Design, Development and Verification of Indigenous Designs for Cardiovascular Healthcare Monitoring

Soni, Pratik Govindprasad (2017) Design, Development and Verification of Indigenous Designs for Cardiovascular Healthcare Monitoring. Masters thesis, Indian Institute of Technology Hyderabad.

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The study of ECG signal is extensively used for analysis of heart diseases. There are many companies in the market which has developed ECG devices to acquire the ECG signal and print them on the paper, but doesn’t have access to store the ECG data of the patent in digital format. Our project aim is to develop the ECG acquisition board to get the digitized ECG which can be used for diagnosis as well as for research. We have developed two ECG acquisition boards and other two development boards to classify the ECG signals, the first Board is developed to store the ECG data in digitized format in SD card. We have used ADS1198(8 channel ADC) and microcontroller LPC1769 to collect the ECG data from body electrodes. ECG Analog data is converted to digital using ADS1198. Data is stored in .bin format in SD card using LPC1769, we are able to store the data accurately. To see the data in .txt or in graphical format we need to transfer the data to the computer manually on each and every trial. There are few issues in working with the first board, since at each and every record we need to remove the SD card from the acquisition board and need to insert in the computer to view the waveforms. To avoid this and to have more convenient and seamless transmission we have developed the second acquisition board which is having a Bluetooth module RN4020 instead of SD card, this board allows the user to directly send the digitized data to the paired Bluetooth device like computer or mobile phone wirelessly to view the ECG waveforms. In next board, we have applied Feature Extraction (FE) and rule engine algorithm on the ECG data acquired in the computer to see ECG signal is healthy or unhealthy. Here, we used RS-232 driver to transfer ECG data from computer to processor using cyclone IV FPGA(EP4CE55_F484), this serves as our third board to classify the ECG signal. The processor used is developed by the DRDO ( ANUCIA). We have implemented the algorithms on ANUCIA using their own instruction set, registers and control logic and we are able to differentiate between healthy and unhealthy ECG signals. vii Fourth development board is to test the functionality of IoT (Internet-of-Things) chip which is designed in-house. For this board we have used ADS1192 to take one lead analog ECG data and convert it to digital. The data is then being transferred to IoT chip using LPC1769.The IoT chip takes one lead ECG data where each sample is of 16 bit, these samples are fed as input to the 16 input pins of the IoT chip.The processing modules in the IoT chip classifies the ECG signal as normal or abnormal. We can develop an ECG acquisition board using Wi-Fi module and directly connect it to the cloud. The data can be accessed by any doctor having internet connection and authority to access that cloud data, this could be the future work of my project.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Thesis (Masters)
Uncontrolled Keywords: ECG, ADS1198, LPC1769, Feature extraction, IoT chip, classifer, TD834
Subjects: Electrical Engineering > Instruments and Instrumentation
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 28 Jun 2017 11:34
Last Modified: 28 Jun 2017 11:34
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