Anti-Snoring Pillow (ASP)Anti-Snoring Pillow (ASP)

December 13, 2007December 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

OutlineBackgroundObjectivesSystem OverviewHigh Level System DesignBusiness CaseResultsWhat was learnedFuture ImprovementsConclusion

Background

Background

“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 libidopsychological and social damage

Current existing solutions

Surgeries, sleeping aids, dental appliances

Downfalls Expensive Invasive Painful Complications Unreliable

Objectives

Objectives

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

System Overview

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

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!!!

System Overview

1x Speaker (Control)2x Microphone (Reference & Error)1x DSP board1x Pillow

System Arrangement

High Level System Design

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)

Adaptation Algorithm

Filtered-U Recursive (RLMS)

Business Case

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

CostParts (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

Financing

Bank loans Investment banking

Private investorsAngel investors

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

SurgeryNone using Active Noise Cancellation!!!

Results

Snoring Sample Spectrum

Experimental Results – 1st Try

Simplified approach…

Results

Sine waves

Frequency (Hz) Attenuation (dB)

200 ~ 10 dB

300 ~ 10 dB

400 ~ 10 dB

500 ~ 23 dB

600 ~ 15 dB

Results

Budget and Timeline

Proposed Timeline

Actual Timeline

Sep-07 Oct-07 Nov-07 Dec-07

Develop Concept For Product

Place Orders

Begin Development Cycle

Functional Spec

Design Spec

Assembly of Modules

Develop Embedded Software

Debugging

Prototype Modification / Optimization

Final Report

Proposed & Actual Budget

Item Predicted Cost

Actual Cost

Difference

Texas Instrument TMS320C6713 DSK

150 $480 $330

Audio Accessories(Cables, Adaptors, etc)

150 $126 -$24

Pillow 100 $0 -$100

Miscellaneous(Book, Interface, etc)

100 $40 -$60

Total 500 $646 $146

Future Improvements

Future Improvements

Try more algorithms Automatic Gain ControlFaster convergence rate for complex audi

o processingControllable pre-amplifier and output-ampli

fier

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!

Conclusion

What was learned

Time management Mike was wrong! “Take what you think and multi

ply it by 3.” …More like by 8

Team workDSP Active Noise CancellationDocumentationIdeas to Product

Conclusion

Target more complex soundsAutomatic Gain ControlStabilitySolutions…

Multi-channel System! Omni-directional Microphones Low frequency speakers More optimization!!

References

[1] American Physical Therapy Association, “Physical Therapy Patient Satisfaction Questionnaire Research Grants”, 2007, http://www.apta.org//AM/Template.cfm?Section=Home

[2] Texas Instruments, “Design of Active Noise Control System with the TMS320 Family, June 1996, http://focus.ti.com/lit/an/spra042/spra042.pdf

[3] Speech Vision Robotics group , “Finite Impulse Response Filters”, http://svr-www.eng.cam.ac.uk/~ajr/SA95/node13.html

[4] TMS320C6713 DSK - Technical Reference. Stafford, TX: Spectrum Digital Inc., 2004. [5] A DSP/BIOS AIC23 Codec Device Driver for the TMS320DM642 EVM, Texas Instrument, Jun

e 2003, http://focus.ti.com/lit/an/spra922/spra922.pdf [6] “Sampling rate” – Wikipedia, September 2007, http://en.wikipedia.org/wiki/Sampling_rate [7] “Understanding Active Noise Cancellation”, Colin N Hansen, 2001 [8] "Headphones." Frontech - Best of Its Kind. 2006. 1 Nov. 2007 <http://www.frontechonline.com

/headphones.html>. [9] "X-540." Logitech. 2007. 1 Nov. 2007 <http://www.logitech.com/index.cfm/speakers_audio/ho

me_pc_speakers/devices/234&cl=ca,en>. [10]“Latex Pillows, Foam Pillows for Head and Neck”, AllergyBuyersClub. 2007 <http://www.allerg

ybuyersclubshopping.com/latex-head-neck-pillows.html> [11] “A Host Port Interface Board to Enhance the TMS320C6713 DSK” Morrow, M.G.; Welch, T.

B.; Wright, C.H.G. May 2006 <http://ieeexplore.ieee.org>.

Acknowledgement

Dr. Andrew Rawicz Wighton Professor for Engineering Development, School of E

ngineering 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

Questions?

Technical Presentation

Block Diagram

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] = 0.9999*A[n]+(muA*En*X[n]); //update weights of adaptive FIR

Xp[0] += (w[l]*X[l]);

Y[0] +=(A[i]*X[i])*10000; //adaptive FIR filter output

Leaky Implementation

A[n] = 0.9999*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)

Results-200Hz

Results-300Hz

Results-400Hz

Results-500Hz

Results-600Hz

Results-400&600Hz