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EOG for REM Sleep Detection. Robert Slavicek & Andrew Wassef. Description of Problem. Over 12 million people suffer from sleep apnea Americans average 6.22 hours of sleep a night, well below the recommended 7 to 8 hours

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eog for rem sleep detection

EOG for REM Sleep Detection

Robert Slavicek & Andrew Wassef

description of problem
Description of Problem
  • Over 12 million people suffer from sleep apnea
  • Americans average 6.22 hours of sleep a night, well below the recommended 7 to 8 hours
  • Currently sleep studies of patients must be done outside of the home and are expensive
objectives
Objectives
  • Wanted to create a cheap, portable sleep observation system
  • Taking input signals from temperature and eye movement
  • Be able to identify when patient is in REM sleep
original design
Original Design

Test Subject

(Electrodes)

Signal Filtering

and Amplification

Signal Filtering

and Amplification

Test Subject

(Thermistor)

Summer

Circuit

Data Acquisition

&

Storage

C Program

&

Display

original design5
Original Design
  • Obtain clear, useable signal
  • Have system be functional for multiple patients
  • Need to insure patient safety
  • Need to sample at a frequency high enough so that no relevant eye data is lost
biosignal corneal retinal potential
Biosignal: Corneal Retinal Potential
  • Natural mV dipole between the cornea and the retina of the eye
  • Front of eye is positively charged, while back is negatively charged
  • Measured by placing electrodes directly lateral to each eye on the canthi and a reference electrode to the forehead
eye motion
Eye Motion

If you look right: - right electrode reads positive voltage

- left electrode reads negative voltage

- circuit takes difference of electrodes

- net voltage is positive (pos-neg)

If you look left: - exact opposite of looking right

- net voltage is negative (neg-pos)

slide12

Buffer Circuit: isolates the output from the signal source

Differential Amplifier: Rejects signals common to both electrodes

4th Order Low Pass Filter: attenuates signals from frequencies greater than 35Hz

slide14

Variable Amplifier: allows operator to control the gain for each subject

Summer Circuit: allows operator to block DC offset

Inverting Amplifier: increases signal to better differentiate eye movement

wein bridge oscillator
Wein Bridge Oscillator

Electronic oscillator used to generate a sine wave so that the temperature sensor is at a different frequency spectrum

temperature sensor
Temperature Sensor

Implementing the temperature signal with the eye signal

data acquisition18
Data Acquisition
  • Used a 16-bit sound card to acquire data
  • Data was collected through a program Audacity
  • Audacity collected the data into a .wav file at 8000KHz sampling
  • Files of a night’s sleep were about 230 MBs of storage.
data acquisition19
Data Acquisition
  • From Audacity, we import the .wav file into Matlab
  • Matlab’s “wavread()” command sorts the .wav data into a M by 2 Matrix
data acquisition20
Data Acquisition
  • When we sort this data into a matrix, we can perform the FFT (Fast Fourier Transform)
  • We isolate the frequency range of the eye signal from the temperature signal
data acquisition21
Data Acquisition
  • Using Matlab’s “sptool” command, we could isolate each signal for analysis
  • Sptool contains FIR bandpass and LS low pass filters that can filter out either signal
data acquisition22
Data Acquisition
  • Used LS low pass filter, order of 80 cutoff at 170 Hz
data acquisition23
Data Acquisition
  • After filtering the original signal we can send the time domain signal back to matlab in a data array
  • The data array can be exported as a .txt file to be further analyzed.

Filtered

c program analysis of data
C Program Analysis of Data

Output file from Matlab

c program analysis of data28
C Program Analysis of Data

remsun1> eog

Enter input file name: eogin.txt

Enter sampling frequency (Hz): 20

Would you like to average the data (y/n)?: n

The output file 'out.txt' was written successfully!

