Passive BCI beyond the lab: current trends and future directions.

Over the last decade, passive brain-computer interface (BCI) algorithms and biosignal acquisition technologies have experienced a significant growth that has allowed the real-time analysis of biosignals, with the aim to quantify relevant insights, such as mental and emotional states, of the users. Several passive BCI-based applications have been tested in laboratory settings, and just a few of them in real or, at least, simulated but highly realistic settings. Nevertheless, works performed in laboratory settings are not able to take into account all those factors (artefacts, non-brain influences, other mental states) that could impair the usability of passive BCIs during real applications, naturally characterized by higher complexity. The present review takes into account the most recent trends in using advanced passive BCI technologies in real settings, especially for real-time mental state evaluations in operational environments, evaluation of team resources, training and expertise assessment, gaming and neuromarketing applications. The objective of the work is to draw a mark on where we are to date and the future challenges, in order to make passive BCIs closer to being integrated into daily life applications.

A passive brain-computer interface application for the mental workload assessment on professional air traffic controllers during realistic air traffic control tasks.

In the last decades, it has been a fast-growing concept in the neuroscience field. The passive brain-computer interface (p-BCI) systems allow to improve the human-machine interaction (HMI) in operational environments, by using the covert brain activity (eg, mental workload) of the operator. However, p-BCI technology could suffer from some practical issues when used outside the laboratories. In particular, one of the most important limitations is the necessity to recalibrate the p-BCI system each time before its use, to avoid a significant reduction of its reliability in the detection of the considered mental states. The objective of the proposed study was to provide an example of p-BCIs used to evaluate the users' mental workload in a real operational environment. For this purpose, through the facilities provided by the École Nationale de l'Aviation Civile of Toulouse (France), the cerebral activity of 12 professional air traffic control officers (ATCOs) has been recorded while performing high realistic air traffic management scenarios. By the analysis of the ATCOs' brain activity (electroencephalographic signal-EEG) and the subjective workload perception (instantaneous self-assessment) provided by both the examined ATCOs and external air traffic control experts, it has been possible to estimate and evaluate the variation of the mental workload under which the controllers were operating. The results showed (i) a high significant correlation between the neurophysiological and the subjective workload assessment, and (ii) a high reliability over time (up to a month) of the proposed algorithm that was also able to maintain high discrimination accuracies by using a low number of EEG electrodes (~3 EEG channels). In conclusion, the proposed methodology demonstrated the suitability of p-BCI systems in operational environments and the advantages of the neurophysiological measures with respect to the subjective ones.

Influence of P300 latency jitter on event related potential-based brain-computer interface performance.

OBJECTIVE: Several ERP-based brain-computer interfaces (BCIs) that can be controlled even without eye movements (covert attention) have been recently proposed. However, when compared to similar systems based on overt attention, they displayed significantly lower accuracy. In the current interpretation, this is ascribed to the absence of the contribution of short-latency visual evoked potentials (VEPs) in the tasks performed in the covert attention modality. This study aims to investigate if this decrement (i) is fully explained by the lack of VEP contribution to the classification accuracy; (ii) correlates with lower temporal stability of the single-trial P300 potentials elicited in the covert attention modality. APPROACH: We evaluated the latency jitter of P300 evoked potentials in three BCI interfaces exploiting either overt or covert attention modalities in 20 healthy subjects. The effect of attention modality on the P300 jitter, and the relative contribution of VEPs and P300 jitter to the classification accuracy have been analyzed. MAIN RESULTS: The P300 jitter is higher when the BCI is controlled in covert attention. Classification accuracy negatively correlates with jitter. Even disregarding short-latency VEPs, overt-attention BCI yields better accuracy than covert. When the latency jitter is compensated offline, the difference between accuracies is not significant. SIGNIFICANCE: The lower temporal stability of the P300 evoked potential generated during the tasks performed in covert attention modality should be regarded as the main contributing explanation of lower accuracy of covert-attention ERP-based BCIs.

Self-calibration algorithm in an asynchronous P300-based brain-computer interface.

