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Galvanic Skin Response

Galvanic Skin Response. B.HEMA KUMAR. Motivation. Regular EEG does not work for everyone An easy to setup portable system is often more practical. Possible alternatives. fMRI GSR fNIR …. The Galvanic Skin Response. Known as a lie detector Costs anywhere from 5-10k

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Galvanic Skin Response

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  1. Galvanic Skin Response B.HEMA KUMAR

  2. Motivation • Regular EEG does not work for everyone • An easy to setup portable system is often more practical

  3. Possible alternatives • fMRI • GSR • fNIR • …

  4. The Galvanic Skin Response • Known as a lie detector • Costs anywhere from 5-10k • Consists of 2 electrodes usually placed on fingers • Measures electrical conductivity of skin • Sweat = Na+ ions • More sweat, more conductivity

  5. Galvanic Skin Response • The GSR is affected when the sympathetic nervous system is active, in particular when a person is anxious

  6. GSR for Control • If voluntarily change GSR level, then we have a biometric switch

  7. How to control GSR • Thinking of exciting imagery usually causes one to sweat more • Calm, relaxing thoughts do the opposite • Other interesting imagery • Multiplying numbers • Blank wall • Lifting weights

  8. GSR with thresholding

  9. Thresholding issues • Where to set the threshold? • What if baseline level changes during trial? • What will happen if threshold • Too high? • Too Low?

  10. Thresholding results Results over 10 runs • Baseline phase accuracy = 52.1% • Accuracy when controlling = 62%

  11. GSR Artifacts • Ideally we want gsr to look like • But if often looks like

  12. Factors affecting GSR • Temperature • Attention • Fatigue • Predictability • Consecutive yes generation • Training? (not proven yet)

  13. Improving accuracy • Raise temperature • Provide user with different stimuli to focus on when trying to say “no” and “yes” • Experimented with Audio and Visual input • Baseline after activation

  14. Visual Input • Looked at difference between “Judge Judy” and “Golf game” • Golf game = 2.6 peaks with peak strength = 834 • Judge Judy = 1.7 peaks with peak strength = 211 • Why?

  15. Auditory Input • Subject listened to book on tape • Average peak strength = 90 • Having a subject focus on a story on tape helps to keep “no” stable.

  16. Predictability • If subject can predict next choice, it gives them advance notice on what to do. • Double edged sword • Can improve performance because more time to generate “yes” • Can cause misfires because of anticipation

  17. Baseline after activation • Subjects could not give 2 yes’s in a row, too tiring • Once subject gives “yes”, give X seconds to relax and establish baseline.

  18. Algorithms • Simple thresholding is ok, but requires manual intervention often • Need automated algorithm to detect “yes” and “no”

  19. Temporal peak comparison • Compare largest peaks across trials • If current largest peak > X * previous largest peak, it’s a “yes” • Empirically we found accuracy is max at X = 1.3

  20. Spelling Interface Letters appear in order of probability If X items, presents sqrt(X) items at a time if X>9

  21. Disadvantages of GSR • VERY slow • Fastest with able bodied subjects was 6 bit/min • Fastest with locked-in subjects was 3 bit/min • Very demanding, within 15-20 min user is tired • Only a “YES” indicates a confirmation, which further lowers information throughput.

  22. Successes • Able bodied subjects have spelled names with 90-100% accuracy with no training • Locked in subject communicated “NE” when asked to spell “NEIL”, then got tired. • Often communicates basic needs using a number chart

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