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Brain Wave Alarm Clock. Engineered by George Neurauter and Humberto Lopez University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering Spring 2001. Overview. Introduction Overview of human sleep patterns and physiology Alarm Clock Operation

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brain wave alarm clock

Brain Wave Alarm Clock

Engineered by

George Neurauter and Humberto Lopez

University of Illinois at Urbana-Champaign

Department of Electrical and Computer Engineering

Spring 2001

  • Introduction
  • Overview of human sleep patterns and physiology
  • Alarm Clock Operation
  • How the clock was built
    • Hardware and software implementation
  • Verification
    • Test inputs, Pspice simulation
  • Special challenges and solutions
  • EEG Brain Wave Wavetraces
why did we pursue this project
Why did we pursue this project?
  • How we came up with this idea….a sleep deprivation story
  • Sleep deprivation in our culture is a major problem, especially in college
  • Consumer market penetration expected to be high – everyone needs sleep!
  • Sleep research led us on interesting tangents
    • Negative ion generators, biofeedback, stimulation therapy, brain waves in high frequency environments
the human sleep pattern
The Human Sleep Pattern
  • 1 ½ hour cycle between stages
  • A typical night’s sleep: 5% Stage I, 45% Stage II, 7% Stage III, 15% Stage IV, 20-25% REM
  • Stage IV most restorative to brain, but very difficult to awaken from
  • If you are sleepy right now, you are probably already in Stage I sleep!
sleep stage cycle throughout a night s sleep
Sleep Stage Cycle Throughout a Night’s Sleep

What if your current alarm clock woke you up during Stage IV sleep?

How can we take advantage of these cycles to awaken you easier and

let you have restful naps?

our clock how does it work
Our Clock - How does it work?

You need to be awake by 8 AM.

  • The clock will begin to see if you enter Stage I or II sleep 1 ½ hours before the set time. When you do, the alarm will sound. You can also nap for about an hour, which will wake you during your first REM episode, allowing you to get about 30-45 minutes of restorative delta wave sleep. Maybe you will remember your dreams….
  • Awakening times will vary. Clock works with natural body functions rather than against them.
  • Hardware
    • 4 biomedical high gain amplifiers (3 EEG and 1 EMG)
    • Harvard Apparatus Ag-AgCl solid gel electrodes
  • Software – NI LabVIEW
    • Clock and circuit logic simulation
    • Acquisition of amplified signals through NI DAQ board
eeg and emg amplifiers
EEG and EMG Amplifiers
  • 3 stage, High CMRR, differential gain
  • Signal Characteristics
    • EEG: 1-10 V , .5 – 50 Hz
    • EMG: 1-10 mV, 20 – 2000 Hz
  • Variable resistor adjusts CMRR
  • Reference electrode key to proper amplifier operation
gain and corner frequency calculation
Gain and Corner Frequency Calculation

Lower Corner Frequency

First Stage (Input Differential)

Second Stage (Differential Amp)

Upper Corner Frequency

Third Stage (Gain)

1st and 2nd stage of all instrumentation amplifiers are the same due

to similar noise rejection and CMRR characteristics.

eeg amplifier
EEG Amplifier

Total Gain = 25.4 * 7675.4 = 194955.2

Gain gives us saturated circuit, but this is good! TTL waves make finding freq. easy

emg amplifier
EMG Amplifier

Total Gain = 25.4 * 577.9 = 14667.1

Muscle tonus characterized by spiking high amplitude wave.

amplifier testing
Amplifier Testing
  • PSpice simulation
  • Sample signals using function generator
  • Differential mode and common mode gain tests
pspice simulation traces and oscilloscope traces
PSpice Simulation Traces and Oscilloscope Traces

EEG Brain Wave Waveforms acquired through Agilent VEEPro 6.0

labview clock implementation
LabVIEW Clock Implementation
  • Very simple VI, similar to alarm clock at home
  • “Almost awake” – Theta, Alpha, Beta waves
buneman frequency estimator
Buneman Frequency Estimator
  • LabVIEW VI that finds frequency of n-sized array
  • Fb: Fourier transform of signal X @ freq. b
  • b is determined by greatest value of |Fb(X)|
  • β is exact for sine waves, good estimate in all other cases
challenges we faced
Challenges We Faced
  • Brain waves are usually never perfect sine waves and have many transient waves such as K-complexes. How can we find the frequency?
  • Biomedical electrodes require sterile, electric noise-free conditions and firm placement. How can we solve these problems so everyone can and will want to use our clock?
solutions to these challenges
Solutions to These Challenges
  • Finding Brain Wave Frequencies
    • Mode function in LabView to assess data
    • Multiple sensor arrays for accurate data
    • Circuit Saturation for TTL waves
    • Alternative methods of determining sleep stages
      • Heartbeat magnitude analysis

  • Electrode Use
    • Expected to be marginal at best, especially if multiple arrays are needed
    • RF/power noise not a problem in our amplifiers
    • Tossing and turning during sleep may hinder wired hookups. RF solution may be possible, but challenging
where do we go from here
Where do we go from here?
  • Testing and more research into sleep needed for acceptable consumer product
  • Durable and reliable electrodes required
  • Determining sleep cycles for everyone not easy, many different variables