OBJECTIVE: Reliability is a desirable characteristic of brain-computer interface (BCI) systems when they are intended to be used under non-experimental operating conditions. In addition, their overall usability is influenced by the complex and frequent procedures that are required for configuration and calibration. Earlier studies examined the issue of asynchronous control in P300-based BCIs, introducing dynamic stopping and automatic control suspension features. This report proposes and evaluates an algorithm for the automatic recalibration of the classifier's parameters using unsupervised data. APPROACH: Ten healthy subjects participated in five P300-based BCI sessions throughout a single day. First, we examined whether continuous adaptation of control parameters improved the accuracy of the asynchronous system over time. Then, we assessed the performance of the self-calibration algorithm with respect to the no-recalibration and supervised calibration conditions with regard to system accuracy and communication efficiency. MAIN RESULTS: Offline tests demonstrated that continuous adaptation of the control parameters significantly increased the communication efficiency of asynchronous P300-based BCIs. The self-calibration algorithm correctly assigned labels to unsupervised data with 95% accuracy, effecting communication efficiency that was comparable with that of supervised repeated calibration. SIGNIFICANCE: Although additional online tests that involve end-users under non-experimental conditions are needed, these preliminary results are encouraging, from which we conclude that the self-calibration algorithm is a promising solution to improve P300-based BCI usability and reliability.

The great beauty: a neuroaesthetic study by neuroelectric imaging during the observation of the real Michelangelo's Moses sculpture.

Recent studies have been showed as the perception of real or displayed masterpieces by ancient or modern painters generate stable neuroelectrical correlates in humans. In this study, we collected the neuroelectrical brain activity correlated with the observation of the real sculpture of Michelangelo's Moses within the church where it is actually installed in a group of healthy subjects. In addition to the cerebral activity also the heart rate (HR) and the galvanic skin response (GSR) were collected simultaneously, to assess the emotional engage of the investigated population. The Moses sculpture was observed by the group from three different point of views, each one revealing different details of the sculpture. In addition, in each location the light conditions related to the specific observation of the sculpture were explicitly changed. Results showed that cerebral activity of the subjects varied significantly across the three different views and for light condition against no light condition (p<;0.04). Furthermore, the emotional engage estimated on the whole population is higher for a point of observation in which the Mose's face is directed toward the eyes of the observers (p<;0.02). Finally, the cerebral appreciation of the investigated group was found maximum from a perspective in which all the details of the sculpture could be easily grab by the eyes. Results suggested how the perception of the sculpture depends critically by the point of view of the observers and how such point of view can produce separate emotional and cerebral responses.

A neurophysiological training evaluation metric for air traffic management.

The aim of this work was to analyze the possibility to apply a neuroelectrical cognitive metrics for the evaluation of the training level of subjects during the learning of a task employed by Air Traffic Controllers (ATCos). In particular, the Electroencephalogram (EEG), the Electrocardiogram (ECG) and the Electrooculogram (EOG) signals were gathered from a group of students during the execution of an Air Traffic Management (ATM) task, proposed at three different levels of difficulty. The neuroelectrical results were compared with the subjective perception of the task difficulty obtained by the NASA-TLX questionnaires. From these analyses, we suggest that the integration of information derived from the power spectral density (PSD) of the EEG signals, the heart rate (HR) and the eye-blink rate (EBR) return important quantitative information about the training level of the subjects. In particular, by focusing the analysis on the direct and inverse correlation of the frontal PSD theta (4-7 (Hz)) and HR, and of the parietal PSD alpha (10-12 (Hz)) and EBR, respectively, with the degree of mental and emotive engagement, it is possible to obtain useful information about the training improvement across the training sessions.

Evaluation of the workload and drowsiness during car driving by using high resolution EEG activity and neurophysiologic indices.

Sleep deprivation and/or a high workload situation can adversely affect driving performance, decreasing a driver's capacity to respond effectively in dangerous situations. In this context, to provide useful feedback and alert signals in real time to the drivers physiological and brain activities have been increasingly investigated in literature. In this study, we analyze the increase of cerebral workload and the insurgence of drowsiness during car driving in a simulated environment by using high resolution electroencephalographic techniques (EEG) as well as neurophysiologic variables such as heart rate (HR) and eye blinks rate (EBR). The simulated drive tasks were modulated with five levels of increasing difficulty. A workload index was then generated by using the EEG signals and the related HR and EBR signals. Results suggest that the derived workload index is sensitive to the mental efforts of the driver during the different drive tasks performed. Such workload index was based on the estimation the variation of EEG power spectra in the theta band over prefrontal cortical areas and the variation of the EEG power spectra over the parietal cortical areas in alpha band. In addition, results suggested as HR increases during the execution of the difficult driving tasks while instead it decreases at the insurgence of the drowsiness. Finally, the results obtained showed as the EBR variable increases of its values when the insurgence of drowsiness in the driver occurs. The proposed workload index could be then used in a near future to assess on-line the mental state of the driver during a drive task.

