Towards a new passive Brain-computer interface to detect accidental awareness during general anesthesia

International audienc

Can the MIQ-RS questionnaire be used to estimate the performance of a MI-based BCI?

International audiencePredicting a subject's ability to use the interface with good accuracy is one of the major issues in the motor Brain-Computer interface (BCI) domain. A few recent studies show that subjective questionnaires could be used to predict the performance of motor imagery (MI) based BCI. Indeed, the Kinesthetic and Visual Imagery Questionnaire (KVIQ), could allow a better predictability of BCI-illiterate cases [1]. Another more recent questionnaire called the Motor Imagery Questionnaire Revised-Second Edition (MIQ-RS) is a suitable option for examining MI ability [2]. In 2016, Marchesotti et al. found that the representation of subjective behaviour, calculated using the MIQ-RS questionnaire, and the control of the BCI were intimately linked [3]. However, in these studies [1, 3], the performance of the classifier was calculated for a right-hand MI versus a left-hand MI task. In this abstract, we classify between resting state and imagined movement, which is a relevant classification task in BCI research [4]. The aim of this study is to answer the following question for a resting state versus MI classification task: can the MIQ-RS be used to estimate the performance of an MI-based BCI

Can a Subjective Questionnaire Be Used as Brain-Computer Interface Performance Predictor?

International audiencePredicting a subject's ability to use a Brain Computer Interface (BCI) is one of the major issues in the BCI domain. Relevant applications of forecasting BCI performance include the ability to adapt the BCI to the needs and expectations of the user, assessing the efficiency of BCI use in stroke rehabilitation, and finally, homogenizing a research population. A limited number of recent studies have proposed the use of subjective questionnaires, such as the Motor Imagery Questionnaire Revised-Second Edition (MIQ-RS). However, further research is necessary to confirm the effectiveness of this type of subjective questionnaire as a BCI performance estimation tool. In this study we aim to answer the following questions: can the MIQ-RS be used to estimate the performance of an MI-based BCI? If not, can we identify different markers that could be used as performance estimators? To answer these questions, we recorded EEG signals from 35 healthy volunteers during BCI use. The subjects had previously completed the MIQ-RS questionnaire. We conducted an offline analysis to assess the correlation between the questionnaire scores related to Kinesthetic and Motor imagery tasks and the performances of four classification methods. Our results showed no significant correlation between BCI performance and the MIQ-RS scores. However, we reveal that BCI performance is correlated to habits and frequency of practicing manual activities

Can the MIQ-RS questionnaire be used to estimate the performance of a MI-based BCI?

International audienc

Innovative Brain-Computer Interface based on motor cortex activity to detect accidental awareness during general anesthesia

International audienceAccidental Awareness during General Anesthesia (AAGA) occurs in 1-2% of high-risk practice patients and is responsible for severe psychological trauma, termed post-traumatic stress disorder (PTSD). Currently, monitoring techniques have limited accuracy in predicting or detecting AAGA. Since the first reflex of a patient experiencing AAGA is to move, a passive Brain-Computer Interface (BCI) based on the detection of an intention of movement would be conceivable to alert the anesthetist and prevent this phenomenon. However, the way in which the propofol (an anesthetic drug commonly used for inducing and maintaining general anesthesia) affects the motor brain activity and is reflected by the electroencephalo-graphic (EEG) signal has been poorly investigated and is not clearly understood. The goal of this forward-looking study is to investigate the motor activity behavior with step-wise increase of propofol doses in 4 healthy subjects and provide a proof of concept for such an innovative BCI

DUX4c Is Up-Regulated in FSHD. It Induces the MYF5 Protein and Human Myoblast Proliferation

