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Biomedical Instrumentation, ,Measurement and Design
ELEC4623/ELEC9734: Semester 2, 2009
Dr Stephen RedmondSchool of Electrical Engineering & TelecommunicationsEmail: s redmond@unsw edu auEmail: [email protected]: 9385 6101Rm: 458, ELECENG (G17)
Session 2, 2009 ELEC4623/ELEC9734 1
Course Outline
12 x 2 hour lectures5 x 3 hour laboratories (only three labs are assessed)
Laboratories (3 lab reports) 25%Assignment 10%Project seminar 10%three labs are assessed)
Project presentation in final weeks
Project seminar 10%Final examination 55%
Course SyllabusWeek Topic
1 Introduction & origin of biopotentials
2 Bioelectrodes and tissue equivalent circuits
3 Principles and operation of basic transducers and sensors3 Principles and operation of basic transducers and sensors
4 Characteristics of biological and instrumentation noise
5 Practical biopotential amplifier design and multilead ECG systems
6 Design testing and analysis of a high quality isolated biopotential amplifier6 Design, testing and analysis of a high quality isolated biopotential amplifier
7 Biological signal processing – filters
8 Statistical algorithms for automated signal detection and analysis
9 Circulatory system and the measurement of blood pressure and flow
10 The measurement of respiratory flows
11 Safety and performance standards (ASA, IEC and FDA) for medical instrumentation
12 Project presentations
13 Project presentations
Biomedical Instrumentation, Measurement and DesignELEC4623/ELEC9734/
Lecture 1Introduction to Biomedical Instrumentation and Physiological Measurement
Importance of physiological measurements in clinical medicine
Modern medicine is characterised by increasing application of scientific method to medicineMeasurement is the essence of the scientific methodMeasurement is the essence of the scientific methodPhysiological monitoring now multi-billion dollar industry (Hewlett Packard, Siemens, Philips and more)
Philips HealthcareClinical Specialties+ Anesthesiology
Home Healthcare+ Sleep Therapy
Mammography+ Analog Mammography + Digital Mammography + Computed Mammography
Mobile C-arms
Radiation Oncology+ Radiation Treatment Simulation + Radiation Treatment Planning
Resuscitationd l f b ll+ Anesthesiology
+ Cardiology + Oncology + Orthopedics + Surgery
Computed Tomography
+ Sleep Therapy + Home Respiratory + Lifeline Medical Alert + Remote Cardiac Services + HeartStart Home Defibrillator + Telehealth
+ C-arm with Flat Detector + C-arms with Image Intensifier
Monitoring+ Patient Monitors + Fetal and Maternal Monitors
+ Automated External Defibrillators + Advanced Life Support Products + AED Program Management + Data Management Solutions + Supplies & Accessories
SolutionsCo puted o og ap y+ Scanners + Workflow Solutions
Diagnostic ECG+ ECG Management + Holter Monitoring
Hospital Respiratory+ Noninvasive ventilation + Acute care ventilation + Patient Interfaces + Pre-hospital CPAP
+ Clinical Decision Support + Clinical Information Systems + Surveillance and Networking + Clinical Measurements + Remote Critical Care
N l M di i
Solutions+ Ambient Experience + BioShield for research + Cath Lab Experience + Discovery to Treatment + DoseWise radiation management + eICU Program g
+ PageWriter Cardiographs + Stress-Test Systems
Fluoroscopy+ Interventional Fluoroscopy + Diagnostic Fluoroscopy
Interventional X-ray+ Interventional Vascular Surgery + Interventional Cardiac Surgery + Electrophysiology + Interventional Cardiology + Interventional Radiology
I i l N di l
Nuclear Medicine+ SPECT/CT + PET/CT + Workflow Solutions
Preclinical Imaging+ MOSAIC HP
g+ Healthcare Consulting + Hospital-Acquired Infections + Remote services
Ultrasound+ Cardiology
Healthcare Informatics+ Cardiology Informatics + Enterprise Imaging Informatics + Applications & Workstations + Acute Care Informatics
ICU I f ti
+ Interventional Neuroradiology
Magnetic Resonance+ Systems + Elite Clinical Solutions + Options & Upgrades
+ MOSAIC HP + NanoSPECT/CT + IMALYTICS Workspace
Radiography+ Analog Radiography + Digital Radiography
+ Emergency Medicine + General Imaging + Regional Anesthesia + Vascular + Women’s Healthcare + Transducers
+ ICU Informatics + Digital Radiography + Computed Radiography + Mobile Radiography
General properties of medical instrumentation systems