Frontal EEG theta changes assess the training improvements of novices in flight simulation tasks.

The aim of the study is to analyze the variation of the EEG power spectra in theta band when a novice starts to learn a new task. In particular, the goal is to find out the differences from the beginning of the training to the session in which the performance level is good enough for considering him/her able to complete the task without any problems. While the novices were engaged in the flight simulation tasks we recorded the brain activity by using high resolution EEG techniques as well as neurophysiologic variables such as heart rate (HR) and eye blinks rate (EBR). Results show clear changes in the EEG power spectra in theta band over the frontal brain areas, either over the left, the midline and the right side, during the learning process of the task. These results are also supported by the autonomic signals of HR and EBR, by the performances' trends and by the questionnaires for the evaluation of the perceived workload level.

A comparison of classification techniques for a gaze-independent P300-based brain-computer interface.

This off-line study aims to assess the performance of five classifiers commonly used in the brain-computer interface (BCI) community, when applied to a gaze-independent P300-based BCI. In particular, we compared the results of four linear classifiers and one nonlinear: Fisher's linear discriminant analysis (LDA), stepwise linear discriminant analysis (SWLDA), Bayesian linear discriminant analysis (BLDA), linear support vector machine (LSVM) and Gaussian supported vector machine (GSVM). Moreover, different values for the decimation of the training dataset were tested. The results were evaluated both in terms of accuracy and written symbol rate with the data of 19 healthy subjects. No significant differences among the considered classifiers were found. The optimal decimation factor spanned a range from 3 to 24 (12 to 94 ms long bins). Nevertheless, performance on individually optimized classification parameters is not significantly different from a classification with general parameters (i.e. using an LDA classifier, about 48 ms long bins).

EEG-based Brain-Computer Interface to support post-stroke motor rehabilitation of the upper limb.

Brain-Computer Interfaces (BCIs) process brain activity in real time, and mediate non-muscular interaction between and individual and the environment. The subserving algorithms can be used to provide a quantitative measurement of physiological or pathological cognitive processes - such as Motor Imagery (MI) - and feed it back the user. In this paper we propose the clinical application of a BCI-based rehabilitation device, to promote motor recovery after stroke. The BCI-based device and the therapy exploiting its use follow the same principles that drive classical neuromotor rehabilitation, and (i) provides the physical therapist with a monitoring instrument, to assess the patient's participation in the rehabilitative cognitive exercise; (ii) assists the patient in the practice of MI. The device was installed in the ward of a rehabilitation hospital and a group of 29 patients were involved in its testing. Among them, eight have already undergone a one-month training with the device, as an add-on to the regular therapy. An improved system, which includes analysis of Electromyographic (EMG) patterns and Functional Electrical Stimulation (FES) of the arm muscles, is also under clinical evaluation. We found that the rehabilitation exercise based on BCI-mediated neurofeedback mechanisms enables a better engagement of motor areas with respect to motor imagery alone and thus it can promote neuroplasticity in brain regions affected by a cerebrovascular accident. Preliminary results also suggest that the functional outcome of motor rehabilitation may be improved by the use of the proposed device.

P300-based brain-computer interface for environmental control: an asynchronous approach.

Brain-computer interface (BCI) systems allow people with severe motor disabilities to communicate and interact with the external world. The P300 potential is one of the most used control signals for EEG-based BCIs. Classic P300-based BCIs work in a synchronous mode; the synchronous control assumes that the user is constantly attending to the stimulation, and the number of stimulation sequences is fixed a priori. This issue is an obstacle for the use of these systems in everyday life; users will be engaged in a continuous control state, their distractions will cause misclassification and the speed of selection will not take into account users' current psychophysical condition. An efficient BCI system should be able to understand the user's intentions from the ongoing EEG instead. Also, it has to refrain from making a selection when the user is engaged in a different activity and it should increase or decrease its speed of selection depending on the current user's state. We addressed these issues by introducing an asynchronous BCI and tested its capabilities for effective environmental monitoring, involving 11 volunteers in three recording sessions. Results show that this BCI system can increase the bit rate during control periods while the system is proved to be very efficient in avoiding false negatives when the users are engaged in other tasks.

