1. Study of Heart Disease and Analysis of PPD Algorithm m5151117 Yumiko Kimezawa October 28, 2011RPS1

2. Outline Previous Work Modification to Methods Current PPD Algorithm My Opinion Future Work October 28, 2011RPS2

3. Previous Work Studying how to actually capture an ECG signal from people An A/D converter included in our daughterboard is unfit for capturing the ECG signal An input amplifier will be required because the ECG signal is very weak October 28, 2011RPS3

4. Modification to Methods Capturing an ECG signal from people actually We use sample data from database as input data Capturing an ECG signal from people actually October 28, 2011RPS4 Hard Taking long time Modification Studying only

5. Current PPD Algorithm This algorithm seems to process only ECG signals include typical peaks (P, Q, R, S, T and U) This algorithm can not process irregular heart rhythm such as ventricular fibrillation (Vf) October 28, 2011RPS5

6. Ventricular Fibrillation (VF) October 28, 2011RPS6 ventricle Extremely dangerous situation Deadly arrhythmia Irregular rhythm P wave is not found QRS waves are wide-ranging Severe decrease in blood pressure and no feeling a pulse

7. Processing Results of VF October 28, 2011RPS7 PPD algorithm must have detected peaks incorrectly On the ventricular fibrillation wave, P waves don’t appear and QRS waves are wide- ranging

8. My Opinion Someone’s heart beats hundreds of thousands of times per day (100,000 times/day) In addition to extracting ECG wave form, computers have to support analysis of the wave whether heart is normal or not Doctors only have to receive information of patients considered at risk for heart disease October 28, 2011RPS8 It is difficult for doctors to diagnose so many patients My Opinion

9. Future Work Analysis of PPD algorithm Optimization of PPD algorithm October 28, 2011RPS9

10. October 28, 2011RPS10

11. October 28, 2011RPS11 MIT:16272 RR Interval PPD AlgorithmMIT Database 0.578s (0.000s - 0.578s)0.570s (0.000s – 0.570s) 0.984s (0.578s – 1.562s)0.984s (0.570s – 1.555s) 0.953s (1.562s – 2.516s)0.953s (1.555s – 2.508s) 0.961s (2.516s – 3.477s)0.969s (2.508s – 3.477s) 0.953s (3.477s – 4.430s) 0.969s (4.430s – 5.398s)0.961s (4.430s – 5.391s) 0.969s (5.398s – 6.367s)0.977s (5.391s – 6.367s) 0.992s (6.367s – 7.359s)0.984s (6.367s – 7.352s) 0.961s (7.359s – 8.320s)0.969s (7.352s – 8.320s) 0.984s (8.320s – 9.305s)

12. October 28, 2011RPS12 MIT:16273 RR Interval PPD AlgorithmMIT Database 0.086s (0.000s - 0.086s)0.070s (0.000s – 0.070s) 0.609s (0.086s – 0.695s)0.609s (0.070s – 0.680s) 0.602s (0.695s – 1.297s)0.602s (0.680s – 1.281s) 0.602s (1.297s – 1.898s)0.602s (1.281s – 1.883s) 0.609s (1.898s – 2.508s)0.609s (1.883s – 2.492s) 0.609s (2.508s – 3.117s)0.609s (2.492s – 3.102s) 0.617s (3.117s – 3.734s)0.617s (3.102s – 3.719s) 0.633s (3.734s – 4.367s)0.633s (3.719s – 4.352s) 0.656s (4.367s – 5.023s)0.656s (4.352s – 5.008s) 0.641s (5.023s – 5.664s)0.641s (5.008s – 5.648s) 0.641s (5.664s – 6.305s)0.633s (5.648s – 6.281s) 0.617s (6.305s – 6.922s)0.625s (6.281s – 6.906s) 0.633s (6.922s – 7.555s)0.633s (6.906s – 7.539s) 0.617s (7.539s – 8.156s) 0.625s (8.156s – 8.781s) 0.617s (8.781s – 9.398s)

