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Braincomputerinterface ppt

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Bhadra Gowdra
Bhadra Gowdra

This document provides an overview of brain-computer interfaces (BCI). It discusses the human brain and electroencephalography. It describes two approaches to BCI - pattern recognition based on mental tasks and operant conditioning based on self-regulation of EEG signals. The document outlines the hardware, software, and basic working process of BCI systems. It also covers feedback types, drawbacks, innovators in the field, and applications of BCI technologies. The conclusion evaluates experiments with an adaptive brain interface system.

Technology
1 of 16
G.BHADRA 1
CONTENTS  INTRODUCTION  THE HUMAN BRAIN  ELECTROENCEPHALOGRAPHY  BCI APPROACHES  HARDWARE & SOFTAWARE REQUIRED  HOW BCI WORKS  BCI FEEDBACK  DRAWBACKS & INNOVATORS  APPLICATIONS  CONCLUSION 03/31/17BRAIN COMPUTER INTERFACE 2
INTRODUCTION  THE BRAIN COMPUTER INTERFACE.  BCI Systems are systems that uses Brain signals (Electrical, Magnetic , Metabolic) to Control external devices such as computers, switches, wheelchairs, or neuroprosthesses . Various Techniques used: FMRI, MEG, PET, SPECT, Optical brain imaging , single Neuron recording (with micro- Electrodes) & ElectroEnce – phaloGraphy (EEG). 03/31/17BRAIN COMPUTER INTERFACE 3
THE HUMAN BRAIN  MAJOR PART OF BRAIN WHICH SUPPORTS BCI  Brain divided in 4 parts:  Cerebral Cortex  Cerebellum  Brain stem  Hypothalamus & Thalamus 03/31/17BRAIN COMPUTER INTERFACE 4 Fig 3: Human Brain
ELECTROENCEPHALOGRAPHY(EEG)  CONCEPT OF EEG  PROPERTIES OF EEG:  RYTHMIC BRAIN ACTIVITY,  COMMON EEG FREQUENCY RANGES,  EVENT RELATED POTENTIALS (ERP`S),  EVENT RELATED DESYNCHRO- NIZATION (ERD)  EVENT RELATED SYNCHRINIZATION (ERS) 03/31/17BRAIN COMPUTER INTERFACE 5 Fig 4 : EEG frequency
BCI APPROACHES  TWO DIFFERENT BCI APPROACHES :  PATTERN RECOGNITION APPROACH BASED ON MENTAL TASK .  OPERANT CONDITIONING APPROACH BASED ON SELF REGULATION OF EEG . 03/31/17BRAIN COMPUTER INTERFACE 6
HARDWARE REQUIREMENTS  ELECTROENCEPHALO PROCESSOR MODEL H11 (EEPH11)  EEG DEVICE  ELECTRODE CAP  EEG AMPLIFIERE  FIBRE OPTIC CABLE  COMPUTER OR SUBJECT SCREEN 03/31/17BRAIN COMPUTER INTERFACE 7
SOFTWARE REQUIREMENTS  EEP H11 SERVER  ABI LEARNING PROGRAME  ABI ONLINE PROGRAME  ABI VISUALIZATION PROGRAME 03/31/17BRAIN COMPUTER INTERFACE 8
HOW BCI WORKS  IT HAS SIX STAGES:  GENERATION OF SIGNALS FROM BRAIN 03/31/17BRAIN COMPUTER INTERFACE 9
HOW BCI WORKS  MEASUREMENT OF EEG,  PREPROCESSING,  FEATURE EXTRACTION,  CLASSIFICATION,  DEVICE CONTROL. 03/31/17BRAIN COMPUTER INTERFACE 10
BCI FEEDBACK  BIOFEEDBACK IN GENERAL  EEG BIOFEEDBACK  FEEDBACKS IN BCI 03/31/17BRAIN COMPUTER INTERFACE 11 Fig 6 : BCI Feedback
BCI FEEDBACKS  EFFECT OF FFEDBACK :  BENEFICIAL FEEDBACK.  FURNISHES BENEFICIAL MOTIVATION.  ENSURES ATTENTION TO THE TASK BY MAINTAINING SUBJECT`S INTEREST.  IMPROVES PERFORMANCE BY RAPID REACTION TO WRONG CLASSIFICATION.  HARMFUL FEEDBACK.  FEEDBACK STIMULUS MIGHT PREVENT CONCENTRATION ON INTERNAL STATES.  FALSE CLASSIFICATION CAN ELICIT FRUSTRATION & THUS AFFECT THE EEG RESPONSE.  VISUAL FEEDBACK STIMULUS AFFECT ALPHA RHYTHM . 03/31/17BRAIN COMPUTER INTERFACE 12
BCI DRAWBACKS  THE DRAWBACKS OF BCI :  THE BRAIN IS INCREDIBLY COMPLEX,  THE SIGNAL IS WEAK & PRONE TO INTERFENCE,  THE EQUIPMENTS IS LESS THAN PORTABLE, 03/31/17BRAIN COMPUTER INTERFACE 13
BCI INNOVATORS  PIONEERS  NASA  CYBERKINETICS NEUROTECHNOLOGY SYSTEM,  JAPANESE REASERCH TEAM 03/31/17BRAIN COMPUTER INTERFACE 14
APPLICATIONS OF BCI  CONTROL A ROBOT  PLAYING GAMES  FOR PHYSICALLY WEAK PERSONS TO HANDLE THE COMPUTER  CURSOR CONTROL 03/31/17BRAIN COMPUTER INTERFACE 15
CONCLUSION 03/31/17BRAIN COMPUTER INTERFACE 16 In this work EEG-based brain computer interface systems were reviewed and compared. Experiments lasting five days with three subjects were done with the new Adaptive Brain Interface system. The comparison of the BCI systems, especially their training duration and performance, proved to be difficult. This was because the results were reported differently in most of the papers. Reporting the experiments and results should be standardized.

