Actualización en el abordaje del drenaje torácico / Update on chest drainage management

La acumulación de aire y/o líquido en el espacio pleural conlleva un incremento de la morbimortalidad. El drenaje pleural permite la evacuación del contenido anormal de la cavidad pleural, con la consiguiente reexpansión pulmonar y estabilización cardiorrespiratoria. La complejidad cada vez mayor de los enfermos ingresados en el hospital hace frecuente en la práctica clínica la necesidad de colocación de un drenaje torácico. Tanto la colocación como los cuidados deben ser realizados por personal entrenado. La presente revisión no tiene como objetivo describir la patología pleural sino demostrar de una forma didáctica y práctica las pautas básicas para la colocación y el manejo adecuado de los sistemas de drenaje pleural al personal sanitario para contribuir a mejorar la seguridad de la práctica clínica. Entre los mayores avances destacan la introducción de la ecografía torácica y la utilización de nuevas técnicas de drenaje.(AU)

Accumulation of air and/or liquid in the pleural cavity leads to an increase in morbidity and mortality. Chest drainage allows the evacuation of the abnormal content of the pleural cavity, with the consequent lung expansion and cardiorespiratory stability. The increased patient-related complexity in hospitals often carries to place chest drainage in clinical practice. Both placement and care must be performed by a highly trained staff. The objective of this review is not to describe pleural pathology, but to demonstrate in a didactic and practical way the basic guidelines for placement and management of chest drainage systems for healthcare professionals to improve workplace safety. Among the greatest advances are the introduction of chest ultrasound and the use of new drainage techniques.(AU)

Microbiome and Allergy: New Insights and Perspectives.

The role of the microbiome in the molecular mechanisms underlying allergy has become highly relevant in recent years. Studies are increasingly suggesting that altered composition of the microbiota, or dysbiosis, may result in local and systemic alteration of the immune response to specific allergens. In this regard, a link has been established between lung microbiota and respiratory allergy, between skin microbiota and atopic dermatitis, and between gut microbiota and food allergy. The composition of the human microbiota is dynamic and depends on host-associated factors such as diet, diseases, and lifestyle. Omics are the techniques of choice for the analysis and understanding of the microbiota. Microbiota analysis techniques have advanced considerably in recent decades, and the need for multiple approaches to explore and comprehend multifactorial diseases, including allergy, has increased. Thus, more and more studies are proposing mechanisms for intervention in the microbiota. In this review, we present the latest advances with respect to the human microbiota in the literature, focusing on the intestinal, cutaneous, and respiratory microbiota. We discuss the relationship between the microbiome and the immune system, with emphasis on allergic diseases. Finally, we discuss the main technologies for the study of the microbiome and interventions targeting the microbiota for prevention of allergy.

Microbiome and Allergy: New Insights and Perspectives

The role of the microbiome in the molecular mechanisms underlying allergy has become highly relevant in recent years. Studies areincreasingly suggesting that altered composition of the microbiota, or dysbiosis, may result in local and systemic alteration of the immuneresponse to specific allergens. In this regard, a link has been established between lung microbiota and respiratory allergy, between skinmicrobiota and atopic dermatitis, and between gut microbiota and food allergy.The composition of the human microbiota is dynamic and depends on host-associated factors such as diet, diseases, and lifestyle. Omics arethe techniques of choice for the analysis and understanding of the microbiota. Microbiota analysis techniques have advanced considerablyin recent decades, and the need for multiple approaches to explore and comprehend multifactorial diseases, including allergy, has increased.Thus, more and more studies are proposing mechanisms for intervention in the microbiota.In this review, we present the latest advances with respect to the human microbiota in the literature, focusing on the intestinal, cutaneous,and respiratory microbiota. We discuss the relationship between the microbiome and the immune system, with emphasis on allergic diseases.Finally, we discuss the main technologies for the study of the microbiome and interventions targeting the microbiota for prevention of allergy. (AU)

