Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                

Lesenfants et al., 2014 - Google Patents

An independent SSVEP-based brain–computer interface in locked-in syndrome

Lesenfants et al., 2014

View PDF
Document ID
6900522216092537016
Author
Lesenfants D
Habbal D
Lugo Z
Lebeau M
Horki P
Amico E
Pokorny C
Gómez F
Soddu A
Müller-Putz G
Laureys S
Noirhomme Q
Publication year
Publication venue
Journal of neural engineering

External Links

Snippet

Objective. Steady-state visually evoked potential (SSVEP)-based brain–computer interfaces (BCIs) allow healthy subjects to communicate. However, their dependence on gaze control prevents their use with severely disabled patients. Gaze-independent SSVEP-BCIs have …
Continue reading at orbi.uliege.be (PDF) (other versions)
  • 201000000251 locked-in syndrome 0 title abstract description 41

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476Electroencephalography
    • A61B5/0484Electroencephalography using evoked response
    • A61B5/04842Electroencephalography using evoked response visually
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402Electrocardiography, i.e. ECG
    • A61B5/0452Detecting specific parameters of the electrocardiograph cycle
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0488Electromyography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/16Devices for psychotechnics; Testing reaction times; Devices for evaluating the psychological state
    • A61B5/165Evaluating the state of mind, e.g. depression, anxiety
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/40Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076Diagnosing or monitoring particular conditions of the nervous system
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/05Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radiowaves
    • A61B5/053Measuring electrical impedance or conductance of a portion of the body
    • A61B5/0531Measuring skin impedance
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation, e.g. heart pace-makers
    • A61N1/36014External stimulators, e.g. with patch electrodes
    • A61N1/36025External stimulators, e.g. with patch electrodes for treating a mental or cerebral condition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data

Similar Documents

Publication Publication Date Title
Lesenfants et al. An independent SSVEP-based brain–computer interface in locked-in syndrome
Waytowich et al. Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials
Biasiucci et al. Electroencephalography
Ng et al. Stimulus specificity of a steady-state visual-evoked potential-based brain–computer interface
Hill et al. An online brain–computer interface based on shifting attention to concurrent streams of auditory stimuli
Won et al. Effect of higher frequency on the classification of steady-state visual evoked potentials
Pasqualotto et al. Toward functioning and usable brain–computer interfaces (BCIs): A literature review
Jochumsen et al. Detection and classification of movement-related cortical potentials associated with task force and speed
Brouwer et al. Estimating workload using EEG spectral power and ERPs in the n-back task
Horki et al. Combined motor imagery and SSVEP based BCI control of a 2 DoF artificial upper limb
Ahn et al. Achieving a hybrid brain–computer interface with tactile selective attention and motor imagery
Martel et al. EEG predictors of covert vigilant attention
Severens et al. A multi-signature brain–computer interface: use of transient and steady-state responses
Pfurtscheller et al. Discrimination of motor imagery‐induced EEG patterns in patients with complete spinal cord injury
Lim et al. Classification of binary intentions for individuals with impaired oculomotor function:‘eyes-closed’SSVEP-based brain–computer interface (BCI)
Jepma et al. The effects of accessory stimuli on information processing: evidence from electrophysiology and a diffusion model analysis
Tonin et al. An online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation
Aloise et al. A comparison of classification techniques for a gaze-independent P300-based brain–computer interface
Wan et al. Alpha neurofeedback training improves SSVEP-based BCI performance
Thurlings et al. Does bimodal stimulus presentation increase ERP components usable in BCIs?
Won et al. P300 speller performance predictor based on RSVP multi-feature
Furdea et al. A new (semantic) reflexive brain–computer interface: in search for a suitable classifier
Hsu et al. Extraction of high-frequency SSVEP for BCI control using iterative filtering based empirical mode decomposition
Brandl et al. Brain–computer interfacing under distraction: an evaluation study
Grosse-Wentrup et al. A brain–computer interface based on self-regulation of gamma-oscillations in the superior parietal cortex