Facioscapulohumeral muscular dystrophy (FSHD) is a dominant disease linked to contractions of the D4Z4 repeat array in 4q35. We have previously identified a double homeobox gene (DUX4) within each D4Z4 unit that encodes a transcription factor expressed in FSHD but not control myoblasts. DUX4 and its target genes contribute to the global dysregulation of gene expression observed in FSHD. We have now characterized the homologous DUX4c gene mapped 42 kb centromeric of the D4Z4 repeat array. It encodes a 47-kDa protein with a double homeodomain identical to DUX4 but divergent in the carboxyl-terminal region. DUX4c was detected in primary myoblast extracts by Western blot with a specific antiserum, and was induced upon differentiation. The protein was increased about 2-fold in FSHD versus control myotubes but reached 2-10-fold induction in FSHD muscle biopsies. We have shown by Western blot and by a DNA-binding assay that DUX4c over-expression induced the MYF5 myogenic regulator and its DNA-binding activity. DUX4c might stabilize the MYF5 protein as we detected their interaction by co-immunoprecipitation. In keeping with the known role of Myf5 in myoblast accumulation during mouse muscle regeneration DUX4c over-expression activated proliferation of human primary myoblasts and inhibited their differentiation. Altogether, these results suggested that DUX4c could be involved in muscle regeneration and that changes in its expression could contribute to the FSHD pathology

Median Nerve Stimulation Based BCI: A New Approach to Detect Intraoperative Awareness During General Anesthesia

International audienceHundreds of millions of general anesthesia are performed each year on patients all overthe world. Among these patients, 0.1–0.2% are victims of Accidental Awareness duringGeneral Anesthesia (AAGA), i.e., an unexpected awakening during a surgical procedureunder general anesthesia. Although anesthesiologists try to closely monitor patientsusing various techniques to prevent this terrifying phenomenon, there is currently noefficient solution to accurately detect its occurrence. We propose the conception of aninnovative passive brain-computer interface (BCI) based on an intention of movementto prevent AAGA. Indeed, patients typically try to move to alert the medical staff duringan AAGA, only to discover that they are unable to. First, we examine the challengesof such a BCI, i.e., the lack of a trigger to facilitate when to look for an intention tomove, as well as the necessity for a high classification accuracy. Then, we present asolution that incorporates Median Nerve Stimulation (MNS). We investigate the specificmodulations that MNS causes in the motor cortex and confirm that they can be alteredby an intention of movement. Finally, we perform experiments on 16 healthy participantsto assess whether an MI-based BCI using MNS is able to generate high classificationaccuracies. Our results show that MNS may provide a foundation for an innovative BCIthat would allow the detection of AAGA

SatIPSec : an optimized solution for securing multicast and unicast satellite transmissions

International audienceIn satellite networks, the security of data exchanged on the satellite segment is threatened by many types of attacks such as eavesdropping, intrusion of unauthorized satellite terminals, satellite terminal cloning... The integration of security mechanisms is therefore considered today as an essential requirement. Some existing solutions may be recommended, however they do not offer all the necessary security services. For instance, the optional security mechanisms defined in the DVB-RCS standard provide insufficient security support, especially in satellite networks with natural broadcast/multicast capability over large areas. The use of well-known upper layers security protocols such as SSL (Secure Socket Layer) or IPSec/IKE can be considered too, but they are dedicated to unicast communications. The SatIPSec solution has been designed to provide an optimized and adapted security solution for satellite networks. It offers a new way of transparently and efficiently securing unicast and multicast satellite transmissions, with a strong access control, data confidentiality, data integrity, and data authentication as security services. SatIPSec has recently been implemented in a demonstrator developed in the context of the SATIP6 IST project. In this implementation, which allows to manage centrally secure multicast groups and Virtual Private Networks, key distribution is achieved according to the “Flat Multicast Key Exchange” protocol of SatIPSec, and data are encrypted and authenticated according to the IPSec protocol adapted to multicast. This paper introduces the principles of the security mechanisms involved in SatIPSec, and presents the features of the implementation and its results

Use of invertebrate traits for the Biomonitoring of European large rivers : the effects of sampling effort on genus richness and functional diversity

International audienc