Medical instruments monitor human tissue (loosely speaking!)Demand high level of safety, performance and qualityCost and complexityp y
Measurand is usually an accessible signal or quantity, e.g.Biopotentials (neural or neuromuscular)TemperaturePressureFlowDisplacementDisplacementImpedanceChemical composition
Examples of physiological measurands:
Electrocardiography (ECG)Electromyography (EMG)Electroencephalography (EEG)Electroencephalography (EEG)Phonocardiography (PCG)Blood pressureBlood flowBlood flowRespiratory pressures, flows and volumesBlood gases, PO2, PCO2Bl d HBlood pH
Essential elements of medical instruments
Great variety of methodsExternal electrodes (e.g. ECG)Application of external energy (e g X-ray ultrasound)Application of external energy (e.g. X ray, ultrasound)Collection of gas, liquid or tissue samples with analysis of chemical composition
Variety of signal content24 hour circadian rhythm (blood pressure) Bandwidth up to ~300 Hz (ECG) or 3-10 KHz (EMG and nerve potentials)Bi t ti l i V ( i lt) 0 300 HBiopotentials in μV (microvolt) range, pressures 0-300 mmHg
In design, must consider effects of Noise (ambient and generated)Temperature humidity pHTemperature, humidity, pHPerturbations caused by emotional or physical arousal
Sensors/Transducers
Conversion of physical quantities (e.g. flow, pressure) to electrical signals IdeallyIdeally
Minimally invasive or noninvasiveRespond only to measurand and not noiseProvide minimum interference to process being measuredp g
Sensing unit + converters e.g. in microphone: diaphragm (sensing element) responds to pressure by changing displacement, conversion of displacement to l t i l i l i t ll d i l telectrical signal requires externally powered conversion element
(such as strain gauge, bridge circuit)Microelectronic sensors revolutionise industry
Low costLow costSmall sizeGreater reliability and improved performance
Signal Conditioning
Transducers rarely provide a signal suitable directly for ADC (analog to digital conversion)
Must firstAmplify signal to appropriate level (fixed or variable gain)Filter signal with low pass, high pass, band pass or notch filtersFilter signal with low pass, high pass, band pass or notch filters
Signal processing in modern instruments is usually a combination of hardware and software
Analog filter in hardware: expensive in terms of cost and real estate, but necessary sometimesDigital filter in software: “free” and more flexible
Control and Feedback
May be required to adjust properties of the Sensor
PositionPositionContact force
ConditionerGainGainFilter properties
Display, storage and transmissionManual or automaticManual or automatic
Performance standards
Equipment from different manufacturers must meet certain performance criteriaStandards usually set by industry bodies:y y y
American Heart Association (AHA)American National Standards Institute (ANSI)Association for the Advancement of Medical Instrumentation (AAMI)(AAMI)International Electrotechnical Commission (IEC)
Certification comes from local bodies e.g.Federal Drug Administration (FDA USA)Federal Drug Administration (FDA USA)Therapeutic Goods Administration (TGA Australia)
Differences between USA and Europe standardsAustralia tends to follow EuropeAustralia tends to follow Europe
Electrical safety
Hospital equipment often used in presence of explosive anaesthetics such as etherMacroshock hazardsMacroshock hazards
defibrillation (~3000V)electrical faults (hot wire to ground)
Mi h k h dMicroshock hazards leakage currents (from direct cardiac electrical connections)
Rigorous safety standards apply to electromedical equipmentIEC601 series
IEC safety standards for ECG equipment
Patient leakage currents 10uA. Under single fault conditions < 50uA
Earth leakage currents500uA from mains to ground across insulation under normal conditionsnormal conditions
Enclosure current100uA from any part accessible to the operator or patientpatient
Isolation>3500 Vac between the patient and the mains inlet to the de icethe device
IEC Symbols for
A) body protected (BF) andA) body protected (BF) and B) cardiac protected (CF) equipment able to withstand defibrillation
Design example: 12 lead ECG
PCs often used as medical instrumentsLow costEase of programmingp g gNumber crunching capacity (DSP)Variety of third party products for support of functionsGraphical user interface (GUI)