El papel del microbioma en los mecanismos moleculares de las enfermedades alérgicas se ha vuelto muy relevante en los últimos años.Cada vez más estudios sugieren que una composición alterada de la microbiota, o disbiosis, puede resultar en una alteración local ysistémica de la respuesta inmune a alérgenos específicos. En este sentido, se ha establecido un vínculo entre la microbiota pulmonar y laalergia respiratoria, así como la microbiota cutánea y el desarrollo de dermatitis atópica, y la microbiota intestinal y la alergia alimentaria.La composición de la microbiota humana es dinámica y depende de diversos factores asociados al huésped como la dieta, las enfermedadesy el estilo de vida, entre otros. Para el análisis y comprensión de la microbiota, las ómicas son las técnicas de elección. En las últimasdécadas, las técnicas de análisis de microbiota han tenido un gran avance y han aumentado la necesidad de múltiples enfoques paraexplorar y comprender las enfermedades multifactoriales, incluidas las enfermedades alérgicas. De esta manera, cada vez son más losestudios que proponen mecanismos de intervención sobre la microbiota de pacientes.En esta revisión, presentamos los últimos avances encontrados en la literatura sobre la microbiota humana, centrándose en las microbiotasintestinal, cutánea y respiratoria. Discutimos la relación entre el microbioma y el sistema inmunológico, con especial énfasis en lasenfermedades alérgicas. Finalmente, discutimos las principales tecnologías para el estudio del microbioma y los estudios de intervencióndirigidos a la microbiota propuestos para la prevención de alergias. (AU)

Clinical Approach to Mast Cell Activation Syndrome: A Practical Overview.

The diagnosis of mast cell activation syndrome (MCAS) is defined by 3 criteria: (1) typical clinical signs and symptoms of acute, recurrent (episodic), and systemic mast cell activation (MCA); (2) increase in tryptase level to >20% + 2 ng/mL within 1-4 hours after onset of the acute crisis; and (3) response of MCA symptoms to antimediator therapy. Classification of MCAS requires highly sensitive and specific methodological approaches for the assessment of clonal bone marrow mast cells at low frequencies. The Spanish Network on Mastocytosis score has been used successfully as a predictive model for selecting MCAS candidates for bone marrow studies based on a high probability of an underlying clonal mast cell disorder. In this article, we propose a diagnostic algorithm and focus on the practical evaluation and management of patients with suspected MCAS.

Radiologic aspects of COVID-19 pneumonia: outcomes and thoracic complications. / Aspectos radiológicos de la neumonía COVID-19: evolución y complicaciones torácicas.

Outcomes vary widely in patients with COVID-19. Whereas some patients have only mild symptoms of short duration, others develop severe disease that leads to acute respiratory distress syndrome requiring prolonged stays in intensive care units. Radiologically, the initial stage is characterized by viral pneumonia with mild expression. In some patients, however, the onset of the immune response results in acute lung damage with organizing pneumonia and diffuse alveolar damage. Moderate-severe disease is associated with a high incidence of pulmonary embolisms, generally peripherally distributed and associated with endothelial damage, prolonged stays in bed, and coagulopathy. Other relatively common complications are spontaneous pneumothorax and pneumomediastinum due to the rupture of alveolar walls and barotrauma in mechanically ventilated patients. Superinfection, generally bacterial and less commonly fungal, is more common in patients with severe disease.

