LABORATORY EXPERIMENT REPORT

BME:2200

Systems, Instrumentation and Data Acquisition Laboratory

Contribution Sheet

Final Laboratory Report

Date: 5/11/16

Printed name: Patrick Crowley

Percent contribution to report: 65%

Electronic Signature: Patrick Joseph Crowley

Printed name: Greg Cuvillier

Percent contribution to report: 35%

Electronic Signature: Greg M. Cuvillier

I. INTRODUCTION

Electromyography (EMG) is used in the medical field due to its practical applications. An EMG can measure the difference in output voltage between two electrodes placed directly on the skin superficial to the muscle being tested. [4] The action potentials are examined to determine any muscular abnormalities, which can be used for monitoring muscle activity in paralyzed or disabled patients, as well as advanced integration into a motion detecting prosthetic. The device created for this experiment was used to measure the variations in output comparing a muscle in flexion and a relaxed muscle. LabVIEW was implemented as a data acquisition platform and as an indicator to the relaxation and flexion of the muscle.

II. METHODOLOGY

In order to obtain measureable data, the physiological signal from the two electrodes were fed into a multi-component circuit. Electrode placement was modeled from the research of Samuel Svensäter, who studied Implementation and Evaluation of Smart Training Gear Measuring and Visualizing Muscle Data in Real Time. Electrode 1 was placed in the

middle of the bicep while electrode 2 was placed on the bicep but closer to the forearm. This allows for a larger

difference in muscle activity to be recorded. A third electrode was placed on the elbow as a ground to establish a baseline potential of the body. The electrodes were then attached to the inputs of the instrumentation amplifier.

The first component consisted of 3 UA741CP operational amplifiers connected through a network of resistors making an instrumentation amplifier. The value of an instrumentation amplifier incorporates the ease of which the gain can be adjusted and its multi-input feature into a singular output signal. [3] Based off of Figure 2, the values of R and Rgain are 100kΩ and 20kΩ, respectively.

The resistor and circuit values used were found using a circuit design software to aid in

time management of the project.[5]

Electromyography Experiment Final ReportP. J. Crowley, G. M. Cuvillier

Department of Biomedical Engineering, University of Iowa, Iowa City, IA

Figure 2A: Instrumentation Amplifier schematic used to converge and amplify the input signals.

Figure 2B: Instrumentation amplifier used in the circuit.

Figure 1: Display of optimized electrode placement to obtain maximized signal difference

Utilizing these resistor values, the gain of the instrumentation amplifier was calculated to be 11 by using Equation 1.

Gain=1+ 2RRgain

Equation1

The instrumentation amplifier’s output signal was fed into component two of the circuit design. Component two entailed a two-stage 3rd order Butterworth filter. A Butterworth filter was used to attenuate any frequencies above the pre-determined cutoff frequency. Using the research of David DeLion of the UNLV Biomechanics Lab, the initial cutoff frequency was set to 500Hz[2]. Manipulating Equation 2, the necessary resistor and capacitor values were calculated.

ωc=1

2πRCEquation 2

After numerous rounds of testing, the output signal reading on a Teletronix TDS 2014B Oscilloscope probe was showing too much noise. The cutoff frequency was lowered to 106Hz. This attenuated a portion of signals not produced directly by the flexion of the muscle

The gain of the

Butterworth filter was computed using Equation 3.

Gain=1+R1

REquation3

The corresponding gains of stage 1 and 2 are 20.6 and 2, respectively. Using the gain from the instrumentation amplifier, the total gain of the circuit is 453.2, computed by multiplying the gains together.

From the output of the circuit, the signal was inputted into

LabVIEW. LabVIEW first read in the signal carried over from the circuit board with the DAQ assistant. The signal was then filtered to only read values below 150 Hz using a digital low pass filter. The signal was then presented in a graphical representation. A virtual instrument measured the amplitude of the signal of the peak to peak distances and loops the program through a Boolean expression. This Boolean expression reads true if the corresponding peak to peak voltages exceed .6V, indicating a flexed muscle, and reads false if peak to peak voltages are less, indicating a relaxed muscle. When the muscle was flexed, LabVIEW would flash a green light under flexion, and a red light under relaxation, the neutral screen is seen in Figure 4.

The block diagram used as a basic guideline of the project can be seen in Appendix A. While the block diagram of the LabVIEW layout can be seen in

Appendix B.

Figure 3A: Stage 1 of Butterworth Filter. Gain of first stage is 20.6

Figure 3B: Stage 2 of Butterworth Filter. Gain of second stage is 2.

Figure 4: LabVIEW reading peak to peak of signal over/under 0.6V threshold to show the bicep is flexing/relaxing.

