real-time heart monitoring and ecg signal...
TRANSCRIPT
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Real-time Heart Monitoring and ECG Signal Processing
Fatima Bamarouf, Claire Crandell, and Shannon Tsuyuki
Advisors: Drs. Yufeng Lu and Jose Sanchez
Department of Electrical and Computer Engineering Bradley University
October 1, 2015
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Introduction and Overview
• Problem Background
• Problem Statement
• Constraints
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Problem Background
• Arrhythmias
• Are irregular heartbeats caused by defective electrical signals in the heart [1]
• Include premature ventricular contractions (PVCs)
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Problem Background
• Premature ventricular contractions (PVCs)
• Up to 40-75% of people have occasional PVC beats [2]
• May lead to ventricular tachycardia (VT)
Figure 1. Electrocardiogram with “V” labels for PVCs [3]
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Problem Background
• Ventricular tachycardia (VT)
• Involves the ventricles contracting before they have filled completely with blood
• Limits blood flow to the body
Figure 2. ECGs for normal heart rhythm and ventricular tachycardia [1]
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Problem Background
• An electrocardiogram (ECG) describes the heart’s electrical activity
• An ECG can be recorded using a Holter monitor or event monitor
Figure 3. Features of a normal ECG [4]
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Problem Background
• Holter monitor
Figure 4. Holter monitor with ECG reading [5]
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Problem Background
• Event monitor
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Figure 5. Wireless event monitor system [6]
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Problem Background
• Holter and event monitors are limited in functionality
• Utilize some in-platform signal processing for diagnostic assistance
• Must perform some signal processing offline
• Are unable to address medical issues in real time
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Problem Statement
• Develop a low-power, stand-alone embedded system for continuous heart monitoring that will
• Process ECG data in real time
• Detect PVCs accurately and consistently
• Alert the patient’s doctor wirelessly of ventricular tachycardia
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Constraints
• Real-time ECG signal processing
• On-board signal processing computations
• Battery-powered functionality
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Scope 13
In Scope Out of Scope ECG signal processing Electrode interfacing, battery
circuit PVC and VT detection Detection of other types of cardiac
arrhythmias High-level wireless communication Security issues (encryption, data
integrity, etc.)
TABLE I. SCOPE OF HEART MONITORING SYSTEM
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Design Approach and Method of Solution
• System Block Diagram
• State Diagram
• Nonfunctional Requirements
• Functional Requirements
• Description of Solution
• Solution Testing
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System Block Diagram
Real-time Heart Monitor System
Unprocessed Heart Data
Wireless Message
Figure 6. Overall heart monitoring system diagram
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State Diagram
Figure 7. State diagram for heart monitoring system
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Store heart data into memory
Perform preprocessing
Classify each beat as PVC or
non-PVC
Determine if VT is present
Transmit a message to the doctor
(for VT)
Start
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Nonfunctional Requirements
• Compatible with all patient data in the MIT-BIH database [3]
• Reasonably priced
• Portable
• Low-power
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Functional Requirements
• Storing heart data input into memory
• The embedded device must have an internal memory of at least 25 kB
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Functional Requirements
• Performing preprocessing on the heart signal
• Filtering/normalization must prepare the heart data for the QRS, PVC, and VT detection functions
• QRS detection must have at least 90% sensitivity and 90% specificity [8]
• QRS detection must be tested using heart data from the MIT-BIH arrhythmia database [3]
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Functional Requirements
• Classifying each QRS complex as PVC or non-PVC
• Must have at least 90% accuracy [9]
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Functional Requirements
• Determining whether ventricular tachycardia is present using PVC detection results
• Must have at least 90% accuracy
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Description of Solution
Functions Means Storing heart data RAM
Preprocessing (Filtering/QRS detection) Pan-Tompkins
PVC detection Template matching
Ventricular tachycardia detection Three or more consecutive PVCs
Wireless functionality CC3200 LaunchPad