Clinical Approach to Mast Cell ActivationSyndrome: A Practical Overview

The diagnosis of mast cell activation syndrome (MCAS) is defined by 3 criteria: (1) typical clinical signs and symptoms of acute, recurrent (episodic), and systemic mast cell activation (MCA); (2) increase in tryptase level to >20% + 2 ng/mL within 1-4 hours after onset of the acute crisis; and (3) response of MCA symptoms to antimediator therapy. Classification of MCAS requires highly sensitive and specific methodological approaches for the assessment of clonal bone marrow mast cells at low frequencies. The Spanish Network on Mastocytosis score has been used successfully as a predictive model for selecting MCAS candidates for bone marrow studies based on a high probability of an underlying clonal mast cell disorder. In this article, we propose a diagnostic algorithm and focus on the practical evaluation and management of patients with suspected MCAS (AU)

El diagnóstico de síndrome de activación mastocitaria (SAM) se basa en 3 criterios: 1) signos y síntomas específicos de activación mastocitaria aguda, recurrente y sistémica, 2) aumento de los valores de triptasa en un 20% + 2 ng/ml sobre el valor basal de cada individuo en el periodo comprendido entre 1-4 horas desde el inicio del cuadro agudo, y 3) resolución de los síntomas con tratamiento antimediador. Para realizar el diagnóstico de SAM, es preciso emplear métodos diagnósticos altamente sensibles y específicos capaces de detectar bajas cantidades de mastocitos en la médula ósea. El modelo predictivo de la Red Española de Mastocitosis (REMA score) resulta útil para identificar a los pacientes con mayor probabilidad de padecer una patología mastocitaria clonal y que, por tanto, requieren que se nealice un estudio de médula ósea en el proceso diagnóstico. En este artículo, proponemos un algoritmo diagnóstico para SAM y abordamos el manejo de estos pacientes desde un punto de vista práctico en la consulta alergológica (AU)

Allergic asthma: an overview of metabolomic strategies leading to the identification of biomarkers in the field.

Allergic asthma is a prominent disease especially during childhood. Indoor allergens, in general, and particularly house dust mites (HDM) are the most prevalent sensitizers associated with allergic asthma. Available data show that 65-130 million people are mite-sensitized world-wide and as many as 50% of these are asthmatic. In fact, sensitization to HDM in the first years of life can produce devastating effects on pulmonary function leading to asthmatic syndromes that can be fatal. To date, there has been considerable research into the pathological pathways and structural changes associated with allergic asthma. However, limitations related to the disease heterogeneity and a lack of knowledge into its pathophysiology have impeded the generation of valuable data needed to appropriately phenotype patients and, subsequently, treat this disease. Here, we report a systematic and integral analysis of the disease, from airway remodelling to the immune response taking place throughout the disease stages. We present an overview of metabolomics, the management of complex multifactorial diseases through the analysis of all possible metabolites in a biological sample, obtaining a global interpretation of biological systems. Special interest is placed on the challenges to obtain biological samples and the methodological aspects to acquire relevant information, focusing on the identification of novel biomarkers associated with specific phenotypes of allergic asthma. We also present an overview of the metabolites cited in the literature, which have been related to inflammation and immune response in asthma and other allergy-related diseases.

Asynchronous Detection of Trials Onset from Raw EEG Signals.

Clinical processing of event-related potentials (ERPs) requires a precise synchrony between the stimulation and the acquisition units that are guaranteed by means of a physical link between them. This precise synchrony is needed since temporal misalignments during trial averaging can lead to high deviations of peak times, thus causing error in diagnosis or inefficiency in classification in brain-computer interfaces (BCIs). Out of the laboratory, mobile EEG systems and BCI headsets are not provided with the physical link, thus being inadequate for acquisition of ERPs. In this study, we propose a method for the asynchronous detection of trials onset from raw EEG without physical links. We validate it with a BCI application based on the dichotic listening task. The user goal was to attend the cued auditory message and to report three keywords contained in it while ignoring the other message. The BCI goal was to detect the attended message from the analysis of auditory ERPs. The rate of successful onset detection in both synchronous (using the real onset) and asynchronous (blind detection of trial onset from raw EEG) was 73% with a synchronization error of less than 1[Formula: see text]ms. The level of synchronization provided by this proposal would allow home-based acquisition of ERPs with low cost BCI headsets and any media player unit without physical links between them.

Promoción de la salud mediante la salvaguarda del medio ambiente / Health promotion through environmental protection

No disponible

Spreading codes enables the blind estimation of the hemodynamic response with short-events sequences.

