1. An FPGA implementation of real-time QRS detection H.K.Chatterjee Dept. of ECE Camellia School of Engineering & Technology Kolkata India R.Gupta, J.N.Bera, M.Mitra Dept. of Applied Physics University Of Calcutta Kolkata India m5151117 Yumiko Kimezawa October 11, 20121RPR

2. Outline Introduction Materials and Methods Testing and Results Conclusion October 11, 2012RPR2

3. Introduction QRS detection is one of the important and primary job and very often used for heart rate computation In recent years, there has been considerable use of FPGA based system for ECG monitoring, QRS detection and feature extraction This paper illustrates a real time QRS detection algorithm using an FPGA based embedded system October 11, 2012RPR3

4. Materials and Methods October 11, 2012RPR4 Data Port Status Port Control Port ptb-db file Data Capture & Analysis Section Display Section 8 Switches 8 LEDs Interfacing Unit Parallel port PC FPGA Xilinx Spartan 2 Figure 1: Block diagram of the system Trigger pulse train Start Capture

5. Materials and Methods The entire work Generation of digitized ECG from ptb-db file Development and testing of the algorithm in FPGA platform October 11, 2012RPR5

6. Materials and Methods Generation of digitized ECG from ptb-db file October 11, 2012RPR6 Figure 2: Generation of ECG data by PC Data send from PC parallel port (D0 – D7) Data accepted by FPGA (P108 – 111, P113 – 115, P119) Pulse train generated by FPGA (P121), & accepted by PC parallel port (S7) “Start Capture” pulse generated by PC parallel port (C0) & accepted by FPGA (P120)

7. Materials and Methods Real time QRS detection from the ECG samples -The training zone: The first 1500 samples -A characterization of QRS polarization is performed based on 20 point slope -ECG samples are stored in a group of memory cells which holds the last 42 samples -Computing 20 point average slope by calculation differences like R20-R19, R19-R18,….., R2-R1 October 11, 2012RPR7 Formula:

8. Materials and Methods October 11, 2012RPR8 R１R１ R４２R４２ R ２０ Current index point Current point of reference R ２０ Figure 3: Illustration of characterization of QRA complex Average of both side slope: (|R20-R40| + |R21-R0|)/2 Group I: Left side 20 pt. slope: R42-R21 > 0 & Right side 20 pt. slope: R20-R1 < 0 Group II: Left side 20 pt. slope: R42-R21 0

9. Testing and Results Test using normal and abnormal data in MIT-PTB database and MIT-BIH arrhythmia database Initially performed in the MATLAB platform 30000 samples (Single lead data) Resolution: 8-bit sampling interval: 1 ms October 11, 2012RPR9

10. Testing and Results The evaluation criteria are Sensitivity (Re) and Positive Predictivity (P+), defined as: October 11, 2012RPR10 and TP (True-Positive): correctly found R peaks FN(False-Negative): missed R peaks FP: the number of misdetection

11. Testing and Results MATLAB simulation -With mit-db, 60,000 samples Re and P+ of 97.82 % 98.35 % respectively -With ptb-db, 120 leads An average sensitivity of 99.47 % Predictivity of 95 % October 11, 2012RPR11

12. Testing and Results FPGA implementation -With a total of 100 single lead data, each containing 7,000 samples An average Re and P+ of 94.8 % 98.17 % respectively October 11, 2012RPR12

13. Conclusion The algorithm is implemented with synthetic ECG data from ptb-db and mit-db In the present approach, 20 point average slope eliminates the effect of high frequency noise and to minimize the effect of any momentary spike 2 point slope should not exceed the slope threshold criteria October 11, 2012RPR13