III. RESULTS

To ensure the functionality of the circuit, the Teletronix AFG2021 Arbitrary Function Generator inputted signals that best represented the anticipated data. The Teletronix TDS 2014B Oscilloscope was used to read the output signals of the circuit establishing the gain of the circuit was accurate.

IV.

DISCUSSION

Initially, the goal of the project was to build an

Electrooculogram (EOG), which measures corneal-

retinal potential. This is the small electrical potential difference between the cornea and the retina. [1]

Significant obstacles were met during the testing phase of the EOG when trying to measure any voltage difference of stationary versus eyes moving horizontally. No evidence was found as the cause of the inability to measure a signal. A potential source of error could be that of the sensitivity of the electrodes. With the muscles surrounding the eye producing low physiological signals, the sensitivity of the electrodes provided were not strong enough to detect weak output signals. In the case of a stronger muscle (the bicep) being tested, the sensitivity of the electrodes was able to be disregarded. The measurement of the bicep changed the project into an EMG apparatus instead of an EOG. This change required additional alterations to the circuit in order to adjust for the measurement of the different signal. These changes altered the gain of both the instrumentation amplifier, and the third order Butterworth Filter. Additionally, the cutoff frequency was lowered to produce a more concentrated signal for measurement. Furthermore, the change of processes restricted the allocated time to expand the data acquisition readings.

In Figure 5, the voltage output was recorded to be 3.52V. A function generator was used to produce this signal, the exact gain could be calculated. A 24mV input into a voltage divider, delivered 8mV into the circuit. Comparing the output to the input, the gain was calculated to be 440. This is only slightly less than the theoretical voltage expected. The variance can be explained by numerous factors such as the tolerance in the impedance of the resistors or the wear on the operational amplifiers from years of usage.

Figure 6 displays a sample of the data collected to portray the output voltage differences of the bicep in flexion and relaxation. Figures 7 and 8 portray the LabVIEW graphing and signaling of the bicep in flexion and relaxation, respectively.

Figure 6: Comparing voltage outputs during period of relaxation (bottom) and flexion (top).

Figure 7: LabVIEW interpreting signal and displaying light due to muscle in flexion

Figure 8: LabVIEW displaying bicep in relaxation while signaling relaxation light.

Figure 5: Results of testing circuit and proper gain.

The sampling frequency implemented in LabVIEW was 1000Hz to collect the data necessary for interpretation while also allowing the cutoff frequency to be small enough to circumvent unnecessary signals. Since the cutoff frequency was significantly lower, the sampling frequency should have been between 200-500Hz. This could account for the additional data collected, some of which does not correlate with the physiological signals wanted for interpolation. Additionally, specialized electrodes to acquire EMG signals could have been used, which would reduce noise seen in Figure 7.

V. CONCLUSION

The goal of this project was to construct a device capable of measuring and interpreting a physiological signal. The EMG constructed was used to acquire the voltage output, specifically of the bicep. Implementation of the signal was inputted into LabVIEW to analyze the functionality of the assembled EMG.

Future experimentations which allow for additional time and another individual to aid in the construction of LabVIEW, allow extended data interpretation to note the frequencies of the incoming signals. A lack of personnel hindered the amount of time spent on LabVIEW, as the principal investigator spent copious amounts of time focusing on the proper function of the circuit instead of LabVIEW.

VI. ACKNOWLEDGMENT

Dr. Osama Saba of the University of Iowa, and Ryan McLaughlin are two individuals whom deserve significant recognition for their efforts towards assisting this project through their time, patience, and advice.

VII. REFERENCES

[1] BioPac Systems. (2014, December 24). EOG vs. EMG amplifier | BIOPAC. Retrieved May 8, 2016, from http://www.biopac.com/knowledge-base/eog-vs-emg-amplifier/

[2] DeLion, D. (2016, April 30). Processing EMG. Lecture presented in UNLV Biomechanics Lab.

[3] EETech Media. (n.d.). The Instrumentation Amplifier. Retrieved May 8, 2016, from http://www.allaboutcircuits.com/textbook/semiconductors/chpt-8/the-instrumentation-amplifier/

[4] The John Hopkins University. (n.d.). Electromyography (EMG). Retrieved May 08, 2016, from http://www.hopkinsmedicine.org/healthlibrary/test_procedures/neurological/electromyography_92,p07656/.

[5] Filter Wizard | Analog Devices. (n.d.). Retrieved May 11, 2016, from http://www.analog.com/designtools/en/filterwizard/

Appendix A

Physiological Signals from

bicepElectrodes

Analog Circuit(Instrumentation Amplifier and 3rd

order Butterworth Filter

LabVIEW

Appendix B

Figure 9: Block diagram schematic of LabVIEW layout.

Graphical Representation

Light Representing

Flexion or Relaxation