UbiBraille: Designing and Evaluating a Vibrotactile Braille-Reading Device.
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UbiBraille: Designing and Evaluating a Vibrotactile Braille-Reading Device.

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Research paper presented at SIGACCESS ASSETS 2013

Research paper presented at SIGACCESS ASSETS 2013

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UbiBraille: Designing and Evaluating a Vibrotactile Braille-Reading Device. Presentation Transcript

  • 1. U BI B RAILLE Designing and Evaluating a Vibrotactile Braille-Reading Device HUGO  NICOLAU   JOÃO  GUERREIRO   TIAGO  GUERREIRO   LUÍS  CARRIÇO  
  • 2. motivation :: constantly online
  • 3. blind users :: auditory feedback
  • 4. challenge :: alternative modality
  • 5. problem :: deaf-blind users
  • 6. problem :: mobile usage
  • 7. problem :: noisy environments
  • 8. problem :: privacy
  • 9. earphones?
  • 10. goal :: inconspicuous and private
  • 11. [Al-Qudah et al, 2011] [Jayant et al, 2010] [Ohtsuka et al, 2008] [Rantala et al, 2009] related work
  • 12. our approach :: UbiBraille
  • 13. inspiration :: perkins brailler
  • 14. example :: ‘a’
  • 15. example :: ‘b’
  • 16. same approach for reading
  • 17. Six rings Lilypad vibe board Vibration motor (10 mm), 3,8 Volts Arduino Mega ADK board ubibraille :: hardware
  • 18. ubibraille :: ‘b’
  • 19. advantage :: mnemonic
  • 20. advantage :: speed
  • 21. 1. Will participants be able to discriminate simultaneous stimuli?
  • 22. 2. Will participants be able to leverage Braille knowledge?
  • 23. 3. What are the most common error patterns?
  • 24. 11 blind participants (8 male, 3 female) Ages 21 – 61 (m=45, sd=16) Braille typists user study :: character recognition
  • 25. assessment :: braille proficiency
  • 26. user study :: procedure
  • 27. 26 letters x 2 blocks 1. Audio signal 2. Delay (2 seconds) 3. Random braille character (from 26 letters) 4. Answer 5. Monitor register answer user study :: procedure
  • 28. results :: character recognition
  • 29. 82% 60% 50% 40% sd=17.25% 30% 20% 10% overall accuracy 0% a b c d e f g h i j k l m n o p q r s t u v w x y z
  • 30. error rate per character 60% 50% 40% 30% 20% 10% 0% a b c d e f g h i j k l m n o p q r s t u v w x y z
  • 31. ‘novyz’ are harder 60% 55% 50% 40% 36% 32% 32% 32% 30% 20% 10% 0% a b c d e f g h i j k l m n o p q r s t u v w x y z
  • 32. ‘novyz’ are harder N O V Y Z 60% 55% 50% 40% 36% 32% 32% 32% 30% 20% 10% 0% a b c d e f g h i j k l m n o p q r s t u v w x y z
  • 33. 51.6% error pattern :: 1 finger issues
  • 34. N O Q R V 1 finger error :: insertion Y Z
  • 35. N O V Y Z Q R U X U 1 finger error :: omission
  • 36. 25.3% error pattern :: 2 finger issues
  • 37. Z X 25.3% error pattern :: 2 finger issues
  • 38. accuracy rate per participant 100% 80% 60% 40% 20% 0% P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
  • 39. result :: individual differences 100% 80% 60% 40% 20% 0% P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
  • 40. [rho=.571, p=.066, N=11] leverage braille knowledge :: reading
  • 41. [rho=.627, p=.039, N=11] leverage braille knowledge :: writing
  • 42. Memory
  • 43. 82% overall accuracy More fingers, more errors Mostly 1-finger errors Leverage braille knowledge character recognition :: major results
  • 44. user study #2 :: word recognition
  • 45. 7 blind participants (from study #1) Ages 21 – 62 user study :: participants
  • 46. 1. Audio signal 2 times 2. Delay (2 seconds) 3. Random word 4. Answer 5. Monitor register answer user study :: procedure
  • 47. ‘a’ ‘c’ stimulus ‘t’ interval Condition Stimulus (ms) Interval (ms) 4000ms 2000 2000 2000ms 1000 1000 1000ms 500 500 500ms 250 250 user study :: conditions ‘o’ ‘r’
  • 48. 4 conditions (randomized) 10 words per condition 280 trials 5 characters per word Commonly used words (Portuguese) user study :: design
  • 49. results :: word recognition
  • 50. recognition accuracy rate 100% 80% 60% 40% 20% 0% 93% 89% 64% 33% 4000ms 2000ms 1000ms 500ms Error bars denote 95% CI
  • 51. recognition accuracy rate No sig. diff. p>.05 100% 80% 60% 40% 20% 0% 93% 89% 64% 33% 4000ms 2000ms 1000ms 500ms Error bars denote 95% CI
  • 52. recognition accuracy rate Z=-2.041, p<.05 100% 80% 60% 40% 20% 0% 93% 89% 64% 33% 4000ms 2000ms 1000ms 500ms Error bars denote 95% CI
  • 53. recognition accuracy rate Z=-2.379, p<.05 100% 80% 60% 40% 20% 0% 93% 89% 64% 33% 4000ms 2000ms 1000ms 500ms Error bars denote 95% CI
  • 54. [rho=.805, p<.05, N=7] [rho=.543, p=.208, N=7] leverage braille knowledge :: reading and writing
  • 55. Identify through context
  • 56. Condition 4000ms 2000ms 1000ms 500ms Median 5 5 3 2 IQR 1 2 2 1 likert scale [1-5] : 5 is better word recognition :: ease of use
  • 57. Condition 4000ms 2000ms 1000ms 500ms Median 5 5 3 2 IQR 1 2 2 1 likert scale [1-5] : 5 is better longest durations are easier
  • 58. Condition 4000ms 2000ms 1000ms 500ms Median 5 5 3 2 IQR 1 2 2 1 Z=-2.530, p<.05 Z=-2.428, p<.05 likert scale [1-5] : 5 is better longest durations are easier
  • 59. 1s duration + 1s interval à 90% leverage braille knowledge 12 wpm room for improvements word recognition :: major results
  • 60. conclusion :: ubibraille
  • 61. conclusion :: inconspicuous communication
  • 62. conclusion :: leverage braille-related abilities
  • 63. conclusion :: character- and word-level results
  • 64. future work :: ubibraille
  • 65. future work :: finger discrimination
  • 66. future work :: new applications
  • 67. future work :: multi-point feedback
  • 68. The End. HUGO NICOLAU hugonicolau@computing.dundee.ac.uk paper and slides @ http:/ /web.ist.utl.pt/hugo.nicolau