Would you like to view it (y/n)?: y

Left at 0.4500 s due to -0.2017 V

Right at 1.9500 s due to 0.2179 V

Left at 3.7500 s due to -0.2174 V

Right at 5.5000 s due to 0.2285 V

Left at 7.2500 s due to -0.2547 V

Right at 9.0000 s due to 0.2144 V

Left at 10.7000 s due to -0.2121 V

Right at 12.5000 s due to 0.2120 V

Left at 14.3000 s due to -0.2259 V

Right at 16.0000 s due to 0.2297 V

Left at 18.0500 s due to -0.2486 V

Right at 18.4500 s due to 0.2181 V

Left at 18.8500 s due to -0.2195 V

Right at 19.3500 s due to 0.2295 V

Left at 19.9000 s due to -0.2308 V

final output file
Final Output File

Left at 0.4500 s due to -0.2017 V

Right at 1.9500 s due to 0.2179 V

Left at 3.7500 s due to -0.2174 V

Right at 5.5000 s due to 0.2285 V

Left at 7.2500 s due to -0.2547 V

Right at 9.0000 s due to 0.2144 V

Left at 10.7000 s due to -0.2121 V

Right at 12.5000 s due to 0.2120 V

Left at 14.3000 s due to -0.2259 V

Right at 16.0000 s due to 0.2297 V

Left at 18.0500 s due to -0.2486 V

Right at 18.4500 s due to 0.2181 V

Left at 18.8500 s due to -0.2195 V

Right at 19.3500 s due to 0.2295 V

Left at 19.9000 s due to -0.2308 V

functional tests
Functional Tests

Left at 0.0500 s due to -0.2066 V

Right at 0.5500 s due to 0.4051 V

Left at 1.2000 s due to -0.2246 V

Right at 1.9500 s due to 0.4172 V

functional tests32
Functional Tests

Left at 0.0500 s due to -0.4279 V

Right at 0.1500 s due to 0.1525 V

Left at 0.4000 s due to -0.3228 V

Right at 0.6500 s due to 0.1831 V

Left at 0.8500 s due to -0.3472 V

Right at 1.0500 s due to 0.1239 V

Left at 1.3500 s due to -0.3410 V

Right at 1.5500 s due to 0.1944 V

Left at 1.8500 s due to -0.3426 V

Right at 2.1000 s due to 0.2452 V

Left at 2.3000 s due to -0.3210 V

Right at 2.5500 s due to 0.1284 V

Left at 2.8000 s due to -0.3957 V

Left at 3.2500 s due to -0.3876 V

Right at 3.5500 s due to 0.2024 V

Left at 3.7500 s due to -0.3952 V

Right at 4.0500 s due to 0.2044 V

Left at 4.2500 s due to -0.4400 V

Left at 4.7000 s due to -0.3433 V

Right at 4.9500 s due to 0.1645 V

Left at 5.1500 s due to -0.3439 V

functional testing34
Functional Testing

remsun1> eog

Enter input file name: eogin.txt

Enter sampling frequency (Hz): 20

Would you like to average the data (y/n)?: n

The output file 'out.txt' was written successfully!

Would you like to view it (y/n)?: y

Left at 1.5500 s due to -0.2017 V

Right at 1.9500 s due to 0.2179 V

Left at 2.4500 s due to -0.2174 V

Right at 2.8000 s due to 0.2285 V

Left at 3.2500 s due to -0.2547 V

Right at 3.8000 s due to 0.2144 V

Left at 4.4500 s due to -0.2121 V

Right at 5.1000 s due to 0.2120 V

Right at 6.0500 s due to 0.2297 V

Left at 7.9500 s due to -0.2486 V

Right at 8.4500 s due to 0.2181 V

Left at 8.8500 s due to -0.2195 V

Right at 9.3500 s due to 0.2295 V

Left at 9.9000 s due to -0.2308 V

Right at 11.3500 s due to 0.2295 V

Right at 13.0000 s due to 0.2235 V

Right at 18.4500 s due to 0.2102 V

successes
Successes
  • Effectively captured lateral eye motion and temperature changes in human subjects in a portable device
  • Measured and stored changes in these signals over an entire night of sleep
  • Ensured patient safety
  • Display in a user friendly fashion when a subject displays mannerisms of REM sleep
challenges
Challenges
  • Actually recovering a signal from the lateral eye motion
  • Offset of electrodes pushed signal out of viewable range and signals were lost due to saturation
  • Electrodes slipped off during sleep / uneasy sleep
  • Digitally sample the two signals in one sound card
  • Temperature not responsive enough to accurately gauge when REM sleep occurs
recommendations
Recommendations
  • Could add more functionality by adding EEG, EMG, HR, or BP monitors to help better determine the exact time of REM sleep
recommendations38
Recommendations
  • A feedback loop in the circuit to normalize the retinal-corneal dipole signal from all users rather than having to manually adjust the potentiometer in the circuit and the threshold values in the program
  • A more accurate and sensitive temperature sensor