Presentation on theme: "Anti-Snoring Pillow (ASP) December 13, 2007 For a peaceful night of sleep."— Presentation transcript:
Anti-Snoring Pillow (ASP) December 13, 2007 For a peaceful night of sleep
LifeX Team Raymond Lee Software Researching parts Camillia Lee Documentation Software Testing Simon Wong Theory Software Debugger Stanley Yang Software Budget
Outline Background Objectives System Overview High Level System Design Business Case Results What was learned Future Improvements Conclusion
“Forty-five percent of normal adults snore at least occasionally, and 25 percent are habitual snorers.” “Thirty percent of adults over age 30 are snorers. By middle age, that number reaches 40 percent.”
Background… continued A number of effects to both the snorer and those who hear him/her daytime drowsiness, irritability, lack of focus, decrease libido psychological and social damage
Produce a affordable non-invasive solution to reduce the sound of snoring Goal: Minimize snoring noise at low frequencies by 10-15dB
LifeX’s Solution The “Anti-Snoring Pillow” -A noise suppression system integrated into a pillow
Types of Noise Control - Passive Reduces noise using specialized materials Sound isolation Sound absorption Vibration damping i.e. Ear muffs
Types of Noise Control - Active Acoustic cancellation that involves a control speaker for emitting a opposite polarity sound
Adaptive ANC Real time controller for monitoring the system’s performance System parameters are always changing Required for complex noise (i.e. speech, snoring, random noise, etc)
Adaptive ANC How? Digital signal travels faster than speed of sound! Advantages over passive acoustic control More effective at low frequencies Less bulky Able to block noise selectively A “good” system will yield better performance (up to 20+dB reduction) Adaptive!!!
Active Noise Cancellation Systems Types of ANC system Digital Filters Adaptation Algorithm
Types of ANC System Two Major types Waveform synthesis (Periodic noise – Engine noise, fan noise) Adaptive Filtering Feedback (No reference signal) Feedforward (Reference signal) Feedforward is always preferred over feedback when reference signal is available
High Level System Design
Feedforward System Adaptive broadband feedforward control with an acoustic input sensor
Digital Filters Finite Impulse Response (FIR) Inherently stable Infinite Impulse Response (IIR) Built in feedback compensation Less computational low Can model complex systems Inherently unstable
Digital Filters Three major parameters: type of system, filter weights, number of filter weights Optimization by trial and error
Adaptation Algorithm Least Mean Square (LMS) FXLMS Secondary path compensation (Offline Training)
Market Our target market would be towards couples sleeping on the same bed Our anti-snoring product is unique compared to other solutions available Benefits to our product Non-invasive Inexpensive Safe Comfortable User friendly
Cost Parts (in thousands) TI DSK 6713$20,000 Microphones x 2$7,000 Speakers x 2$60,000 Pillow$30,000 Analog parts$1,000 Parts Total$132,000 Services Packaging$1,000 Labour$9,000 Market Fees$1,000 Market agent's fees$3,000 Service Total$14,000 Total Cost$146,000 Total Revenue (1000 x $200)$200,000 Total Profit$78,000
Competition High performance passive ANC foam ear plugs Chin-up Strips Keeps mouth closed to reduce snoring Nasal strips Keep nostrils opened for better breathing Surgery None using Active Noise Cancellation!!!
Snoring Sample Spectrum
Experimental Results – 1st Try
Results Sine waves Frequency (Hz)Attenuation (dB) 200~ 10 dB 300~ 10 dB 400~ 10 dB 500~ 23 dB 600~ 15 dB
Try more algorithms Automatic Gain Control Faster convergence rate for complex audio processing Controllable pre-amplifier and output- amplifier
Future Improvements – cont. More suitable equipment Low frequency Omni-directional microphones Low frequency speakers Perform testing in a controlled environment Wideband ANC Solution: Multi-channel System!
What was learned Time management Mike was wrong! “Take what you think and multiply it by 3.” …More like by 8 Team work DSP Active Noise Cancellation Documentation Ideas to Product
Conclusion Target more complex sounds Automatic Gain Control Stability Solutions… Multi-channel System! Omni-directional Microphones Low frequency speakers More optimization!!
References  American Physical Therapy Association, “Physical Therapy Patient Satisfaction Questionnaire Research Grants”, 2007,  Texas Instruments, “Design of Active Noise Control System with the TMS320 Family, June 1996,  Speech Vision Robotics group, “Finite Impulse Response Filters”,  TMS320C6713 DSK - Technical Reference. Stafford, TX: Spectrum Digital Inc.,  A DSP/BIOS AIC23 Codec Device Driver for the TMS320DM642 EVM, Texas Instrument, June 2003,  “Sampling rate” – Wikipedia, September 2007,  “Understanding Active Noise Cancellation”, Colin N Hansen, 2001  "Headphones." Frontech - Best of Its Kind Nov  "X-540." Logitech Nov “Latex Pillows, Foam Pillows for Head and Neck”, AllergyBuyersClub  “A Host Port Interface Board to Enhance the TMS320C6713 DSK” Morrow, M.G.; Welch, T.B.; Wright, C.H.G. May 2006.
Acknowledgement 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. Lakshman One Professor, School of Engineering Science, SFU
Secondary Path Estimation E = fir_out - adaptfir_out; //error signal adaptfir_out +=(c[i]*dly_adapt[i]); //adaptive filter filter output c[i] = c[i]+(beta*E*dly_adapt[i]); //update weights of adaptive filter
FXLMS Implementation A[n] = *A[n]+(muA*En*X[n]); //update weights of adaptive FIR Xp += (w[l]*X[l]); Y +=(A[i]*X[i])*10000; //adaptive FIR filter output
Leaky Implementation A[n] = *A[n]+(muA*En*X[n]); //update weights of adaptive FIR Roundoff and quantization error can accumulate and cause coefficients to grow out of the allowed range (overflow)