1. Project Progress Presentation Project Title: Real-time ECG Processing for Mobile Digital Healthware Student: Darren Craven Date: 24/01/2010 Supervisor: Dr. Eddie Jones Co-Supervisor: Dr. Peter Corcoran

2. Aims/Tasks (Development Plan) Develop algorithm to detect the QRS intervals in a ECG signal. This algorithm must calculate the heart rate to monitor potential problems. Algorithm then implemented in a Body Area Network.

3. Aims/Tasks (Development Plan) Top-level breakdown of the work to be done: Semester 1: Development of the algorithm, the testing of it for different attributes: efficiency, accuracy etc. Semester 2: Investigation of this implementation of the algorithm.

4. Milestones Characterisation of compression algorithm in Matlab (on the basis of compression ratio and signal distortion only). Development of a basic system for screening of ECG signals for arrhythmia detection.

5. Milestones Investigation of the effect of ECG signal compression on performance of automatic arrhythmia detection system. Real-time development of screening/classification algorithm, and implementation on either embedded sensor node or mobile phone.

6. Body Area Network(BAN) The BAN worn by person will communicate with a mobile device such as a mobile phone. Warning signal could be sent out depending on the state of the patients ECG signals. The algorithm must be able to screen accurately for the possible cardiac arrythmias in the ECG signals.

7. Body Area Network(BAN) Aims to develop highly reusable software applications. Comfort is also important. Power requirements important for a setup such as this.

8. Pan-Tompkins Algorithm The Pan-Tompkins algorithm being worked on for QRS detection in ECG signals. 6 different stages to the algorithm: High Pass Filter, Low Pass Filter, Differentiation,Integration, Squaring and Sliding Window Threshold Adjustment.

9. Pan-Tompkins Algorithm Algorithm Implementation in Matlab:

10. Pan-Tompkins Algorithm Algorithm Implementation continued:

11. Current/Future Work Developing C code for the Pan-Tompkins algorithm tested in Matlab. Further compression testing on the Pan- Tompkins algorithm Matlab code for various ECG signals. Choice of the mobile system to be implemented.

12. Any Questions?