Finite impulse response (FIR) filters are considered the least constrained option for the blind estimation of the hemodynamic response function (HRF). However, they have a tendency to yield unstable solutions in the case of short-events sequences. There are solutions based on regularization, e.g. smooth FIR (sFIR), but at the cost of a regularization penalty and prior knowledge, thus breaking the blind principle. In this study, we show that spreading codes (scFIR) outperforms FIR and sFIR in short-events sequences, thus enabling the blind and dynamic estimation of the HRF without numerical instabilities and the regularization penalty. The scFIR approach was applied in short-events sequences of simulated and experimental functional magnetic resonance imaging (fMRI) data. In general terms, scFIR performed the best with both simulated and experimental data. While FIR was unable to compute the blind estimation of two simulated target HRFs for the shortest sequences (15 and 31 events) and sFIR yielded shapes barely correlated with the targets, scFIR achieved a normalized correlation coefficient above 0.9. Furthermore, scFIR was able to estimate in a responsive way dynamic changes of the amplitude of a simulated target HRF more accurately than FIR and sFIR. With experimental fMRI data, the ability of scFIR to estimate the real HRF obtained from a training data set was superior in terms of correlation and mean-square error. The use of short-events sequences for the blind estimation of the HRF could benefit patients in terms of scanning time or intensity of magnetic field in clinical tests. Furthermore, short-events sequences could be used, for instance, on the online detection of rapid shifts of visual attention that, according to literature, entails rapid changes in the amplitude of the HRF.

Dry EEG electrodes.

Electroencephalography (EEG) emerged in the second decade of the 20th century as a technique for recording the neurophysiological response. Since then, there has been little variation in the physical principles that sustain the signal acquisition probes, otherwise called electrodes. Currently, new advances in technology have brought new unexpected fields of applications apart from the clinical, for which new aspects such as usability and gel-free operation are first order priorities. Thanks to new advances in materials and integrated electronic systems technologies, a new generation of dry electrodes has been developed to fulfill the need. In this manuscript, we review current approaches to develop dry EEG electrodes for clinical and other applications, including information about measurement methods and evaluation reports. We conclude that, although a broad and non-homogeneous diversity of approaches has been evaluated without a consensus in procedures and methodology, their performances are not far from those obtained with wet electrodes, which are considered the gold standard, thus enabling the former to be a useful tool in a variety of novel applications.

[Clinical decision-making support systems in renal failure]. / Sistemas de soporte a la toma de decisiones clínicas en insuficiencia renal.

INTRODUCTION: Support systems in clinical decision-making use individual characteristics of the patient to generate recommendations to the clinician. OBJECTIVE: To assess the impact of a tool for adjusting drug dosing in renal failure asa support system in clinical decision-making regarding the level of acceptance of the interventions as well as the time invested by the pharmacist. METHOD: Non-randomized, prospective and hospital interventional study comparing pre- and post-implementation phases of an automated renal function alert system, carried out at two county hospitals. Forty drugs were monitored before the intervention(2007). The blood work of the patients receiving any of these drugs was reviewed. In case of impaired renal function, an adjustment recommendation was inserted in the medical prescription. If the physician accepted it, it was rated as success. The average time was 1 minute per blood work reviewed and 3 minutes per recommendation. An automated adjustment recommendation system according to renal function with alert pop-ups was implemented in 2008 for 100 drugs. Later (2009), the number of interventions and the success rate for this tool were assessed and compared. RESULTS: Pre-implementation phase. 28,234 electronic medical prescriptions corresponding to a mean number of 205 hospitalized patients/day were validated and 4,035 blood works were reviewed. One hundred and twenty-one pharmaceutical interventions(0.43% of the medical prescriptions) were inserted. A success rate of 33.06% of the interventions was obtained. The time invested by the pharmacist for consulting the bloodworks and making the recommendations was 73.3 hours (67.25 hours corresponding to patients without renal function impairment and in whom no intervention was made).Post-implementation phase. 26,584 electronic medical orders corresponding to 193 hospitalized patients/day were validated and 1,737 automated interventions were performed(6.53% of total medical orders), of which 65.69% were accepted (success). CONCLUSIONS: The implementation of clinical decision-making support systems allows extending the number of patients and drugs monitored, optimizing the time invested by the pharmacist. Simultaneous occurrence of an alert during prescription may have contributed to the greater success rate observed.

