Song et al., 2014 - Google Patents

Mobile robot control by BCI based on motor imagery

Song et al., 2014

Document ID
13032350700118853077
Author
Song W
Wang X
Zheng S
Lin Y
Publication year
Publication venue
2014 Sixth International Conference on Intelligent Human-Machine Systems and Cybernetics

External Links

Snippet

Current interests in BCI development mainly derive from rehabilitation engineering, assistant control for normal people, entertainment, brain cognition, and so on. This paper has developed an online mobile robot control system by BCI based on motor imagery (MI). In the …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0476—Electroencephalography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7232—Signal processing specially adapted for physiological signals or for diagnostic purposes involving compression of the physiological signal, e.g. to extend the signal recording period
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0488—Electromyography
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input 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
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection

Similar Documents

Publication Publication Date Title
Kumar et al. Comparative analysis to identify efficient technique for interfacing BCI system
Bi et al. EEG-based brain-controlled mobile robots: a survey
Benalcázar et al. Hand gesture recognition using machine learning and the Myo armband
Aljalal et al. Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals
Sadiq et al. A matrix determinant feature extraction approach for decoding motor and mental imagery EEG in subject-specific tasks
Bascil et al. Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN
Lahane et al. A review of recent trends in EEG based Brain-Computer Interface
Esfahani et al. Using brain–computer interfaces to detect human satisfaction in human–robot interaction
Liu et al. Cognitive neuroscience and robotics: Advancements and future research directions
Song et al. Mobile robot control by BCI based on motor imagery
Zhang et al. Clustering linear discriminant analysis for MEG-based brain computer interfaces
Hamedi et al. Human facial neural activities and gesture recognition for machine-interfacing applications
Lashgari et al. An end-to-end CNN with attentional mechanism applied to raw EEG in a BCI classification task
Mohamed et al. Comparison of EEG signal decomposition methods in classification of motor-imagery BCI
Jeong et al. Decoding of multi-directional reaching movements for EEG-based robot arm control
Mahajan et al. A real time set up for retrieval of emotional states from human neural responses
Padmavathi et al. A review on EEG based brain computer interface systems
Li et al. Wireless sEMG-based identification in a virtual reality environment
Zhang et al. A hybrid EEG-based BCI for robot grasp controlling
Bhalerao et al. Automatic detection of motor imagery EEG signals using swarm decomposition for robust BCI systems
Lee et al. Source-free subject adaptation for eeg-based visual recognition
Forney et al. Echo state networks for modeling and classification of EEG signals in mental-task brain-computer interfaces
Özdenizci et al. On the use of generative deep neural networks to synthesize artificial multichannel EEG signals
Jubien et al. Decoding of finger activation from ECoG data: a comparative study
Ramakrishna et al. Classification of human emotions using EEG-based causal connectivity patterns