Posted: November 18th, 2022

Filtering Simulated Heart Beat to evaluate and understand

Filtering Simulated Heart Beat to evaluate and understand the ECG’s PQRST Waves

Abstract
The lab report gives an analysis of the ECG signals using the LabView. The study of ECG waves includes signal filtering, and simulation of signals from various impedance levels depending on the circuits used. The LabView was used to show the associated waves from various inputs. The proper utilization of ECG Application helps in both simulation and real time processing and analysis at great accuracy. The aim of the experiment is to evaluate and understand the ECG’s PQRST Waves using filtering simulated heartbeat.
Introduction
The first lab (lab 8) shows the various amplifiers abilities in medical measurements to perform mathematical operations including integrator, differentiator, and summer (which combine integration, differentiation, and summation respectively. Basically, it focused on determining the signal behaviors or the property of the AC waves. The op-amp integration means that an output voltage is proportionate to the integral of the input voltage and these integrals determine areas under curves. Differentiator, on the other hand is a function that gives a slope. For instance, for a time-varying alternative current voltage signal, the derivative relates to the slope. Lastly, for summer, the op-amps carry out addition operations that add two signals. Such summing op-amps show variations of the inverting amp with multiple inputs. The gain in this case is given by the equation;
V_out=-(Rf/R1*V1+Rf/R2*V2)
Multiple signals including those with different frequencies and the one requiring different levels of gains can be added together using the above equation.
The second lab (lab 9) used the Electrocardiogram (ECG) to analyze the associated waves of the heart’s electrical pulses. ECG is a graphical interpretation of the results of diagnostic tool that measures records electrical impulses of the heart over a period of time (Sörnmo, & Laguna, 2006). The results are helpful to identify the heart conditions whether minor or life-threatening. The graph produced by the ECG is characterized by five particular waves or peaks known by letters PQRST. The figure 1 below shows an example showing the segments of ECG. The P is attributed to atrial contraction.
The QRS peaks are defined as the ventricles contract, and T is characterized by the relaxation of the ventricles. The data are commonly collected from hospitals and allows the medical practitioners to assess the health progress of a patient at any given time. A number of analytic approaches like the Fast Fourier Transformation can help in the detection of cardiac diseases (Sörnmo, & Laguna, 2006). The electrical pulses/activities in the cardiac are measured in mV, and to be evaluated, the signals need amplification and the noise due to surrounding environment and instrument leads must be filtered out.

Figure 1: Explanation of ECG by Segments PQRST
The lab seeks to show how the ECG can be utilized in the biomedical instrumentation to assess the electrical nature of various conditions associated with signals/waves. The apparatus used were used to filter out a simulated heartbeat to better understand the PQRST wave.
Materials and Methods
Below is a list of the materials used in both the experiment.
ECG LabView-based simulator
Circuitboard
Biomedical workbench
In lab 8 the first part involved building an integrator. The integrator circuit was connected as per the figure below and the power supplied using the +15V and -15V DC power supply (fixed). The supply was set to 0.2V p-p at 1000 Hz frequency. The wave form was visualized and the output captured with input and output waveforms for square, triangle, and sine waves inputs.

Figure 2: op-amp integrator circuit

The second part involved building a differentiator. The first circuit was dismantled to build a differentiator circuit. The supply was set to 0.2V p-p at 1000 Hz frequency. The wave form was visualized and the output captured with input and output waveforms for square, triangle, and sign waves inputs.

Figure 3: Op-amp circuit for differentiator
The circuit was then connected to calculate the resistor for gain of five in V1 and two in V2. The V2 analogue output was wired to 0 AO 0 to the red bus line in the second column and the blue bus connected to ground. Keeping the supply of V1 using FGEN, the arbitrary waveform generator and the file 1V sine1000 were open. The red line on the second bus line column was connected to AI 4+ and AI 4- ground. This was important to visualize the waveform to be used for V2. The voltage amplitude was chosen for input V1 in an unclipped output. The wave form was then visualized using 1 kHz triangle, sine and square inputs.