13. October 28, 2011RPS13 MIT:16273 RR Interval PPD AlgorithmMIT Database 0.086s (0.000s - 0.086s)0.070s (0.000s – 0.070s) 0.609s (0.086s – 0.695s)0.609s (0.070s – 0.680s) 0.602s (0.695s – 1.297s)0.602s (0.680s – 1.281s) 0.602s (1.297s – 1.898s)0.602s (1.281s – 1.883s) 0.609s (1.898s – 2.508s)0.609s (1.883s – 2.492s) 0.609s (2.508s – 3.117s)0.609s (2.492s – 3.102s) 0.617s (3.117s – 3.734s)0.617s (3.102s – 3.719s) 0.633s (3.734s – 4.367s)0.633s (3.719s – 4.352s) 0.656s (4.367s – 5.023s)0.656s (4.352s – 5.008s) 0.641s (5.023s – 5.664s)0.641s (5.008s – 5.648s) 0.641s (5.664s – 6.305s)0.633s (5.648s – 6.281s) 0.617s (6.305s – 6.922s)0.625s (6.281s – 6.906s) 0.633s (6.922s – 7.555s)0.633s (6.906s – 7.539s) 0.617s (7.539s – 8.156s) 0.625s (8.156s – 8.781s) 0.617s (8.781s – 9.398s)

14. Our Architecture October 28, 2011RPS14 A/D converter FilterRAM Processing Results From patient Sensor Processing results are sent through the Ethernet

15. Important Things in Measurement of ECG Signal Clinically-important frequency component of ECG signal - 0 ~ 250Hz October 28, 2011RPS15 Change in voltage in chest wall -Less than 3mV (very weak) Measurement in environments with much noise Change in voltage inside this range must be faithfully reproduced Voltage gain of high signal-to-noise ratio (250 to 1000 times) must be gained Signal-to-noise ratio: The ratio of signal power to the noise power

16. Book Knowledge October 28, 2011RPS16 Impedance converter Lead network Head amplifier Micro computer ADC Main amplifier Isolation circuit Output equipment Lead Code Power Circuit An example of block diagram illustrating cardiography equipment

17. Book Knowledge October 28, 2011RPS17 Impedance converter Lead network Head amplifier Micro computer ADC Main amplifier Isolation circuit Output equipment Lead Code Power Circuit An example of block diagram illustrating cardiography equipment This circuit prevents body’s impedance from being lower than input circuit’s impedance

18. Book Knowledge October 28, 2011RPS18 Impedance converter Lead network Head amplifier Micro computer ADC Main amplifier Isolation circuit Output equipment Lead Code Power Circuit An example of block diagram illustrating cardiography equipment Constitution of 12-lead from the combination of sensors A~J : Sensors Example - Ⅰ : Output between A and E -aVR: Output between A and F

19. Book Knowledge October 28, 2011RPS19 Impedance converter Lead network Head amplifier Micro computer ADC Main amplifier Isolation circuit Output equipment Lead Code Power Circuit An example of block diagram illustrating cardiography equipment ECG signal is very weak The signal must not be amplified suddenly Differential amplifier is used as head amplifier An amplifier is needed The signal is amplified in stages Noises are reduced signal-to-noise ratio is improved

20. Book Knowledge October 28, 2011RPS20 Impedance converter Lead network Head amplifier Micro computer ADC Main amplifier Isolation circuit Output equipment Lead Code Power Circuit An example of block diagram illustrating cardiography equipment For securing of security, impedance converter, lead network and head amplifier have to be isolated from main amplifier, power circuit and A/D converter

21. Question A/D converter (AD9254) is included in HSMC -Pipelined switched capacitor ADC -Sampling frequency: 150MHz -Resolution: 14-bit -Power: 430mW October 28, 2011RPS21 HSMC Performance is overmuch Clinically-important frequency component of ECG signal is from 0 to 250Hz 500Hz is enough for sampling frequency Using a lot of electricity Conversion process is complex Using A/D converter in HSMC is of questionable value

22. 心電計の回路を表すブロック 図の例 October 28, 2011RPS22 イン ピーダ ンス変 換器 誘導ネッ トワーク 前置 増幅器 マイクロコ ンピュータ AD 変換器 主増幅器 アイソ レーショ ン回路 出力装置

23. 標準１２誘導を作るための 誘導ネットワークの原理 October 28, 2011RPS23 A BCD E F G H I J A~J の各点の出 力を組み合わ せる。 例えば、第Ⅰ誘 導は A と E 、 aVR は A と F を組み 合わせたもの となる。