TABLE II. SELECTED DESIGN FOR HEART MONITORING SYSTEM
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Description of Solution: Hardware
• SimpleLink Wi-Fi CC3200 Launchpad
• Inexpensive: $30.00
• Simplifies data transmission
• 256 kB RAM
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Figure 8. CC3200 Launchpad [10]
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Description of Solution: QRS Detection
• Pan-Tompkins algorithm [11]
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Figure 9. Preliminary QRS detection using the Pan-Tompkins algorithm and MATLAB
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Description of Solution: PVC Detection
• Correlation with normal QRS-complex and RR-interval templates
• Low correlation signals PVC
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Figure 10. QRS and RR-interval templates and correlation [9]
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Description of Solution: Ventricular Tachycardia
• Three or more consecutive PVC beats
• Wireless message transmitted to medical authorities
Figure 11. ECG demonstrating ventricular tachycardia [3]
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Solution Testing
• MATLAB simulation of QRS, PVC, and VT detection
• Use MIT-BIH arrhythmia database for testing data
• Ensure that accuracy, sensitivity, and specificity are at least 90% using the WFDB toolbox
• Estimate the execution time
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Solution Testing
• C implementation of QRS, PVC, and VT detection
• Store the heart data in the board’s memory and export the detection results to a file
• Evaluate number of clock cycles required and quantization error propagation
• Test the amount of time needed to send heart data from a PC to the board
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Solution Testing
• Wireless communication
• Use a packet sniffer to verify wireless communication
• Verify that testing data sent from the board matches the data that the doctor would receive
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Solution Testing
• System integration (C implementation and wireless communication)
• Evaluate the delay between uploading the heart data and the doctor’s access to the data
• Verify that heart data input with three or more consecutive PVCs correctly transmits a message to the doctor
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Economic Analysis
Component Cost
CC3200 LaunchPad $30.00
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TABLE III. PROJECT COSTS FOR HEART MONITORING SYSTEM
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Schedule 35
Task Duration (hours) PVC Algorithm (MATLAB) 65
PVC Algorithm (C) 100 Wi-Fi Communication 150
Progress Report I 80
Progress Report II 80
Final Presentation 80
Final Report 80
TABLE IV. PROJECT SCHEDULE
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Schedule 36
Figure 12. Gantt chart for the fall semester
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Schedule 37
Figure 13. Gantt chart for the spring semester
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Division of Labor
• MATLAB Simulation (PVC detection)
• Shannon/Fatima
• C Programming (PVC detection)
• Claire/Shannon
• Wi-Fi Communication
• Fatima/Claire
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Societal and Environmental Impacts
• Low-power modes minimize battery consumption
• Testing data contains no personally identifiable information
• Wi-Fi technology allows for additional security [10]
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Contents
• Introduction and Overview
• Design Approach and Method of Solution
• Economic Analysis
• Schedule
• Division of Labor
• Societal and Environmental Impacts
• Summary and Conclusions
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Summary and Conclusions
• PVCs are irregular heartbeats that may lead to VT
• An embedded device is proposed that will detect PVCs in real time and wirelessly alert the patient’s doctor of VT
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Summary and Conclusions
• Design should be compatible with all patient data in the MIT-BIH database, reasonably priced, portable, and low-power
• Design must include real-time ECG signal processing, on-board signal processing computations, and battery-powered functionality
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Summary and Conclusions
• Proposed Design
• CC3200 LaunchPad (Texas Instruments)
• Pan-Tompkins algorithm for QRS detection
• Template matching for PVC detection
• Three consecutive PVC beats for VT detection
• Tested using MIT-BIH arrhythmia database and MATLAB
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Real-time Heart Monitoring and ECG Signal Processing
Fatima Bamarouf, Claire Crandell, and Shannon Tsuyuki
Advisors: Drs. Yufeng Lu and Jose Sanchez
Department of Electrical and Computer Engineering Bradley University
October 1, 2015
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References • [1] Arrhythmias. [Online] Available: http://watchlearnlive.heart.org/CVML_Player.php?moduleSelect=arrhyt
