative cerebellar diseases, the role of the cerebellum in depressive disorder needs to be elucidated. To address this aim, we investigated self-perception of the negative mood state in patients with cerebellar pathology and depressive symptoms.

Methods: Thirty-eight patients with cerebellar damage (10 with depressive symptoms - CB-DP and 28 with no depressive symptoms - CB-nDP), 11 subjects with depressive disorders without cerebellar damage (DP) and 29 healthy controls (CTs) were enrolled.

New protocol for dissociating visuospatial working memory ability in reaching space and in navigational space.

Several studies have demonstrated that the processing of visuospatial memory for locations in reaching space and in navigational space is supported by independent systems, and that the coding of visuospatial information depends on the modality of the presentation (i.e., sequential or simultaneous).

Hybrid P300-based brain-computer interface to improve usability for people with severe motor disability: electromyographic signals for error correction during a spelling task.

Objective: To evaluate the impact of a hybrid control on usability of a P300-based brain-computer interface (BCI) system that was designed to control an assistive technology software and was integrated with an electromyographic channel for error correction.

Design: Proof-of-principle study with a convenience sample.

Setting: Neurologic rehabilitation hospital.

Monitoring mood states in everyday life: a new device for patients with cerebellar ataxia.

Thirty patients with cerebellar ataxia and 40 healthy volunteers underwent 7 days of mood monitoring using a new device requiring a low motor load. Its convergent validity and compliance were tested. The measurements resulted consistent with validated scale scores.

Asynchronous gaze-independent event-related potential-based brain-computer interface.

Objective: In this study a gaze independent event related potential (ERP)-based brain computer interface (BCI) for communication purpose was combined with an asynchronous classifier endowed with dynamical stopping feature. The aim was to evaluate if and how the performance of such asynchronous system could be negatively affected in terms of communication efficiency and robustness to false positives during the intentional no-control state.

Material And Methods: The proposed system was validated with the participation of 9 healthy subjects.

On the control of brain-computer interfaces by users with cerebral palsy.

Objective: Brain-computer interfaces (BCIs) have been proposed as a potential assistive device for individuals with cerebral palsy (CP) to assist with their communication needs. However, it is unclear how well-suited BCIs are to individuals with CP. Therefore, this study aims to investigate to what extent these users are able to gain control of BCIs.

Control or no-control? Reducing the gap between brain-computer interface and classical input devices.

In order to improve Brain Computer Interface usability for real life context, they should be able to adapt their speed to the user's current psychophysical state and to understand from the ongoing EEG when he/she intends to suspend the control. In this work we evaluated an asynchronous classifier which provides these feature with 20 healthy subjects, who were engaged in an environmental control task or in a spelling task. We also demonstrated how the proposed classifier can improve communication efficiency with respect to classical synchronous classifiers.

A covert attention P300-based brain-computer interface: Geospell.

Unlabelled: The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention.

Smart homes to improve the quality of life for all.

A home is smart when, being aware of its own state and that of its users, is capable of controlling itself in order to support the user wishes and thus improving their quality of life. This holds both for users with special needs and for those with ordinary domestic needs. In this paper, we overview the Smart Homes for All project which represents the current state of the art with respect to software control and user interfaces in the smart homes arena.

Asynchronous P300-based brain-computer interface to control a virtual environment: initial tests on end users.

Motor disability and/or ageing can prevent individuals from fully enjoying home facilities, thus worsening their quality of life. Advances in the field of accessible user interfaces for domotic appliances can represent a valuable way to improve the independence of these persons. An asynchronous P300-based Brain-Computer Interface (BCI) system was recently validated with the participation of healthy young volunteers for environmental control.

Accuracy of a P300 speller for people with motor impairments: a comparison.

A Brain-Computer Interface (BCI) provides a completely new output pathway that can provide an additional option for a person to express himself/herself if he/she suffers a disorder like amyotrophic lateral sclerosis (ALS), brainstem stroke, brain or spinal cord injury or other diseases which impair the function of the common output pathways which are responsible for the control of muscles. For a P300 based BCI a matrix of randomly flashing characters is presented to the participant. To spell a character the person has to attend to it and to count how many times the character flashes.

On the use of EEG or MEG brain imaging tools in neuromarketing research.

Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies.

Out of the frying pan into the fire--the P300-based BCI faces real-world challenges.