Yttrium and lanthanides in human lung fluids, probing the exposure to atmospheric fallout.

Inhalation of airborne particles can produce crystallization of phosphatic microcrysts in intraaveolar areas of lungs, sometimes degenerating into pulmonary fibrosis. Results of this study indicate that these pathologies are induced by interactions between lung fluids and inhaled atmospheric dust in people exposed to volcanic dust ejected from Mount Etna in 2001. Here, the lung solid-liquid interaction is evaluated by the distribution of yttrium and lanthanides (YLn) in fluid bronchoalveolar lavages on selected individuals according the classical geochemical approaches. We found that shale-normalised patterns of yttrium and lanthanides have a 'V shaped' feature corresponding to the depletion of elements from Nd to Tb when compared to the variable enrichments of heavy lanthanides, Y, La and Ce. These features and concurrent thermodynamic simulations suggest that phosphate precipitation can occur in lungs due to interactions between volcanic particles and fluids. We propose that patterns of yttrium and lanthanides can represent a viable explanation of some pathology observed in patients after prolonged exposure to atmospheric fallout and are suitable to become a diagnostic parameter of chemical environmental stresses.

HCV infection and oral lichen planus: a weak association when HCV is endemic.

Oral lichen planus (OLP), an immune-mediated disorder, has been reported as an extra-hepatic manifestation of Hepatitis C virus (HCV) infection, especially in HCV hyperendemic areas such as southern Europe and Japan. The aim of this study was to investigate from an epidemiological standpoint whether HCV infection is an important factor affecting the relative risk of OLP in a Mediterranean population or whether this relates to the degree of HCV endemicity. Two cohorts of OLP patients resident in two different regions of southern Italy (Campania and Sicily; n = 859) were evaluated for HCV infection status and categorized into five age classes to respective region-matched controls. No significant difference was found between OLP patients and the general population in this area, when data were corrected by the age-stratified prevalence of HCV. Therefore, the age-specific prevalence of HCV infection in OLP patients shows a close trend of direct association with increasing age, without significant differences with the general population of each geographical area. An aetiological link between OLP and HCV cannot be inferred solely by epidemiological data.

A new delivery system of clobetasol-17-propionate (lipid-loaded microspheres 0.025%) compared with a conventional formulation (lipophilic ointment in a hydrophilic phase 0.025%) in topical treatment of atrophic/erosive oral lichen planus. A Phase IV, randomized, observer-blinded, parallel group clinical trial.

BACKGROUND: Topical application of clobetasol-17-propionate has been diffusely reported as an efficacious therapy in atrophic/erosive oral lichen planus (OLP), without exposing the patient to systemic side-effects. However, prolonged contact and respective topical effects on the oral mucosa should be avoided. OBJECTIVES: The aim of the present study was to evaluate efficacy and compliance of new lipid microspheres loaded with 0.025% of clobetasol propionate (formulation A) compared with a commonly used formulation (a sort of dispersion of a lipophilic ointment in a hydrophilic phase) with the same amount of drug (formulation B) in the topical treatment of OLP. PATIENTS AND METHODS: Fifty patients with symptomatic OLP were enrolled in a controlled single-blind phase IV clinical trial. After a dropout of five patients, a total of 45 patients [12 males and 33 females; mean age 61.1 years (+/- 12.3 SD; range 25-82)] were treated (17 with formulation A and 28 with formulation B, matched for gender and age; P > 0.2) with the same dosage regimen. At times T0, T1 and T2 we evaluated the following parameters: (i) pain score (by linear visual analogue scale; 0-100); (ii) clinical score; (iii) clinical resolution; and (iv) patient compliance. Statistical analysis was calculated using S-Plus 4.0 and SPSS 9.0 (Student's t-test, chi(2), Kolmogorov-Smirnow, Friedman, Student-Newman-Keuls, Mann-Whitney U-test and Spearman tests). RESULTS: Both formulations were found to be similar for parameters ii, iii and iv, although with a better general trend for formulation A; a significant difference was registered for formulation A in terms of a reduction in painful symptoms (parameter i) at time T2 (P = 0.02). CONCLUSIONS: Our results suggest that the new topical drug delivery system (formulation A) may enhance, at least in terms of symptom remission and compliance, the effectiveness of clobetasol propionate at a dose of 0.025% in OLP therapy.