• [2] A. Pérez-Silva and J. L. Merino. “Frequent ventricular extrasystoles: significance, prognosis and treatment,” E-Journal of the ESC Council for Cardiology Practice, 2011. [Online] Available: http://www.escardio.org/COMMUNITIES/COUNCILS/CCP/E-JOURNAL/VOLUME9/Pages/frequent-ventricular-extrasystoles-significance-prognosis-treatment-Perez-Silva.aspx#.VNpf6_nF9TR
• [3] MIT-BIH Arrhythmia Database. [Online] Available: http://www.physionet.org/physiobank/database/mitdb/
• [4] Cardiovascular System Assessments. [Online] Available: http://media.lanecc.edu/users/driscolln/RT116/softchalk/Cardia_Assessment/Cardia_Assessment_print.html
• [5] Holter Monitor. [Online] Available: http://www.hopkinsmedicine.org/healthlibrary/test_procedures/cardiovascular/holter_monitor_92,P07976/
• [6] Cardiac Monitors. [Online] Available: https://www.medicompinc.com/cardiac-monitors/
• [7] Holter monitor (24h). [Online] Available: http://www.nlm.nih.gov/medlineplus/ency/article/003877.htm
• [8] B. Ribeiro, et al., “Choosing Real-Time Predictors for Ventricular Arrhythmia Detection,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 21, no. 08, pp. 1249-1263, 2007. [Online] Available: https://eden.dei.uc.pt/~bribeiro/FCT_files_2006/LNCS_ICONIP2006.pdf
• [9] P. Li, et al., “A low-complexity data-adaptive approach for premature ventricular contraction recognition,” Signal, Image and Video Processing, vol. 8, no. 1, pp. 111-120, 2013. [Online] Available: http://link.springer.com/article/10.1007%2Fs11760-013-0478-6
• [10] CC3200-LAUNCHXL. [Online] Available: http://www.ti.com/ww/en/launchpad/launchpads-connected-cc3200-launchxl.html?DCMP=cc3100cc3200&HQS=cc3200launchpad-oob
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References • [11] J. Pan and W. Tompkins, “A Real-Time QRS Detection Algorithm,” IEEE Transactions on Biomedical Engineering, vol. -32, no. 3,
pp. 230-236, 1985. [Online] Available: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4122029
• [12] MSP430 Wireless Development Tool. [Online] Available: http://www.ti.com/tool/ez430-rf2500
• [13] R. Chang, et al., “High-Precision Real-Time Premature Ventricular Contraction (PVC) Detection System Based on Wavelet Transform,” J Sign Process Syst, vol. 77, no. 3, pp. 289-296, 2013. [Online] Available: http://link.springer.com/article/10.1007%2Fs11265-013-0823-6
• [14] M. Tsipouras, et al., “An arrhythmia classification system based on the RR-interval signal,” Artificial Intelligence in Medicine, vol. 33, no. 3, pp. 237-250, 2005. [Online] Available: http://www.ncbi.nlm.nih.gov/pubmed/15811788
• [15] S. Fokkenrood, et al., “Ventricular Tachycardia/Fibrillation Detection Algorithm for 24/7 Personal Wireless Heart Monitoring,” Pervasive Computing for Quality of Life Enhancement, Lecture Notes in Computer Science, vol. 4541, pp. 110-120, 2007. [Online] Available: http://link.springer.com/chapter/10.1007%2F978-3-540-73035-4_12
• [16] CC2540 SimpleLink Bluetooth Smart Wireless MCU with USB. [Online] Available: http://www.ti.com/product/cc2540
• [17] CC2530 Development Kit. [Online] Available: http://www.ti.com/tool/cc2530dk
• [18] Deaths: Final Data for 2013. [Online] Available: http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_02.pdf
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Detailed Gantt Chart (1) 49
Figure 14. Gantt chart for the MATLAB simulation (PVC algorithm) phase of the project
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Detailed Gantt Chart (2) 50
Figure 15. Gantt chart for the C implementation (PVC algorithm) phase of the project
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Detailed Gantt Chart (3) 51
Figure 16. Gantt chart for the wireless development phase of the project
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Specificity and Sensitivity [8]
• TP (True Positive): detected QRS complex that is present in the signal
• TN (True Negative): data point between QRS complexes that does
not contain a QRS peak
• FP (False Positive): incorrect identification of QRS peak
• FN (False Negative): QRS peak that was not detected by the algorithm
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Memory Requirements
• Sampling rate for ECG signal (MIT-BIH arrhythmia database): 360 Hz
• Number of samples required for 30 seconds of ECG data: 10,800
• Amount of memory required: 21 kB
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Problem Background
• Heart disease is the number one cause of death in the United States
0 2 4 6 8
Heart Disease
Cancer
Chronic lower respiratory diseases
x 100,000
Number of Deaths Per Year
Figure 17. Chart of the three leading causes of death in the United States Source: Centers for Disease Control and Prevention [17]
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Nonfunctional Requirements: Metrics
Objective: The device should be compatible with all patient data in the MIT-BIH database. [3]
Metric:
• Highly compatible: 10 points
• Very compatible: 7.5 points
• Compatible: 5.0 points
• Somewhat compatible: 2.5 points
• Not compatible: 0 points
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Nonfunctional Requirements: Metrics
Objective: The device should be portable.
