1. DEPARTMENT OF BIOMEDICAL ENGINEERING Advisor: Mitch Tyler Client: Dr. Christopher Green, MD University of Wisconsin-Madison Anna Karas Meghan Olson Blake Hondl Zachary Cohen

2. PTT is not calculated with the current Sleep Apnea Equipment (Flaga system) Design a solution which interfaces with the current system and is capable of detecting and measuring changes in pulse transit time which occur due to vasoconstriction during a micro arousal Problem Statement

3. Must interface with existing Sleep Apnea Study Equipment –Cannot void current system’s warranty Accurately detect the ECG and Pulse Oximetry peaks –Must reject signals due to noise or motion artifact Calculate PTT Correlate PTT with other sleep study measurements Design Constraints

4. Affects 12 million Americans Obstructive Sleep Apnea –Is caused by obstruction of the trachea (windpipe) From tongue, tonsils, uvula, fatty tissue in the throat, and/or relaxed muscles –Individual can stop breathing for 10-30 sec. –Low blood oxygen level activates “flight or fight” response releases adrenaline causes vasoconstriction –Individual brought out of REM sleep –Can occur every 1-4 minutes (~400 times a night) Results in health problems and poor sleep Sleep Apnea: Biological Aspect

5. Time will decrease with a micro arousal Measure from peak Signal from ECG machine Pulse Transit Time Theory Obstruction of breathing causes release of endorphins monitored by cerebral cortex The blood vessels constrict causing higher blood pressure (blood flows faster) The amount of time from heart pumping blood for the pressure wave to reach an extremity decreases PTT is correlated with micro arousals Signal from Pulse Oximeter t

6. PTT Correlates to Micro Arousals Blood pressure rises imply arousals (through PTT) are as good as EEG micro-arousals at predicting subjective sleepiness PTT detects subcortical/autonomic arousals, currently undetected by EEG monitoring ΔPTT is a sensitive indicator of inspiratory effort variance due to obstructions PTT detects events of a respiratory obstruction, but cannot differentiate types of events » v = K*√{V* ΔP/ΔV} « v=Pulse Wave Velocity V= Initial Vessel Volume K= Constant ΔP= Pressure Delta ΔV= Vessel Volume Delta

7. FLAGA / Somnologica System Incorporates a variety of sleep study signals: EOG, EEG, ECG, Pulse Oximeter, Respiratory CO2, Noise/Vibration (snoring), Visual monitoring – Signals can be sampled at 2-2000 Hz Somnologica program process signals and displays information in GUI format Data can be extracted in European Data Format (EDF)

8. Design 1: Spaced Transducer Technique Original method to test PTT Pressure sensors placed on skin consecutively on an artery Sensors measure the pulse moving in the artery below Sensors placed known distance apart (d) Analog to Digital conversion of signal Calculate the time between when the first sensor feels the pulse and the second Real time PTT calculation Store information for later reference Pressure Sensor d d

9. Design 1: Spaced Transducer Technique Advantages –Simple design –Low cost –Independent of Flaga system Disadvantages –Noisy signals –Difficult to use with sleeping patients –Inaccurate compared with other techniques

10. Design 2: Automated Ambulatory Blood Pressure Blood pressure can be measured and correlated with PTT Measure blood pressure with piezoelectric microphones Measures systolic and diastolic blood pressure Portable, lightweight, can run on batteries Used from 24-48 hr. periods – measurements taken at set intervals (~every 5-60 min.) Tiba Medical – ~$1800 for a unit – $225/month to rent – Connects to PC – 512 MB storage capability

11. Advantages –Lightweight –Portable –Interface with computer for post analysis –Past studies show it does not effect sleep of child –Another way to measure micro arousals (correlated to blood pressure increase) Disadvantages –Costly –Dependent on cuff inflation –Data can only be taken at intervals of 5- 60 min. –Not a continuous measurement –Micro arousals may not be detected Design 2: Automated Ambulatory Blood Pressure

12. Design 3: PTT Software Solution Interface with existing Flaga System Stored data interfaces with Matlab Programming –Signal analysis Rejection of motion artifact Detection of QRS and Pulse Oximeter wave –PTT calculation Correlation of PTT with collected data from Flaga –Via Epic Number

13. Design 3: PTT Software Solution Advantages –Feasibile –Cost –Meets client requirements –Interfaces with existing system No additional signal measurements required –Provides accurate PTT Disadvantages –Not real time –Not portable

14. Design Matrix CriteriaTransducerBlood PressureSoftware Cost231 Feasibility (time restraints) 211 Satisfies Client Requirements 332 Ease of Use221 Interfaces with Flaga system 331 Average Score2.4 1.2 Good Best Rated 1-3: 1=Best, 3=Worst

15. Potential Problems/Future Work Obtaining real-time signal from FLAGA system to output PTT in real-time Motion artifacts are introduced into ECG, influencing PTT –Need processing algorithms to account for this Convert EDF to text file Using Matlab develop algorithms to detect wave peaks Create rejection algorithm for motion artifact Calculate PTT & display

16. Appendix / References http://www.biopac.com/AppNotes/app117PTT/ptt.html http://www.tibamedical.com/ABPM.htm http://www.medicinenet.com/sleep_apnea/page5.htm http://www.disabilitysecrets.com/medicine- medication-prescription-drugs-sleep-apnea.html http://www.aafp.org/afp/20030601/2343.html