Brain-computer interfaces (BCIs) have been investigated for more than 20 years. Many BCIs use noninvasive electroencephalography as a measurement technique and the P300 event-related potential as an input signal (P300 BCI). Since the first experiment with a P300 BCI system in 1988 by Farwell and Donchin, not only data processing has improved but also stimuli presentation has been varied and a plethora of applications was developed and refined.

Patterns of cortical activity during the observation of Public Service Announcements and commercial advertisings.

Background: In the present research we were interested to study the cerebral activity of a group of healthy subjects during the observation a documentary intermingled by a series of TV advertisements. In particular, we desired to examine whether Public Service Announcements (PSAs) are able to elicit a different pattern of activity, when compared with a different class of commercials, and correlate it with the memorization of the showed stimuli, as resulted from a following subject's verbal interview.

Methods: We recorded the EEG signals from a group of 15 healthy subjects and applied the High Resolution EEG techniques in order to estimate and map their Power Spectral Density (PSD) on a realistic cortical model.

EEG analysis of the brain activity during the observation of commercial, political, or public service announcements.

The use of modern brain imaging techniques could be useful to understand what brain areas are involved in the observation of video clips related to commercial advertising, as well as for the support of political campaigns, and also the areas of Public Service Announcements (PSAs). In this paper we describe the capability of tracking brain activity during the observation of commercials, political spots, and PSAs with advanced high-resolution EEG statistical techniques in time and frequency domains in a group of normal subjects. We analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects.

The study of brain activity during the observation of commercial advertising by using high resolution EEG techniques.

In this paper we illustrate the capability of tracking brain activity during the observation of commercial TV spots by using advanced high resolution EEG statistical techniques in time and frequency domains. In particular, we analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the prime minister of Italy was analyzed in two groups of swing and "supporter" voters.

The track of brain activity during the observation of TV commercials with the high-resolution EEG technology.

We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In particular, we recover statistically significant information about cortical areas engaged by particular scenes inserted within the TV commercial proposed with respect to the brain activity estimated while watching a documentary.

Non-invasive brain-computer interface system: towards its application as assistive technology.

The quality of life of people suffering from severe motor disabilities can benefit from the use of current assistive technology capable of ameliorating communication, house-environment management and mobility, according to the user's residual motor abilities. Brain-computer interfaces (BCIs) are systems that can translate brain activity into signals that control external devices. Thus they can represent the only technology for severely paralyzed patients to increase or maintain their communication and control options.

Vibrotactile feedback for brain-computer interface operation.

To be correctly mastered, brain-computer interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications.

Modern electrophysiological methods for brain-computer interfaces.

Modern electrophysiological studies in animals show that the spectrum of neural oscillations encoding relevant information is broader than previously thought and that many diverse areas are engaged for very simple tasks. However, EEG-based brain-computer interfaces (BCI) still employ as control modality relatively slow brain rhythms or features derived from preselected frequencies and scalp locations. Here, we describe the strategy and the algorithms we have developed for the analysis of electrophysiological data and demonstrate their capacity to lead to faster accurate decisions based on linear classifiers.

Preliminary experimentation on vibrotactile feedback in the context of mu-rhythm based BCI.

Brain-Computer Interfaces (BCIs) need an uninterrupted flow of feedback to the user, which is usually delivered through the visual channel. Our aim is to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications. An experimental setup for delivery of vibrotactile feedback, including specific hardware and software arrangements, was specified.

Non-invasive brain-computer interface system to operate assistive devices.

In this pilot study, a system that allows disabled persons to improve or recover their mobility and communication within the surrounding environment was implemented and validated. The system is based on a software controller that offers to the user a communication interface that is matched with the individual's residual motor abilities. Fourteen patients with severe motor disabilities due to progressive neurodegenerative disorders were trained to use the system prototype under a rehabilitation program.

High-resolution EEG techniques for brain-computer interface applications.

High-resolution electroencephalographic (HREEG) techniques allow estimation of cortical activity based on non-invasive scalp potential measurements, using appropriate models of volume conduction and of neuroelectrical sources. In this study we propose an application of this body of technologies, originally developed to obtain functional images of the brain's electrical activity, in the context of brain-computer interfaces (BCI). Our working hypothesis predicted that, since HREEG pre-processing removes spatial correlation introduced by current conduction in the head structures, by providing the BCI with waveforms that are mostly due to the unmixed activity of a small cortical region, a more reliable classification would be obtained, at least when the activity to detect has a limited generator, which is the case in motor related tasks.