Metric:
• Very easy to carry around: 10 points
• Easy to carry around: 7.5 points
• Portable: 5.0 points
• Uncomfortable to carry around: 2.5 points
• Difficult to carry around: 0 points
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Nonfunctional Requirements: Metrics
TABLE VI. QUANTITATIVE PERFORMANCE LEVELS FOR REAL-TIME HEART MONITORING [8,
9]
Power Consumption in
24 Hours of
Continuous Use (W)
Price ($)
Value Scaled
1.50 500 10
2.50 600 7.5
3.25 700 5
4.00 800 2.5
4.75 900 0
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Design Evaluation: Morphological Chart
Functions Means
Storing heart data Flash memory RAM
Preprocessing (Filtering/QRS detection)
Pan-Tompkins Wavelet transform Wavelet transform and Pan-Tompkins
PVC detection Wavelet transform Template matching RR-interval
Ventricular tachycardia detection Three or more consecutive PVCs
Three or more consecutive PVCs, heart rate greater
than 100 beats per minute
Statistical analysis
Wireless functionality eZ430-RF2500 CC2540 (Bluetooth) CC3200
TABLE V. MORPHOLOGICAL CHART FOR HEART MONITORING SYSTEM [10,11,12,13,14,15,16]
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Design Evaluation: Design Alternatives
• Total design space: 162 designs
• Two designs analyzed in detail
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Design Evaluation: Design 1
Functions Means Storing heart data Flash memory
Preprocessing (Filtering/QRS detection) Pan-Tompkins
PVC detection RR-interval
Ventricular tachycardia detection Three or more consecutive PVCs and heart rate above 100 beats
per minute
Wireless functionality CC2540 (Bluetooth)
TABLE VIII. FIRST DESIGN FOR HEART MONITORING SYSTEM
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Design Evaluation: Design 2
Functions Means Storing heart data Flash memory
Preprocessing (Filtering/QRS detection) Wavelet transform and Pan-Tompkins
PVC detection Wavelet transform
Ventricular tachycardia detection Three or more consecutive PVCs
Wireless functionality eZ430-RF2500
TABLE IX. SECOND DESIGN FOR HEART MONITORING SYSTEM
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Design Evaluation: NEM
• The two designs were then evaluated against the constraints
and objectives
Constraints Objectives
Real-time ECG signal processing Compatible with all patient data in the MIT-BIH database [3]
On-board signal processing computations
Low-power
Battery-powered functionality Reasonably priced
Portable
TABLE X. CONSTRAINTS AND OBJECTIVES FOR HEART MONITORING SYSTEM
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Design Evaluation: NEM
Design Constraints
Design 1 Design 2
Real-time ECG signal processing + +
On-board signal processing computations + +
Battery-powered functionality + +
+ : Constraint met
TABLE XI. NUMERAL EVALUATION MATRIX
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Design Evaluation: NEM
TABLE XII. NUMERAL EVALUATION MATRIX Design
Objectives Design 1 Design 2
Compatible with all patient data in the MIT-BIH database
7.5 10
Low-power 10 10
Reasonably priced 10 10
Portable 10 10
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Alternative Solution: Hardware
• eZ430-RF2500 (Texas Instruments)
• MSP430F2274 MCU
• CC2500 wireless transceiver
• 32 kB flash memory
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Figure 18. eZ430-RF2500 Development Kit [12]
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Alternative Solution: Software
• PVC detection
• Wavelet transform algorithm [13]
• RR-interval algorithm [14]
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