Bri503 lecture05

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  • 1. HOW DOES A BCI WORK?Monday, March 19, 2012
  • 2. MOTOR IMAGERY Sensorimotor rhythms (SMR) Detected in the sensorimotor area Somatosensory cortex Motor cortex Mu rhythms: 8-12 Hz Beta rhythms: 12-30Hz ECoG can also use gamma rhythms (30-80Hz)Monday, March 19, 2012
  • 3. MOTOR IMAGERY ERD (Event Related Desynchronization) Planning and execution of hand/finger movements block (desynchronize) mu rhythms ERS (Event Related Synchronization) Inhibition of movements synchronizes mu rhythms Foot and tongue movements enhance mu rhythms ERD/ERS is generally observed for the contralateral movementsMonday, March 19, 2012
  • 4. MOTOR IMAGERY Does not need external stimuli Does need long training Users learn the best imagery Closed-loop feedback plays an important role in learningMonday, March 19, 2012
  • 5. SIGNAL PROCESSING - Simplifies signals: e.g. filtering Preprocessing - Improves the signal-to-noise ratio (SNR) - Extract features relevant to control parameters using Feature mathematical methods Extraction - e.g. Amplitudes, Frequencies, Firing rates, ... - Detection: detects specific patterns from ordinary Detection/ patterns Classification - Classification: classifies a given pattern to one of many variablesMonday, March 19, 2012
  • 6. SIGNAL PROCESSING Synchronous BCIs Cue-paced Operates a BCI with a fixed time frame Asynchronous BCIs Self-paced Operates a BCI whenever the user wantsMonday, March 19, 2012
  • 7. BCI PERFORMANCEMonday, March 19, 2012
  • 8. PERFORMANCE MEASURES Classification Rate (= 1 - Error Rate) # correct / total attempts Letters / minute for a speller Information transfer rate (ITR) Depends on classification accuracy, performance time, and # classes Bits / minute Ball park: 30 bits/min ~ 90 bits/min (?)Monday, March 19, 2012
  • 9. CONFUSION MATRIX Estimated As Estimated As Positives Negatives True Positives False Negatives Sensitivity = Positives (TP) (FN) TP / (TP + FN) False Positives True Negatives Specificity = Negatives (FP) (TN) TN / (TN + FP)Monday, March 19, 2012
  • 10. BCI APPLICATIONSMonday, March 19, 2012
  • 11. BCI OUTPUT Discrete output (Discrete State Variables) Output = one of N possible values e.g. “go” / “stop” Continuous output (Continuous State Variables) Output = continuous values, probably within a finite or infinite range e.g. position on a 2D spaceMonday, March 19, 2012
  • 12. Fig. 7 Examples of BCI applications. (a) Environmental control with a P300 BCI (see chapter “The First Commercial Brain–Computer Interface Environment”), (b) P300 Speller (see chapterMonday, March 19, 2012
  • 13. SMART HOME CONTROLMonday, March 19, 2012
  • 14. NAVIGATION IN VRMonday, March 19, 2012
  • 15. 2D CURSOR CONTROLMonday, March 19, 2012
  • 16. CONTROL LEVEL Low-level High-level Process-oriented Goal-oriented control control e.g. move a cursor to a e.g. move a cursor in target #4 45 degree with a speed of 2cm/s at this All the details are time instant (for 50ms) managed by an actuator More specific More generalMonday, March 19, 2012
  • 17. It is system based on a conventional wheelchair equipped with a stereo camera sys- tem, a robot arm with 7 degrees-of-freedom, a gripper with force/torque sensor, a smart tray with tactile surface and weight sensors, and a computing unit consist- ing of three independent industrial PCs. FRIEND II can perform certain operations Rolland III FRIEND II Fig. 8 Semi-autonomous assistive devices developed at the University of Bremen that include high level control: Intelligent wheelchair Rolland III, and rehabilitation robot FRIEND II (modified from [35])Monday, March 19, 2012
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  • 22. CURRENT LIMITS OF BCIS Reliability Nonstationary brain signals Sensitive to noise Bandwidth Low information transfer per second Less competitive than conventional techniques Healthy subjects: keyboards, mouse, speech, ... Disabled subjects: eye-tracker, head mouse, ...Monday, March 19, 2012
  • 23. WILL NORMAL PEOPLE USE BCIS? Yes if, combined with intelligent systems bandwidth continues to improve used as an augmented interface more accessible by general researchers (e.g. HCI fields, robotics fields, ...)Monday, March 19, 2012
  • 24. APPLICATION IN NEUROFEEDBACK A BCI can be thought as the most advanced neurofeedback system A BCI can be applied to neurorehabilitation fields where neurofeedback is necessary ADHD Autism Epilepsy StrokeMonday, March 19, 2012
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