Free Essay

Testing Heart Rate Detector

In: Computers and Technology

Submitted By breizh
Words 1975
Pages 8
Experimentation
Analog Circuit
The following figures are screenshots of the oscilloscope after each stage.
Voltage Follower

Grounded

Not Grounded
Differentiator

Not Grounded
Grounded

Low pass Filter, f0 = 150Hz
Grounded

Not Grounded
High pass Filter, f0 = 0.5Hz

Grounded

Not Grounded

N

Muscles repeatedly flexing (no high pass filter)

Muscles repeatedly flexing (after high pass filter)

60Hz Notch Filter

Grounded

Not Grounded

Final ECG Output (after amplifier)

Grounded

Not Grounded

The following figure was captured using LabVIEW.

Top Waveform (White) = Output
Middle Waveform (Red) = After differential amplifier, before any filtering
Last Waveform (Green) = Buzzer Output, R wave detected This output demonstrates that our filters are working well enough to detect Rwaves. Looking at the 4th R-wave in the red waveform, which is before any filtering, we see that the EMG noise is at the same magnitude as the R-wave. However, our buzzer still detected an R-wave. The noise was reduced in such that the R-wave is not clearly above the noise. We are also able to see 60Hz noise filtered out in the output.

Digital Circuit
Timer Interrupt at 250Hz (Sampling Rate)
Verified by checking on the oscilloscope to see a spike every 4ms (250Hz)

Analog-to-Digital Converter
We inputted the ECG waveform to the microcontroller ADC and graphed the output values. The graph resembles an ECG waveform. This means the ADC was able to digitilize the analog signal. By creating a conversation chart, we could were able to confirm the ADC representation of the signal corresponded with the original ECG signal.

ADC Shifting
Shows the ADC values stored into our variables correctly. Un | Un-1 | Un-2 | Un-3 | 139 | 0 | 127 | 0 | 116 | 139 | 0 | 127 | 113 | 116 | 139 | 0 | 117 | 113 | 116 | 139 | 121 | 117 | 113 | 116 | 123 | 121 | 117 | 113 | 124 | 123 | 121 | 117 | 123 | 124 | 123 | 121 | 123 | 123 | 124 | 123 | 122 | 123 | 123 | 124 | 119 | 122 | 123 | 123 | 1121 | 119 | 122 | 123 | 119 | 121 | 119 | 122 | 115 | 119 | 121 | 119 | 112 | 115 | 119 | 121 | 108 | 112 | 115 | 119 | 108 | 108 | 112 | 115 | 102 | 104 | 108 | 112 | 106 | 102 | 104 | 108 | 114 | 103 | 102 | 104 | 125 | 114 | 103 | 102 | 131 | 125 | 114 | 103 | 133 | 131 | 125 | 114 |

Calculating u[n], x[n], and Y[n] This portion of the algorithm implements the nonlinear transform. The derivative of the ECG is approximated by the backwards difference. Let un denote the current ECG sample. The backward difference xn is given by: Xn=un-un-1 u (0) = most current sample, represents u(0) u (3) = oldest sample, represents un-3
X1= u(1)-u(0)
X2=u(2)-u(1)
X3= u(3)-u(2)
Y= (X1)(X2)(X3)

Y2 is only calculated if X1*X2*X3 is positive: X(n) > 0
Example raw data (Dom): u(0) | u(1) | u(2) | u(3) | X1 | X2 | X3 | Y2 | (x-X)^2 | sigma | 195 | 162 | 73 | 31 | 33 | 89 | 42 | 123354 | 14019668246 | 23680.94 | 122 | 120 | 116 | 115 | 2 | 4 | 1 | 8 | 24416643.34 | | 129 | 126 | 124 | 122 | 3 | 2 | 2 | 12 | 24377128.78 | | 132 | 129 | 126 | 124 | 3 | 3 | 2 | 18 | 24317916.94 | | 135 | 132 | 129 | 126 | 3 | 3 | 3 | 27 | 24229234.18 | | 136 | 135 | 132 | 129 | 1 | 3 | 3 | 9 | 24406761.7 | | 138 | 136 | 135 | 132 | 2 | 1 | 3 | 6 | 24436412.62 | | 136 | 135 | 133 | 131 | 1 | 2 | 2 | 4 | 24456189.9 | | 137 | 136 | 135 | 133 | 1 | 1 | 2 | 2 | 24475975.18 | | 140 | 135 | 134 | 130 | 5 | 1 | 4 | 20 | 24298195.66 | | 141 | 140 | 135 | 134 | 1 | 5 | 1 | 5 | 24446300.26 | | 132 | 131 | 130 | 128 | 1 | 1 | 2 | 2 | 24475975.18 | | 140 | 135 | 134 | 132 | 5 | 1 | 2 | 10 | 24396882.06 | | 143 | 140 | 135 | 134 | 3 | 5 | 1 | 15 | 24347513.86 | | 146 | 143 | 140 | 135 | 3 | 3 | 5 | 45 | 24052354.66 | | 142 | 141 | 140 | 139 | 1 | 1 | 1 | 1 | 24485870.82 | | 140 | 137 | 136 | 133 | 3 | 1 | 3 | 9 | 24406761.7 | | 132 | 128 | 123 | 122 | 4 | 5 | 1 | 20 | 24298195.66 | | 135 | 132 | 128 | 123 | 3 | 4 | 5 | 60 | 23905450.06 | | 136 | 131 | 128 | 125 | 5 | 3 | 3 | 45 | 24052354.66 | | 137 | 135 | 132 | 131 | 2 | 3 | 1 | 6 | 24436412.62 | | 132 | 127 | 126 | 125 | 5 | 1 | 1 | 5 | 24446300.26 | | 134 | 132 | 127 | 126 | 2 | 5 | 1 | 10 | 24396882.06 | | 135 | 134 | 132 | 127 | 1 | 2 | 5 | 10 | 24396882.06 | | 128 | 126 | 121 | 118 | 2 | 5 | 3 | 30 | 24199709.26 | |