Introducción: Los sistemas de soporte a la toma de decisiones clínicas utilizan característicasindividuales del paciente para generar recomendaciones a los clínicos.Objetivo: Evaluar el impacto de una herramienta de ajuste de fármacos en insuficienciarenal como sistema de soporte en la toma de decisiones clínicas encuanto al grado de aceptación de las intervenciones y el tiempo invertido por elfarmacéutico.Método: Estudio cuasi-experimental del tipo antes y después realizado en dos hospitalescomarcales. La intervención consistía en la incorporación de una alerta automatizadade función renal en la orden médica. Antes de la intervención (2007) semonitorizaron 40 fármacos. Se revisaron las analíticas de pacientes cuyo tratamientocontenía alguno de ellos. En caso de función renal alterada, se insertabauna recomendación de ajuste en la orden médica. Si el médico aceptaba, se considerabaéxito. El tiempo medio empleado fue 1 minuto/analítica consultada y 3minutos/recomendación. En 2008 se incorporó un sistema de recomendación automáticade ajuste según función renal de 100 fármacos con mensajes emergentes.En una fase posterior (2009) se evaluó y comparó el número de intervenciones y elporcentaje de éxito con la herramienta.Resultados: Fase previa: Se validaron 28.234 Ordenes Médicas Electrónicas, correspondientesa un promedio de 205 pacientes hospitalizados/día, y se revisaron 4.035analíticas. Se realizaron 121 intervenciones farmacéuticas (0,43% del total de órdenesmédicas). Se obtuvo éxito en el 33,06% de las intervenciones. El tiempo invertidopor el farmacéutico en consultar analíticas y realizar recomendaciones fue 73,3horas (67,25 horas correspondían a pacientes sin alteración de la función renal y enlos que no se realizó ninguna intervención). Fase posterior: Se validaron 26.584Ordenes Médicas Electrónicas, correspondientes a un promedio de 193 pacienteshospitalizados/día, y se realizaron 1.737 intervenciones automatizadas (6,53% deltotal de ordenes médicas), de las cuales se aceptaron 65,69% (éxito).Conclusiones: La implantación de sistemas de soporte a la toma de decisiones clínicas,permite ampliar los pacientes y fármacos monitorizados, optimizando eltiempo invertido por el farmacéutico. La aparición simultánea de la alerta durantela prescripción puede haber contribuido al mayor porcentaje de éxito observado.

Sistemas de soporte a la toma de decisiones clínicas en insuficiencia renal / Clinical decision-making support systems in renal failure

