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Audica ™

Nov 30, 2007. Audica ™. VChoice Innovation presents…. A better way to communicate ®. Team Formation. Consists of four dedicated engineers Caroline Chen Biomedical Engineer Micky Pun Computer Engineer Richard Tang Computer Engineer Jeramy Wu Computer Engineer. Contents. Background

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Audica ™

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  1. Nov 30, 2007 Audica™ VChoice Innovation presents… A better way to communicate®

  2. Team Formation • Consists of four dedicated engineers • Caroline Chen • Biomedical Engineer • Micky Pun • Computer Engineer • Richard Tang • Computer Engineer • Jeramy Wu • Computer Engineer

  3. Contents • Background • Design Process • System Integration • Results • Applications & Features • Project Aspects • Conclusion

  4. Background Purpose & Vision

  5. Facts • Amyotrophic lateral sclerosis (ALS) is an incurable neuromuscular disease. • One’s motor neurons degenerate leading to losing control over voluntary muscles. • 2new cases of ALS are diagnosed every year per 100 000 individuals, 2500 of which are Canadians. • It can happen to anyone at any time with an average of 3-5 year life expectancy after onset of the disease. • 20% of the diagnosed will survive more than 5 years, and longer with the advancement of medical treatments.

  6. Problem • People with ALS would eventually become breathing-impaired and rely on a respiratory machine. • Noise produced by the respiratory machine, along with the deterioration of speech muscles, together would make their voice slurry and unrecognizable. • Communication is critical between a person living with ALS and his or her family members, therapist, caregivers, and anyone around.

  7. BiPAP™ Machine • BiPAP™ • Bi-level Positive Airway Pressure • A non-invasive apparatus that helps patients experiencing respiratory failure to breathe

  8. BiPAP™ Machine

  9. Solution • Our team is proposing a speech enhancer which: • Works in conjunction with a BiPAP™ • Suppresses ambient noise • Improves speech intelligibility • Promises comfort • Guarantees low-cost

  10. Design Process Design and Considerations

  11. Design Process • Requirements elicitations • Examine the BiPAP™ machine • Contact persons living with ALS • Visit PROP • Functional specifications • Three categories • Core • Less core • Development phase

  12. Design Process • Design • Phase 1: Noise reduction • Phase 2: Intelligibility improvement • Simulation • Evaluate performance • Iterative implementation • Continuous refinements • Verifications and validations • Compare with simulation results

  13. System Integration Design Consideration

  14. System Integration • We have looked into multiple solutions for voice reception • Throat microphone • Microphone in mask • Microphone in tube

  15. System Integration Throat Microphone Microphone in mask

  16. System Integration • Inverted Y-connector • Small branch for microphone integration and speech reception • Top part is a rubber gasket • Connect between the mask and the BiPAP™ hose • Prevent wind noise from directing at microphone

  17. System Integration

  18. System Integration • For final product, there are three components: • Y-Connector with microphone integrated within it • Processing module with one button for turning the system on and off • Speaker with volume adjustment

  19. Product Realization

  20. Speech Intelligibility Linear Predictive Coding

  21. Speech Intelligibility • Linear Predictive Coding • Adjust vowel sound • Re-create speech using adjusted vowel sound • Matlab Simulation • No significant improvement • No further investigation due to time constraint

  22. Noise Reduction Algorithm Choice

  23. Research Conducted • Research conducted by Dynastat • 32 participants • 4 classes of filters • 4 different environments

  24. Filters Performance

  25. Audica™ Filter • Statistical and wiener filters have superior performances in general • We adapted modified version of statistical filter at the end • Assumptions made about noise closely models the BiPAP noise™

  26. Results • We performed subjective listening tests, • Noise reduction is significant • Intelligibility for daily conversation is high • To quantize the result in numbers • Correlation between the input and output • 89.1% • Noise was reduced by 19.47dB (88x) !

  27. Results • The algorithm has successfully removed the noise. Original Noise Contaminated WavePad Filter Audica™ Filter

  28. Applications & Features For Various Environments

  29. Applications • We are submerged in noisy environments • Air conditioning • PC and office equipment • Vacuum cleaners • Radio channel • Motor vehicle noise • Machinery • Appliances, power tools • … etc

  30. Applications • Persons using BiPAP™ • Home and hospital • Industrial Workers • Pilots • Scuba Divers • Broadcasting Companies

  31. C3

  32. C3 - Comfort • No physical contact between the microphone and the user to avoid extra skin break-down • Light-weight

  33. C3 - Convenience • Simple plug-and-play design • Superior performance in various environments • Train station, busy intersections, and highways

  34. C3 – Cost-efficiency • Mass Production Cost: • Development kit is much more costly due to prototyping purposes • After consulting with a professional engineer • Production cost of the base unit would be ~$50 • Microphones ~$1 • Speakers ~$10

  35. Other Features • Real-time adaptive noise filter • Stylish casing • Voice Activation Detection (VAD)

  36. Project Aspects Finance and Timelines

  37. Budget • Proposed Project Costs vs. Actual Project Costs Difference between Proposed/Actual costs = ($512)

  38. Timeline • Proposed Timeline

  39. Timeline • Actual Timeline

  40. Conclusion Final Thoughts & Acknowledgement

  41. Conclusion • What could be done better? • Skills learned • Technical skills • Soft skills

  42. Conclusion • Future Plans • Optimization of the Statistical Model Filter • Slower DSP can be utilized – lower cost • System Portability • System powered by rechargeable battery • Further Research of LPC • Integration of speech intelligibility into the system

  43. Acknowledgments • Dr. Andrew Rawicz • Wighton Professor for Engineering Development, School of Engineering Science, SFU • Mr. Mike Sjoerdsma • Lecturer, School of Engineering Science, SFU • Mr. Brad Oldham • Teaching Assistant, School of Engineering Science, SFU • Ms. Lisette Paris-Shaadi • Teaching Assistant, School of Engineering Science, SFU • Dr. John Bird • Professor, School of Engineering Science, SFU • Dr. Patrick Leung • Professor, School of Engineering Science, SFU

  44. Acknowledgments • Dr. Jim McEwen • President, ALS Society of British Columbia • Mr. Simon Cox • Executive Director, Provincial Respiratory Outreach Program • Mr. Les • Person living with ALS • Ms. Reva Vaze • Graduate Student, UBC • Mr. Thusjanthan (Nathan) Kubendranathan • System Consultant, School of Computing Science • Mr. Johnny Pak • Undergraduate Student, SFU

  45. THANK YOU! Questions?

  46. Technical Presentation Engineering behind Audica™

  47. System Overview Software & Hardware

  48. System Overview

  49. System Overview • Digital System Design • Rapid prototyping • Capable of intensive numerical calculations • Widely supported development environment

  50. General Architecture • Interrupt driven design • Sampling rate of 8kHz • Suitable for conversation

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