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Braincomputerinterface ppt

  • 2. CONTENTS  INTRODUCTION  THE HUMAN BRAIN  ELECTROENCEPHALOGRAPHY  BCI APPROACHES  HARDWARE & SOFTAWARE REQUIRED  HOW BCI WORKS  BCI FEEDBACK  DRAWBACKS & INNOVATORS  APPLICATIONS  CONCLUSION 03/31/17BRAIN COMPUTER INTERFACE 2
  • 3. INTRODUCTION  THE BRAIN COMPUTER INTERFACE.  BCI Systems are systems that uses Brain signals (Electrical, Magnetic , Metabolic) to Control external devices such as computers, switches, wheelchairs, or neuroprosthesses . Various Techniques used: FMRI, MEG, PET, SPECT, Optical brain imaging , single Neuron recording (with micro- Electrodes) & ElectroEnce – phaloGraphy (EEG). 03/31/17BRAIN COMPUTER INTERFACE 3
  • 4. THE HUMAN BRAIN  MAJOR PART OF BRAIN WHICH SUPPORTS BCI  Brain divided in 4 parts:  Cerebral Cortex  Cerebellum  Brain stem  Hypothalamus & Thalamus 03/31/17BRAIN COMPUTER INTERFACE 4 Fig 3: Human Brain
  • 5. ELECTROENCEPHALOGRAPHY(EEG)  CONCEPT OF EEG  PROPERTIES OF EEG:  RYTHMIC BRAIN ACTIVITY,  COMMON EEG FREQUENCY RANGES,  EVENT RELATED POTENTIALS (ERP`S),  EVENT RELATED DESYNCHRO- NIZATION (ERD)  EVENT RELATED SYNCHRINIZATION (ERS) 03/31/17BRAIN COMPUTER INTERFACE 5 Fig 4 : EEG frequency
  • 6. BCI APPROACHES  TWO DIFFERENT BCI APPROACHES :  PATTERN RECOGNITION APPROACH BASED ON MENTAL TASK .  OPERANT CONDITIONING APPROACH BASED ON SELF REGULATION OF EEG . 03/31/17BRAIN COMPUTER INTERFACE 6
  • 7. HARDWARE REQUIREMENTS  ELECTROENCEPHALO PROCESSOR MODEL H11 (EEPH11)  EEG DEVICE  ELECTRODE CAP  EEG AMPLIFIERE  FIBRE OPTIC CABLE  COMPUTER OR SUBJECT SCREEN 03/31/17BRAIN COMPUTER INTERFACE 7
  • 8. SOFTWARE REQUIREMENTS  EEP H11 SERVER  ABI LEARNING PROGRAME  ABI ONLINE PROGRAME  ABI VISUALIZATION PROGRAME 03/31/17BRAIN COMPUTER INTERFACE 8
  • 9. HOW BCI WORKS  IT HAS SIX STAGES:  GENERATION OF SIGNALS FROM BRAIN 03/31/17BRAIN COMPUTER INTERFACE 9
  • 10. HOW BCI WORKS  MEASUREMENT OF EEG,  PREPROCESSING,  FEATURE EXTRACTION,  CLASSIFICATION,  DEVICE CONTROL. 03/31/17BRAIN COMPUTER INTERFACE 10
  • 11. BCI FEEDBACK  BIOFEEDBACK IN GENERAL  EEG BIOFEEDBACK  FEEDBACKS IN BCI 03/31/17BRAIN COMPUTER INTERFACE 11 Fig 6 : BCI Feedback
  • 12. BCI FEEDBACKS  EFFECT OF FFEDBACK :  BENEFICIAL FEEDBACK.  FURNISHES BENEFICIAL MOTIVATION.  ENSURES ATTENTION TO THE TASK BY MAINTAINING SUBJECT`S INTEREST.  IMPROVES PERFORMANCE BY RAPID REACTION TO WRONG CLASSIFICATION.  HARMFUL FEEDBACK.  FEEDBACK STIMULUS MIGHT PREVENT CONCENTRATION ON INTERNAL STATES.  FALSE CLASSIFICATION CAN ELICIT FRUSTRATION & THUS AFFECT THE EEG RESPONSE.  VISUAL FEEDBACK STIMULUS AFFECT ALPHA RHYTHM . 03/31/17BRAIN COMPUTER INTERFACE 12
  • 13. BCI DRAWBACKS  THE DRAWBACKS OF BCI :  THE BRAIN IS INCREDIBLY COMPLEX,  THE SIGNAL IS WEAK & PRONE TO INTERFENCE,  THE EQUIPMENTS IS LESS THAN PORTABLE, 03/31/17BRAIN COMPUTER INTERFACE 13
  • 14. BCI INNOVATORS  PIONEERS  NASA  CYBERKINETICS NEUROTECHNOLOGY SYSTEM,  JAPANESE REASERCH TEAM 03/31/17BRAIN COMPUTER INTERFACE 14
  • 15. APPLICATIONS OF BCI  CONTROL A ROBOT  PLAYING GAMES  FOR PHYSICALLY WEAK PERSONS TO HANDLE THE COMPUTER  CURSOR CONTROL 03/31/17BRAIN COMPUTER INTERFACE 15
  • 16. CONCLUSION 03/31/17BRAIN COMPUTER INTERFACE 16 In this work EEG-based brain computer interface systems were reviewed and compared. Experiments lasting five days with three subjects were done with the new Adaptive Brain Interface system. The comparison of the BCI systems, especially their training duration and performance, proved to be difficult. This was because the results were reported differently in most of the papers. Reporting the experiments and results should be standardized.
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