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Embedded Cardiac Rhythm Interpretative Assistant

This project focuses on the development of an embedded cardiac rhythm interpretative assistant that enables real-time analysis of EKG data for diagnosing various cardiac conditions. It encompasses the entire architecture, including hardware for data acquisition and wireless transmission, alongside sophisticated software for data analysis. Key features include mapping of cardiac waveforms, detection of normal QRS complexes and P waves, heart rate calculation, and identification of abnormalities. Future considerations include enhanced EKG signal acquisition, reduced system size, and improved diagnostic capabilities using advanced algorithms.

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Embedded Cardiac Rhythm Interpretative Assistant

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  1. Embedded Cardiac Rhythm Interpretative Assistant Faculty: Dr. Patrick Bobbie Research Assistants: Chaudary Zeeshan Arif Hema Chaudhari Thara Soman

  2. EKG Description

  3. Mapping of Waveforms to different sections in the heart

  4. Hardware and Software Implementation • Hardware • Data Acquisition: • Capture cardiac data in digital format • Transfer data to set-top box • Software • Data Analysis: • Analyze EKG data to diagnose cardiac condition of the patient

  5. Architecture of ECG Sensor-Transmitter

  6. ECG Cables, Electrodes etc.

  7. EKG Data Acquisition Unit

  8. Data Buffering & Wireless Transmission Unit

  9. Resultant EKG – Scope View

  10. Resultant EKG – PC View

  11. EKG Analysis • Noise ion using Filters • Detection of normal QRS complex • Detection of P wave • Derive relationship between P and QRS wave • Determine the heart rate • Determine the abnormality or heart conditions • Map heart condition to knowledge of diseases

  12. Diagnosis of Tachycardia

  13. QRS Detection & Heart Beat Calculation

  14. Future Considerations • EKG signal acquisition from individually measured electrode potentials • Wireless EKG electrodes and size reduction of the system • Signal compression • Software filters and improved diagnosis • OSGi Bundle-based analysis of captured EKG data. • Ambulatory EKG capture and analysis using fuzzy logic.

  15. Other Projects • eRx prescription – smart card based prescription • Lego robotics programming – lejos API • Home automation using X10 • Digital TV applications

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