Polygraph Machine

Neil Quinn

John Zwarich

Introduction

• A polygraph machine is an instrument that simultaneously records changes in physiological processes such as heartbeat, blood pressure, and respiration.

• Our project will collect and analyze these signals and output a certainty factor associated with each question.

Initial Objectives

Uses:Lie detection for a wide variety of users:- Criminal interrogation- Interviewing processes- Employee analysis

Other Features:-Monitoring of signals for health reasons-Healthy values compared to test data-PC based GUI for displaying signals-Adaptive algorithm for better patient compatibility

Physiological conditions to be measured:-Heart rate-Blood pressure-Respiration rate / depth-Perspiration

Initial Specifications

Technical Specs:

Heart rate accuracy: >90% Electrical noise (60hz) must be filtered Output results within 30 seconds of initial question Output accuracy exceeding 50%. (random guessing)

Estimated Cost:

Heart Rate/Pressure Transducer ~ $200 Respiration Transducer ~ $100 DSP chip and board ~ $300 Amplifiers ~ $15 Analogue Filters ~ $10

Building our project

Inputs:The initial signal conditioning circuit gave us

poor results.

Differential Op-AmpGain = 10

Low-Pass FilterGain = 47Fc = 33 Hz

Design Review

Adjustments made:

• amplifier / filter had to be redesigned several times to get a good signal

• Physiological signals simplified to heart rate and pressure

• DAQ board used to record and output signals for testing purposes

• Output of DAQ board needed an additional filter to smooth response

Pressure Transducer

Instrumentation Amplifier

High-Pass Filter

Oscilloscope

PC (Labview)

Low-Pass Filter

Amplifier

TI DSP

MatLab GUI

Pressure Transducer

• Blood Pressure Cuff to acquire input signal

• MicroSwitch 120PC Pressure Transducer to get differential voltage

Pressure Transducer Specs:- 0-5 psi range- 115mV full scale output- Sensitivity: 23mV / psi- 12v supply voltage- response time: 1ms max

Instrumentation Amplifier

More suited for our purposes because:

- provides a maximum gain of 4577

- easily adjustable gain

- eliminates common mode signals(from arm movements, etc)

- specifically recommended for pressure sensing lines

Vout = ( 1 + 2R/Rg ) (V2 – V1)

Measured Low Pass Filter Response

0

0.2

0.4

0.6

0.8

1

1.2

0 10 20 30 40 50 60

frequency (Hz)

volta

geLow-Pass Filter, Fc = 24 Hz

Low-Pass Filter

This filter design is a Sallen-Keys Butterworth filter design.

Advantages: • Faster rolloff rate because of double pole frequency response• Maximally flat pass-band for desired frequencies

High Pass Filter and Amplifier

Design Advantages:

- like LPF, also a Sallen-Keys Butterworth filter design

- HPF cutoff at 0.1hz

- final amplifier gives additional boost to desired range

Total Signal Conditioning Circuit

Instrumentation AmplifierMax Gain = 4577

Low-Pass FilterFc = 24 Hz

High Pass FilterFc = 0.1 Hz

AmplifierGain = 5

Heartbeat Capture

This output also allowed us to measure the peak-to-peak voltageand frequency of the signal from the oscilloscope.

Collect Input

Put sample in Buffer

Write Sample?

Yes

Windowing

FFT Equalization Find FrequencyW/ Highest Amplitude

Compare Frequency to Weighted Average of

Past Frequencies

Check Verification

Update Difference and Threshold

MATLAB

OutputNo

DSP Block Diagram

Frequency Response of DSP

• Input Frequency Response of DSP was non linear

• Equalized response in DSP Code by multiplying each fft bin by appropriate gain

Testing Phase

• Used Labview 6i to collect data through PCI-MIO-16E DAQ

• Waveforms stored to files and played back

• Files could be converted to spreadsheet format for analysis

• Analog output required a LPF

Writefile.vi

-Scans analog input from channel 68 (ACH0)-Writes data to waveform file

Readfile.vi

-Reads waveform file-Outputs to channel 21 (DAC0out)

Analog Output Adjustment

Low-Pass FilterFc = 5hz

Filtered to avoid zero-order hold effects

Data Samples

Region 1 – True AnswerRegion 2 – False AnswerRegion 3 – True Answer

Testing and Measurement Statistics

Polygraph Performance

33%

42%

17%

8%

TP - Properly detected lie TN - Properly detected truth

FP - Detected truth, but lie was told FN - Detected lie, but truth was told

Sensitivity - 66% / Specificity - 83%

Accomplishments

Demonstrated functionality of overall circuit in detecting lies

• Identified ~80% of lies of testing set

• Misidentified ~14% of truths as lies

• Far exceeds 50% accuracy expected from random guessing

Signal conditioning circuitry successfully amplified and filtered data to suitable range for processing

Demonstrated adaptability across subjects by adjusting to individuals’ average heart rate and physiological responses

Greatly reduced cost from initial estimation

Challenges• Initial amplifier and filters redesigned for better performance

• Amplifier instrumentation amp (common mode)• LPF a higher-order design for better dB attenuation slope

• Input circuitry overly sensitive to the subject’s arm movements • 2 Pressure sensors pins got cracked off in testing phase

• Labview 6i• Wrote a custom program for reading in waveform• Analog output needed a LPF• Poor documentation

• Op-amps clipped with subject movement due to high gain on amplifiers

• DSP AC coupling required equalization for low frequencies within the routine

Other Tests / Recommendations

• Given more time, we would have liked to collect sample data from a wider range of subjects

• It may have been better to spend more money to purchase an amplified pressure sensor to speed up construction of hardware

• More physiological inputs may improve results (respiration, electro-dermal)

• Investigate other algorithms for low frequency spectral analysis (zero crossing, peak counting)

Questions?