Introducción: Los sistemas de soporte a la toma de decisiones clínicas utilizan características individuales del paciente para generar recomendaciones a los clínicos. Objetivo: Evaluar el impacto de una herramienta de ajuste de fármacos en insuficiencia renal como sistema de soporte en la toma de decisiones clínicas en cuanto al grado de aceptación de las intervenciones y el tiempo invertido por el farmacéutico. Método: Estudio cuasi-experimental del tipo antes y después realizado en dos hospitales comarcales. La intervención consistía en la incorporación de una alerta automatizada de función renal en la orden médica. Antes de la intervención (2007) se monitorizaron 40 fármacos. Se revisaron las analíticas de pacientes cuyo tratamiento contenía alguno de ellos. En caso de función renal alterada, se insertaba una recomendación de ajuste en la orden médica. Si el médico aceptaba, se consderaba éxito. El tiempo medio empleado fue 1 minuto/analítica consultada y 3minutos/recomendación. En 2008 se incorporó un sistema de recomendación automática de ajuste según función renal de 100 fármacos con mensajes emergentes. En una fase posterior (2009) se evaluó y comparó el número de intervenciones y el porcentaje de éxito con la herramienta. Resultados: Fase previa: Se validaron 28.234 Ordenes Médicas Electrónicas, correspondientes a un promedio de 205 pacientes hospitalizados/día, y se revisaron 4.035 analíticas. Se realizaron 121 intervenciones farmacéuticas (0,43% del total de órdenes médicas). Se obtuvo éxito en el 33,06% de las intervenciones. El tiempo invertido por el farmacéutico en consultar analíticas y realizar recomendaciones fue 73,3 horas (67,25 horas correspondían a pacientes sin alteración de la función renal y en los que no se realizó ninguna intervención). Fase posterior: Se validaron 26.584Ordenes Médicas Electrónicas, correspondientes a un promedio de 193 pacientes hospitalizados/día, y se realizaron 1.737 intervenciones automatizadas (6,53% del total de ordenes médicas), de las cuales se aceptaron 65,69% (éxito). Conclusiones: La implantación de sistemas de soporte a la toma de decisiones clínicas, permite ampliar los pacientes y fármacos monitorizados, optimizando el tiempo invertido por el farmacéutico. La aparición simultánea de la alerta durante la prescripción puede haber contribuido al mayor porcentaje de éxito observado

Introduction: Support systems in clinical decision-making use individual characteristics of the patient to generate recommendations to the clinician. Objective: To assess the impact of a tool for adjusting drug dosing in renal failure as a support system in clinical decision-making regarding the level of acceptance of the interventions as well as the time invested by the pharmacist. Method: Non-randomized, prospective and hospital interventional study comparingpre- and post-implementation phases of an automated renal function alert system, carried out at two county hospitals. Forty drugs were monitored before the intervention(2007). The blood work of the patients receiving any of these drugs was reviewed. In case of impaired renal function, an adjustment recommendation was inserted in the medical prescription. If the physician accepted it, it was rated as success. The average time was 1 minute per blood work reviewed and 3 minutes per recommendation. Anautomated adjustment recommendation system according to renal function with alert pop-ups was implemented in 2008 for 100 drugs. Later (2009), the number of interventions and the success rate for this tool were assessed and compared. Results: Pre-implementation phase. 28,234 electronic medical prescriptions corresponding to a mean number of 205 hospitalized patients/day were validated and 4,035 bloodworks were reviewed. One hundred and twenty-one pharmaceutical interventions(0.43% of the medical prescriptions) were inserted. A success rate of 33.06% of the interventions was obtained. The time invested by the pharmacist for consulting the bloodworks and making the recommendations was 73.3 hours (67.25 hours corresponding to patients without renal function impairment and in whom no intervention wasmade). Post-implementation phase.26,584 electronic medical orders corresponding to 193 hos-pitalized patients/day were validated and 1,737 automated interventions were performed (6.53% of total medical orders), of which 65.69% were accepted (success). Conclusions: The implementation of clinical decision-making support systems allow sextending the number of patients and drugs monitored, optimizing the time invested by the pharmacist. Simultaneous occurrence of an alert during prescription may have contributed to the greater success rate observed

A binary phase-shift keying receiver for the detection of attention to human speech.

Synthetic sounds, tone-beeps, vowels or syllables are typically used in the assessment of attention to auditory stimuli because they evoke a set of well-known event-related potentials, whose characteristics can be statistically contrasted. Such approach rules out the use of stimuli with non-predictable response, such as human speech. In this study we present a procedure based on the robust binary phase-shift keying (BPSK) receiver that permits the real-time detection of selective attention to human speeches in dichotic listening tasks. The goal was achieved by tagging the speeches with two barely-audible tags whose joined EEG response constitutes a reliable BPSK constellation, which can be detected by means of a BPSK receiver. The results confirmed the expected generation of the BPSK constellation by the human auditory system. Also, the bit-error rate and the information transmission rate achieved in the detection of attention fairly followed the expected curves and equations of the standard BPSK receiver. Actually, it was possible to detect attention as well as the estimation a priori of its accuracy based on the signal-to-noise ratio of the BPSK signals. This procedure, which permits the detection of the attention to human speeches, can be of interest for new potential applications, such as brain-computer interfaces, clinical assessment of the attention in real time or for entertainment.