Require an interface cardInternal
Work with desktops but not with notebooksSerial interface
RS-232 (old), USB or Firewire (IEEE1394)USB excellent choice for modern equipment
PC-ECG design example
PC-ECG design example
Defibrillation protection and RF filteringPrevents device from damage by high voltage during defibrillationBl k t i l di f (RF) i t fBlocks out wireless radio frequency (RF) interference
Driven right leg circuitReduces common mode noise (mains frequency) by ~50dB by driven right legdriven right leg
Shield driveReduces capacitance of cable shields thus improving common mode rejection ratio (CMRR) and high frequency performancemode rejection ratio (CMRR) and high frequency performance
PC-ECG design example
Differential amplifiersProvide high CMRR with tolerance to DC offsets (± 300mV)
High pass filter stageHigh pass filter stageRemoves baseline wander (fc = 0.5 Hz or 0.05 Hz)
Variable gain stageComputer controlled gain of 20 – 100Computer controlled gain of 20 100
Low pass filterBessel filter (or similar) for anti-aliasing (fc = 40, 100 or 150 Hz)Software controlSoftware control
PC-ECG design example
Analogue to digital converter (ADC)12 bit range, 8 channel
IsolationIsolationFor patient safety, isolates patient circuit from mains groundOptical method of isolating digital data and control lines Transformer isolation for powerTransformer isolation for power
PC bus interfaceFor communication with host PC and control of parameters (e.g. amplifier gain, filter cutoff)
Data display, printing and storageUsing normal PC resources
Data reduction and compression
12 lead ECG typically sampled at 500 or 1000 Hz10 second records require 80Kbytes storage
f h d h l h d d dLess of an issue these days with large hard drives and storage disks Still a big problem with long recordings (24 hour)Various data compression schemes available for ECG (such as turning point algorithm)
but quality may (will) be affected
Programming languages
MATLABExcellent for initial signal processing developmentC t C++ d f d l tCan generate C++ code for deployment
Visual BasicEase of programming for rapid development
C++Generally language of choice for final applicationObject orientedDSP libraries available
Database design
Relational databases commonly usedData and relationships between data are represented by a series of tablestablesEach column is known as a fieldEach row is known as a record
Data retrieval occurs by a programData retrieval occurs by a programStructured Query Language (SQL) is the most common language used
A sample relational database
Pat_code Pat_Name Pat_CityTable ‘patient’
0001 Jack Smith Brisbane
0002 John Doe Sydney
0003 Susan Smith Melbourne0003 Susan Smith Melbourne
Table ‘procedures’
Proc_code Proc_Date Proc_Description Proc_Blob0001 12/07/2005 12 lead ECG “binary data”
0002 05/06/2005 3 l d ECG “bi d t ”0002 05/06/2005 3 lead ECG “binary data”
0003 01/12/2004 Spirometry “binary data”
Automated interpretation of ECGs
Alternative to cardiologist (human) interpretationAccuracy comparable to cardiologists
fTwo formsRule-based decision logic (If-then)
Mimics decision process used by cardiologistC b d d b hCan be understood by humans
Statistical pattern recognition methodArtificial Neural Networks, Support Vector Machine, Regression Tree, and (many) moreand (many) moreMany alternatives these days with at least equal performance and fast trainingBlack box models (can’t see inside the box)
Automated interpretation of ECGs - Procedure
Preliminary signal processing/noise removalFind reference point (usually R wave)
f l d f ( lDetermine if valid waveform (e.g. cross correlation to some reference wave)Average all valid waveforms over some period (e.g. 10
d )seconds)Extract features from average waveformUse extracted features in model to determine an output (e.g. left bundle branch block)
Characteristic ECG beat with parameters measured in HP automated ECG interpretation
Reference
Adapted from Physiological Monitoring, Branko Celler, chapter 17 from “Health Informatics – an Overview”, edited by E. Hovenga, M Kidd B Cesnik Churchill Livingstone Melbourne 1996M. Kidd, B. Cesnik. Churchill Livingstone. Melbourne. 1996.
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