Figure 4: The Summer Amplifier Circuit
The first part was a portion of the lab built on op-amp arrangement that filtered an ECG signals produced by the Biomedical Workshop in LabView. The Biomedical Workbench application was opened and the signal settings selected from the Biosignal Generator to show how the fuzzy ECG generated looks like. The output upper limit was set to 2.3 mV, lower limit set to -0.7mV, noise amplitude to 0.1mV, and power noise to 60H and 0.24mV. The inverted circuit was then built with the input voltage wired to AO-O (source of ECG signal). The screenshots of the filtered signals were then captured.

Figure 5: Circuit Arrangements for Part 1
In the second part of the experiment, the Op-amp in biomedical instrumentation was used for buffering of impedance. The magnetic buzzer utilized an input square wave at 50% cycle and produces a sound. In this case, the resistance of the magnetic buzzer was measured and recorded. The voltage divider circuit was built to supply a square wave with 1000 Hz and 1V. The voltage drop across R1 was determined using the oscilloscope and the buzzer connected in parallel to R1. The voltage drop across R1 was again measured to determine whether the buzzer went off. Finally, a unity gain/follower non-inverting op-amp was inserted and the observation recorded as well as the behavior of the amplitude of voltage wave in the buzzer after the follower. The equation used to determine the gain was;
V_out=-(Rf/R1*V1+Rf/R2*V2)

Figure 6: Voltage Divider Circuit

Figure 7: Voltage Divider with BZZR

Figure 8: Voltage Divider with follower and BZZR
Results
Lab 8 Results
Part 1:

Figure 9: The output sine wave in an integral circuit
Part 2:

Figure 10: Sign wave in differentiator circuit

Figure 11: Triangle wave

Figure 12: Square Wave
Part 3:

Figure 13: Input

Figure 14: Output
Lab 9 Results

Figure 15: Filtered ECG Signals

Figure 16: A Square Wave when Using Voltage Divider Circuit

Figure 17: A Square Wave with Voltage Divider with BZZR Circuit

Figure 18: A Square Wave with follower with BZZR Circuit
Figure six shows how the op-amp configuration acts as a filter in an ECG Biomedical Workbench generated Signals. In part two, the measured resistance at the buzzer was 20 Ohms. The behavior of the square signals in the figures 16, 17, and 18 change depending on the function generator used. The square signals produced with voltage divider circuit is different from the one produced with voltage divider with BZZR, which also differs from when the follower and BZZR are used.
Discussion and conclusion
The objective of this lab was to show how the ECG can be utilized in the biomedical instrumentation to assess the electrical nature of various conditions associated with signals/waves. Op-amps are useful in providing amplification and gains of signals as well as their analyses as shown in part 1. In part two, op-amp is also useful in impedance buffering of biomedical instrumentation. Circuits have elements that can place impedance load to prevent operations as intended. An Ideal op-amp has very high input impedance but very low output resistance. Therefore, they can serve as buffers between circuit parts. The amount of gain provided by the op-amp is calculated below.
V_out=-(Rf/R1*V1+Rf/R2*V2)=-(20/22*1 +20/22*1)=-1.82
In this set up, the op-amp setup is differential. The op-amp helps to monitor the frequency of the current flowing through the circuit. The ECG filtered the simulated heartbeat and noise so that the PQRST waves can be understood better. Signals analysis toolkits like ECG applications are significant to resolve problems on signals processing (Sörnmo, & Laguna, 2006). This application has demonstrated its crucial use in de-noising, ECG signals extraction, and analysis useful in the ECG processing bio-medication and research.
In conclusion, the labs enabled to show the different kinds of waves under mathematics operators on integrator, differentiator, and summer Op-amp circuits. Various output waves include sine waves, square waves and triangle waves. The input AC voltage should be moderate to ensure an ideal integrator circuit, and avoid chip damages. The lab was also able to simulate heartbeat and noise in ECG so that the PQRST waves can be understood better. It was also able to show the property of op-amps in impedance buffering. The different measurements were displayed using the LabView ECG Application. Anything unusual in the ECG signals waves helps in identifying any defect in the simulator.

Reference
Sörnmo, L., & Laguna, P. (2006). Electrocardiogram (ECG) signal processing. Wiley encyclopedia of biomedical engineering.

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