Example raw data (Vic): u(0) | u(1) | u(2) | u(3) | X1 | X2 | X3 | Y2 | (x-X)^2 | sigma | 145 | 1 | 3 | 128 | 144 | -2 | -125 | 36000 | 1288614711 | 31363.98 | 148 | 147 | 139 | 129 | 1 | 8 | 10 | 80 | 516.1984 | | 193 | 143 | 78 | 31 | 50 | 65 | 47 | 152750 | 2.3301E+10 | | 137 | 130 | 124 | 122 | 7 | 6 | 2 | 84 | 350.4384 | | 121 | 120 | 119 | 118 | 1 | 1 | 1 | 1 | 10346.9584 | | 130 | 128 | 121 | 115 | 2 | 7 | 6 | 84 | 350.4384 | | 127 | 117 | 112 | 108 | 10 | 5 | 4 | 200 | 9463.3984 | | 129 | 127 | 117 | 112 | 2 | 10 | 5 | 100 | 7.3984 | | 155 | 146 | 134 | 126 | 9 | 12 | 8 | 864 | 579547.238 | | 166 | 155 | 146 | 134 | 11 | 9 | 12 | 1188 | 1177832.68 | | 174 | 166 | 155 | 146 | 8 | 11 | 9 | 792 | 475106.918 | | 182 | 174 | 166 | 155 | 8 | 8 | 11 | 704 | 361537.638 | | 125 | 124 | 119 | 116 | 1 | 5 | 3 | 15 | 7694.7984 | | 119 | 115 | 106 | 102 | 4 | 9 | 4 | 144 | 1704.0384 | | 122 | 119 | 115 | 106 | 3 | 4 | 9 | 108 | 27.8784 | | 127 | 122 | 119 | 115 | 5 | 3 | 4 | 60 | 1824.9984 | | 130 | 129 | 125 | 121 | 1 | 4 | 4 | 16 | 7520.3584 | | 132 | 130 | 126 | 124 | 2 | 4 | 2 | 16 | 7520.3584 | | 136 | 134 | 131 | 130 | 2 | 3 | 1 | 6 | 9354.7584 | | 143 | 140 | 131 | 129 | 3 | 9 | 2 | 54 | 2373.6384 | | 125 | 124 | 118 | 112 | 1 | 6 | 6 | 36 | 4451.5584 | | 126 | 125 | 124 | 118 | 1 | 1 | 6 | 6 | 9354.7584 | | 131 | 126 | 125 | 124 | 5 | 1 | 1 | 5 | 9549.1984 | | 140 | 131 | 126 | 125 | 9 | 5 | 1 | 45 | 3331.5984 | | 143 | 140 | 131 | 126 | 3 | 9 | 5 | 135 | 1041.9984 | |

From the collected data, Y2 is significantly larger when an R wave is detected. For Dom, most all non-R-wave Y2 values are below 100. For Victoria, whose ECG seems to be less clean, values still remain below 4,000 vs the 152,750 of an R-wave. Nonetheless, the majority of the Y2 values lie below a couple thousand. From the 10 trials, we selected our base threshold to be 2,000 based on the standard deviation.

Detection Performance: Accuracy Testing and Human Testing To test the accuracy of our device, we used LabVIEW to simultaneously record the ECG waveform and the buzzer waveform. When the R-wave was detected, the buzzer beeped. The buzzer spikes indicated when the algorithm detected an R-wave. This test has been performed with 4 human subjects.

