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Goal: To understand bioelectrical signals To understand ECG acquisition To understand time domain analysis of the ECG To understand frequency domain analysis of the ECG To become acquainted with data storage and recovery Materials: Electrodes PC ADC LabVIEW Isolated differential amplifiers Oscilloscope Connectors Volunteer Student Labview Build a LabVIEW VI to acquire the ECG signal. The program should include some signal processing. The bandpass of the signal should be 0.05 to 100 Hz. Also, you want to remove 60 Hz noise from the signal (bandstop). You will also need an FFT for part 3. You can perform the signal processing in the same VI. (Alternatively, you could acquire the signal and process it later using LabVIEW, Excel or Matlab.) Filtering can occur either before acquisition (in hardware) or after (in software). 1. Measurement of the ECG waveform 1.1 Use the electrodes supplied in the lab to measure the standard Lead I ECG (left arm +, right arm -). 1.2Amplify the signal using the differential isolated amplifiers (SCXI or Grass amplifier). 1.3 Use the computer to record the ECG waveform over three heart beats. Store the data. 1.4 Place the electrodes to measure standard Lead II ECG (keep all the other connections). 1.5 Repeat 1.3. Be sure to store the data under a different name. 1.6 Place electrodes to measure standard Lead III ECG 1.7 Repeat 1.3. Be sure to store the data under a different name. 1.8 For your best Lead, collect 10 beats for later signal averaging (Section 5) 2. Time Analysis 2.1 For data from Lead I do: 2.1.1 Measure the duration of each portion of the wave. 2.1.2 Measure the beat frequency 2.1.3 Create a file containing one beat (P-QRS-T complex) 2.1.4 Import the data into a spreadsheet 2.1.5 Consider the PQ segment as baseline and measure the maximum amplitude and peak to peak values for each portion of the wave. 2.2 Repeat steps 2.1.3 to 2.1.6 for Lead II 2.3 Repeat steps 2.1.3. to 2.1.6. for Lead III 2.4 Discuss the values obtained. Compare to nominal values. 3. Find the electrical axis of the heart 3.1 Calculate the area under the QRS complex for Leads I and II. 3.2 The ‘mean QRS vector’ lies in the frontal plane of the chest. Its component in the Lead I direction equals the area under the QRS complex for that lead. The same is true for the other leads. Calculate the orientation of the mean QRS vector using your data from part 3.1 3.3 The mean QRS vector roughly corresponds to the anatomical longitudinal axis of the heart. Is the orientation you found in part 3.2 reasonable? Why don’t you need to use the Lead III data? 4. Signal Averaging Here we will examine two averaging techniques for computing an average ECG wave: mean and median. In order to average, the signals have to be aligned. Use a fiducial point in the heart beat, such as the R wave in order to divide and align the signals. 4.1 For the 10 beat data you collected in Section 1.8, divide it into ten beats, each starting at the R wave. Obtain the MEAN composite signal as: N Cmean(n) = (1/N) * xk (n) k=1 for 0 =< n <= L-1, where xk, k=1,...,N are noisy epochs of length L 4.2 Obtain the MEDIAN composite signal as: Cmedian(n) = median {x1 (n), x2 (n),...xn(n)} for 0 <= n <= L-1, where xk, k=1,...,N are noisy epochs of length L. 4.3 Compare the results. 4.4 Make an artifact (glitch) in one of the signals (or use a noisy signal that you acquired) and repeat 5.1 and 5.2. Compare the effect of the artifact on the results. 5. Illustrate the use of the ECG as a diagnostic tool. How does the electrical activity of the heart reflect its mechanical properties?