Transcript Anti-Snoring Pillow (ASP)

Anti-Snoring Pillow (ASP)
For a peaceful night of sleep
December 13, 2007
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
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 libido
psychological 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 board
1x 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
Cost
Parts (in thousands)
TI DSK 6713
Microphones x 2
$20,000
$7,000
Speakers x 2
$60,000
Pillow
$30,000
Analog parts
Parts Total
$1,000
$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 investors
Angel 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
Surgery
None 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
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
Oct-07
Nov-07
Dec-07
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
500
$646
$146
Total
Future Improvements
Future Improvements
Try more algorithms
Automatic Gain Control
Faster convergence rate for complex
audio processing
Controllable pre-amplifier and outputamplifier
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
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
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[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://svrwww.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, June
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/home_pc_speakers/devices/234&cl=ca,en>.
[10]“Latex Pillows, Foam Pillows for Head and Neck”, AllergyBuyersClub. 2007
<http://www.allergybuyersclubshopping.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
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
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
Roundoff and quantization error can accumulate and
cause coefficients to grow out of the allowed range
(overflow)
A[n] = 0.9999*A[n]+(muA*En*X[n]); //update
weights of adaptive FIR
Results-200Hz
Results-300Hz
Results-400Hz
Results-500Hz
Results-600Hz
Results-400&600Hz