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ABSTRACT Annually, heart disease causes over 17 million deaths worldwide. One of the best ways of getting preventive prognoses is to use electrocardiograms.

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Presentation on theme: "ABSTRACT Annually, heart disease causes over 17 million deaths worldwide. One of the best ways of getting preventive prognoses is to use electrocardiograms."— Presentation transcript:

1 ABSTRACT Annually, heart disease causes over 17 million deaths worldwide. One of the best ways of getting preventive prognoses is to use electrocardiograms (ECGs). The newest trend with ECG devices has been to increase their mobility, which allows them to be more broadly usable. A critical aspect of this is using recent advances in low-power computing and wireless transmission to create a small, unobtrusive device. With such a device, patients can maintain their regular lifestyles while still receiving intermittent monitoring feedback. Such a device would also be useful for monitoring the progress of pacemakers and other heart implants in non-hospital settings. One of the shortcomings of current devices (eg. Holter monitors) is that they are still unwieldy and thus interfere with patients' activities. This project takes the first step towards making such a device by designing and implementing a low-cost hardware prototype which acquires, digitizes, and wirelessly transmits a simulated ECG signal to a nearby computer acting as a web server. This data can then be accessed over the Internet through a mobile device. AUTHORS: Willy Bernal EE ‘10 Rohit Chandra EE ‘10 Jason Delisser EE ‘10 Eric Pinter EE ‘10 ADVISORS: Dr. Rahul Mangharam Special thanks to Ni Lei, Godwin Meyers, and Matthew Shieh DEMO TIMES: Thursday, April 22, :00, 9:30 AM, 3:00, 3:30 PM GROUP #3 FRONT-END ACQUISITION ECG signals read from a patient’s body have small amplitudes and are very noisy. Such a signal is unsuitable for digitization. The original analog signal must be filtered and amplified to yield a more easily interpreted signal. The front-end acquisition portion of the circuit amplifies the differential signal from a patient before putting it through notch and low pass filters. These filters attenuate ambient noise and also remove high frequency components which are irrelevant for ECG analysis. This filtered analog signal is then digitized using the AD7718, a 24-bit sigma- delta ADC. WIRELESS COMMUNICATION The Firefly Sensor Networking Platform is used in this project for one way data communication between the device and a computer. This platform uses the IEEE standard which is suited for wireless personal area networks implemented using embedded devices. One node is connected to the device, and the other to a computer which receives the data. Data transmission rates can be adjusted depending on the application. SMART PHONE DISPLAY The digitized signal is transmitted to a web server which can then be accessed using any web browser. This signal can also be displayed on a smart phone capable of Internet access (in this case an iPhone). The application on the iPhone can plot the transmitted data for viewing by the patient or a medical professional. It also has an emergency button which calls a pre- programmed medical provider or professional. MICROCONTROLLER This circuit uses the ATmega1281 to control the operation of the main components. Using a serial peripheral interface (SPI), the microcontroller communicates with and synchronizes the ADC, the accelerometer, the MicroSD memory chip, and the transceiver, dividing computing time between all of them. It runs the Nano-RK real time operating system which is specially developed for the Firefly Sensor Networking Platform. ECG ANALYSIS Beat rate analysis alone is sufficient to diagnose certain problems. Thus, a beat rate detector was developed in Matlab to process the digital output of the circuit. Eventually, this will be converted to C, which can then be implemented on the microcontroller (considerably reducing the amount of data transmitted). For now, it is a standalone application which takes an existing ECG waveform and calculates the effective beat rate. RESULTS Wireless ECG Monitor Front-End Acquisition Analog to Digital Converter Microcontroller Transmitting Node Receiving Node and Web Server Receiving Node and Web Server Smart Phone Application Band-pass Filter Remove Baseline Drift Differentiate Square Integrate Differentiate Square Integrate Thresholding Peak Detection Beat Rate Calculation


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