The figure shows a comparison of the output of the analog circuit and the spike of the buzzer. If there is a miss, the buzzer will not spike but we will be able to clearly indicate an R-wave on the ECG waveform. If the buzzer spikes without an R-wave, it is a false positive. By measuring over a period of time, we can determine the percentage accuracy of our algorithm by how many R-waves it detects.

* True positive (TP): There is an R-wave and our algorithm detects an R-wave * False positive (FP): There is no R-wave but our algorithm detects and R-wave * True negatives (TN): There is no R-wave but and our algorithm does not detect an R-wave * False negatives (FN): Where there is an R-wave but our algorithm does not detect the R-wave

For the above test, # of R-waves | True Positives | False Positive | FN + FP | | # | % | # | % | # | % | 13 | 12 | 92 % | 1 | 8% | 2 | 16% |

Human Testing
The following is the output of the human subject’s ECG waveform and the buzzer spikes. From the human testing data, we determined two things: 1. Algorithm Accuracy 2. Overall System Accuracy
Algorithm Accuracy
Our system outputs heart rate as an average of the last 5 BPMs. In order to test that our algorithm was functioning correctly, we manually re-implemental the actions of the microcontroller (in LabVIEW and excel) and compared the outputs between the two. To find the BPM being displayed on the 7 segment in Excel, we first found the distance between each R-wave, calculated the BPM, and found the 5 BPM average. We compared the experimental results with what was appearing on the 7segment display, which we recorded with a camera. The algorithm accuracy was found to be within 3%.
Overall System Accuracy
Our 7 segment display outputs the heart rate as an average of the last 5 BPMs in order to prevent a high rate of change on the 7segment display; therefore, it is not instantaneous. We defined our overall system accuracy to be within ±10% of the instantaneous, or actual, heart rate. The instantaneous BPM would always be the 5th BPM in the average of 5 BPMs in our algorithm. The overall system accuracy was found to be 95%, or within 5%.
The figure is the manual calculation of the algorithm and the overall system accuracy of the human testing waveform. Notice the first 5 BPM outputs of the 7 segment display are disregarded since they are averaged with zeros when the system first turns on.
Other common movements of ECG were also captured and recorded for accuracy: * Lightly moving fingers * Lightly Scratching palm * Lightly Coughing * Heavy Coughing * Anxious Legs * Heavy breathing * Mild shivering * Respiration
[Figures will be included with buzzer spikes] Our algorithm was robust enough to detect Rwaves in all cases with little error. We improved the accuracy of our algorithm by changing the threshold and by varying the window length (or refractory period). Changing the threshold to detect an R wave allowed some noise to be filtered out. Varying the refractory period prevented false positives on a high T wave.
Environmental Testing [TBA] * Average Lifetime: 6.3 Hours * Water [Pic spray with water] * Drop Test [Pic] * Temperatures * Usage Range: 0°C - 60°C (32°F - 140°F) * Freezer * Heater

Processing Time * Average time to compute entire algorithm: TBA * Average time for BPM to show on display: TBA * Display Refresh Rate: TBA * Comparison of our device with predicate devices * Users Manuel * Medical Electrical Equipment standards met | Marketing Requirement | Engineering Requirement | Requirement Met? | Primary Mission | Should measure heart rate | Sensor accuracy must be within +/- 10% | Yes –within 7% | | | Processing time should be less than five seconds | Yes – expected | | Should display heart rate | Display must handle 3 digits (LCD, 7-segment display, etc) | Yes – Displays heart rate on 7-segment displays | | Should have a low cost (affordable for most developing countries) | Production cost should not exceed $20 | Yes – Production in quantity of 1,000 ~$15 | | Should be portable | Total product weight should not exceed 10 oz (including batteries) | No – Device has exceeded 1o oz (final weight TBA) | | Must be comfortable for the end user | Device should be enclosed in a casing of hard material (preferably plastic) | Yes – Plastic enclosure | | Must be sterile for applicable medical use | The product must be enclosed such that a sanitizing spray or wipe will not damage the unit or cause it to malfunction | Yes – Plastic enclosure allows for safe sterilization | | Should operate on battery power | Power requirements should not exceed 9V | Yes- System operates at 6V | Secondary Mission | Store heart rate levels for up to 5 hours | Should have at least 128MB of internal RAM | Yes – Can continuously measure heart rate for over 6 hours | | Should provide access for data retrieval (usb interface, wifi, etc.) | Device should connect and be "plug-and-play" ready (no need for software) | No | | Should provide low-battery warning | Either a Display or LED should change color to warn user of status | No |

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