Initiation and discontinuation of substrate inhibitor treatment in patients with Niemann-Pick type C disease.

Niemann-Pick type C disease (NP-C) is a lysosomal storage disorder characterized by a progressive neurological deterioration. Different clinical forms have been defined based on patient age at neurological symptoms onset: perinatal, early infantile (EI), late infantile (LI), juvenile and adult. There is no curative treatment for NP-C. Miglustat is the first effective therapy for the neurological manifestations of NP-C patients, as it can slow down the progression of the disease. Our aim is to establish recommendations on the initiation and discontinuations with miglustat therapy based on the modified disability scale scores and describe therapeutic options to prevent treatment-related adverse effects. Four patients with different clinical forms of NP-C are reported. The modified disability scale was applied at baseline and treatment on follow up. Treatment with miglustat was initiated in patient 1 (EI form) at onset of delayed speech. Patient 2 (LI form) who started miglustat therapy in the advanced stage of the disease, died 2 years thereafter. Patient 3 (juvenile form) started treatment with miglustat at diagnosis and remains stable at four years on follow up. Patient 4, asymptomatic, is not currently treated. Miglustat has demonstrated efficacy to slow down the neurological impairment in NP-C patients assessed by the modified disability scale. Miglustat should be initiated at the onset of the first neurological symptoms. Disability scores above 20 reflect an advanced neurological impairment of the disease and miglustat therapy should be discontinued or not initiated. The gastrointestinal adverse effects can be prevented by dose titration and dietary modifications.

An auditory brain­computer interface evoked by natural speech.

Brain­computer interfaces (BCIs) are mainly intended for people unable to perform any muscular movement, such as patients in a complete locked-in state. The majority of BCIs interact visually with the user, either in the form of stimulation or biofeedback. However, visual BCIs challenge their ultimate use because they require the subjects to gaze, explore and shift eye-gaze using their muscles, thus excluding patients in a complete locked-in state or under the condition of the unresponsive wakefulness syndrome. In this study, we present a novel fully auditory EEG-BCI based on a dichotic listening paradigm using human voice for stimulation. This interface has been evaluated with healthy volunteers, achieving an average information transmission rate of 1.5 bits min⁻¹ in full-length trials and 2.7 bits min⁻¹ using the optimal length of trials, recorded with only one channel and without formal training. This novel technique opens the door to a more natural communication with users unable to use visual BCIs, with promising results in terms of performance, usability, training and cognitive effort.

An auditory brain-computer interface with accuracy prediction.

Fully auditory Brain-computer interfaces based on the dichotic listening task (DL-BCIs) are suited for users unable to do any muscular movement, which includes gazing, exploration or coordination of their eyes looking for inputs in form of feedback, stimulation or visual support. However, one of their disadvantages, in contrast with the visual BCIs, is their lower performance that makes them not adequate in applications that require a high accuracy. To overcome this disadvantage, we employed a Bayesian approach in which the DL-BCI was modeled as a Binary phase shift keying receiver for which the accuracy can be estimated a priori as a function of the signal-to-noise ratio. The results showed the measured accuracy to match the predefined target accuracy, thus validating this model that made possible to estimate in advance the classification accuracy on a trial-by-trial basis. This constitutes a novel methodology in the design of fully auditory DL-BCIs that let us first, define the target accuracy for a specific application and second, classify when the signal-to-noise ratio guarantees that target accuracy.