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Introduction to Biomedical Signal Processing

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Title: Introduction to Biomedical Signal Processing


1
Introduction to Biomedical Signal Processing
  • 1st practice
  • Medical InformaticsBiomedical Signal Processing
  • TAMUS, Zoltán Ádám
  • zoltanadam_tamus_at_yahoo.com

2
The Nature of Biomedical Signals
  • The living organism made up of many component
    system and each system is made up of several
    subsystems that carry on many physiological
    processes.
  • Most physiological processes are accompanied by
    or manifest themselves as signals that reflect
    their nature and activities.
  • Signals biochemical, electrical, physical

3
The Nature of Biomedical Signals
  • Diseases or defects in a biological system cause
    alteration its normal physiological processes,
    leading to pathological processes.
  • A pathological process is typicaaly associated
    with signals that are different in some respects
    from the corresponding normal signals.

4
Sensing of Biological Signals
  • The signals can be sensed by qualitative or
    quantitative manner.
  • Measurement
  • Scalar
  • Function of time
  • discrete xn
  • continuous x(f)
  • digital
  • Multivariant vector

5
Objectives of Biomedical Signal Analysis
  • Information gathering
  • measurement of phenomena to interpret a system
  • Diagnosis
  • detection of malfunction, pathology, or
    abnormality
  • Monitoring
  • obtaining continuous or periodic information
    about a system

6
Objectives of Biomedical Signal Analysis
  • Therapy and control
  • Modification of the behaviour of system based
    upon the outcome of the activities listed above
    to ensure a specific result
  • Evaluation
  • Objective analysis to determinate the ability to
    meet functional requirements, obtain a proof of
    performance, perform quality control, or qualify
    the effect of treatment

7
Signal Acqusition Procedures
  • Invasive
  • placement of transducers or other devices inside
    the body
  • Noninvasive
  • minimize risk
  • surface electrodes
  • Active
  • require external stimuli
  • Passive
  • not require external stimuli

8
The Components of Human-Instrument System
  • The subject or patient
  • Stimulus or procedure of activity
  • Transducers
  • electrodes, sensors
  • Signal-conditioning equipment
  • amplifier, filter
  • Display equipment
  • oscilloscopes, strip charts, computer monitors
    etc.

9
The Components of Human-Instrument System
  • Recording, data processing, and transmission
    equipment
  • Analog instrumentation tape recorders,
    analog-to-digital converters (ADCs),
    digital-to-analog converters (DACs), digital
    tapes, CDs, computers, telemetry systems etc.
  • Control devices
  • Power supply, isolation equipment, patient
    intervention systems

10
Properties of Biomedical Instruments
  • Isolation of the subject or patient
  • Range of operation
  • The minimum to maximum values of the signal being
    measured.
  • Sensitivity
  • the smallest signal variation measurable
    (resolution)
  • Linearity
  • Hysteresis
  • a lag in measurement due to the direction of
    variation of the entity being measured.

11
Properties of Biomedical Instruments
  • Frequency response
  • represents of the variation of the sensitivity
    with frequency
  • Stability
  • an unstable system could preclude repeatability
    and consistency of measurements
  • Signal to noise Ratio (SNR)
  • noises could compromise the quality of the signal
    being acquired.
  • Accuracy

12
Difficulties of Biomedical Signal Processing
  • Accessibility of the variables to measurement
  • Variability of the signal source
  • Inter-relationship and interactions among
    physiological systems
  • Effect of the instrumentation or procedure on the
    system
  • Physiological artifacts and interference
  • Energy limitation
  • Patient safety

13
Computer Aided Diagnosis and Therapy
Signal data acquisition
Patient
Amplifiers filters
A/D conversion
Transducers
Isolation
CAD T
Pattern recognition, classification, diagnosis
decision
Analysis of events of waves feature extraction
Filtering to remove artifacts
Detection of events components
Physician
Signal analysis
Signal processing
14
Why the CAD Systems are Used?
  • Humans are highy skilled and fast in analysis of
    visual patterns and waveforms, but are slow in
    arithmetic operations with large numbers of
    values.
  • Humans could be affected by fatigue, boredom and
    enviromental factors. Computers are inanimate but
    mathematically accurate and consistent machines
    can be designed to perform repetitive tasks.

15
Why the CAD Systems are Used?
  • Analysis by humans is usually subjective and
    qualitative.
  • Analysis by humans is subject inter-observers and
    intra-observers variation with time.
  • The biomedical signals are fairly slow therefore
    these can be analised on-line by low-end
    computers.
  • Off-line analysis by the stored data.

16
Reference
  • Rangaraj M. Rangayyan Biomedical Signal
    Analysis, IEEE Press/Wiley, New York, NY, 2002.
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