A Biomedical Application of the Polhemus System

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A Biomedical Application of the Polhemus System Powered By Docstoc
					Trends in Bioelectric signal
         analysis




                 By
       Dr. Ajat Shatru Arora
   Principal, DAVIET, Jalandhar
      Professor, EIE, SLIET, Longowal
Biomedical Engineering
Description
 “Biomedical engineering is a discipline
  concerned with the development and
  manufacture of prostheses, medical devices,
  diagnostic devices, drugs,, and other therapies.
  It is a field that combines the expertise of
  engineering with medical needs for the
  progress of health care. It is more concerned
  with biological, safety, and regulatory issues
  than other forms of engineering. It may be
  defined as "The application of engineering
  principles and techniques to the medical field.””
  -.Wikipedia.org
     Challenges in Man-machine
              Interface
 Ethical and human subject protection
  (externally applied energy interacting with
  living tissue)
 Low rage measurement as compared to
  non-medical parameters
 Many crucial parameter are inaccessible
  (cardiac output etc.)
 Inherent variability ( most parameters vary
  with time even under similar conditions)
 Harsh environment (Corrosive chemicals in
  body)
 High risk of micro shock
Major Segments
Biomedical engineering can be segmented in two
   major fields
 – physiological
 and industrial automation.
    The physiological field concentrates more on
   measuring, simulating, and analyzing
   bioelectrical signals as well as modeling body
   parts and processes. The industrial automation
   field focuses on the automation of labs and
   production lines along with the design and
   testing of medical devices.
Sub-disciplines
   Bioinstrumentation
   Biomaterials
   Biomechanics
   Biomedical computing & signal processing
   Cellular, Tissue, and Genetic Engineering
   Clinical Engineering
   Medical Imaging
   Orthopaedic Bioengineering
   Rehabilitation Engineering
   Biometrics
   MEMS
   Minimally invasive surgery
Bioinstrumentation

 The application of electronics and
  measurement principles to develop devices
  used in diagnosis and treatment of disease.
 A medical device is intended for use in:
 the diagnosis of disease or other conditions, or
 in the cure, mitigation, treatment, or
  prevention of disease,
 EXAMPLES are the electrocardiogram, cardiac
  pacemaker, blood pressure measurement,
  hemoglobin oxygen saturation, kidney dialysis,
  and ventilators
Biomaterials
 Describes both living tissue and
  materials used for implantation.
 Choose appropriate material
 Nontoxic, chemically inert, stable,
  and mechanically strong enough to
  withstand the repeated forces of a
  lifetime.
 Metal alloys, ceramics, polymers, and
  composites
 Biomechanics
 Mechanics applied to biological or
  medical problems
 Study of motion, material deformation,
  flow within the body and in devices, and
  transport of chemicals across biological
  and synthetic media and membranes.
 EXAMPLES: artificial heart and
  replacement heart valves, the artificial
  kidney
Biomedical computing & signal
processing
 Computers are becoming increasingly
  important in medical signal
  processing, from the microprocessor
  used to do a variety of small tasks in
  a single-purpose instrument to the
  extensive computing power needed to
  process the large amount of
  information in a medical imaging
  system
Biomolecular engineering
 Design molecules to achieve specific
  biological function
 New drugs or therapeutic strategies
  for treating disease.
 Cell biology, genetics, human
  physiology, chemistry
 EXAMPLES: targeted drug delivery;
  directed evolution of inhibitors of viral
  growth
 Micro-electromechanical
 systems (MEMS)
 Microtechology and micro scale
  phenomena is an emerging area of
  research in biomedical engineering
 Many of life's fundamental processes
  take place on the micro scale
 We can engineer systems at the cellular
  scale to provide new tools for the study
  of biological processes and
  miniaturization of many devices,
  instruments and processes
 Minimally invasive medicine &
 surgery
 Uses technology to reduce the debilitating
  nature of some medical treatments.
 Minimally invasive surgery using
  advanced imaging techniques that
  precisely locate and diagnose problems
 Virtual reality systems that immerse
  clinicians directly into the procedure
  reduce the invasiveness of surgical
  interventions
Medical imaging
 Medical/Biomedical Imaging is a major
  segment of Medical Devices. This area deals
  with enabling clinicians to directly or indirectly
  "view" things not visible in plain sight (such as
  due to their size, and/or location). This can
  involve utilizing ultrasound, magnetism, UV,
  other radiology, and other means.
Medical imaging
Imaging technologies are often essential to
  medical diagnosis, and are typically the most
  complex equipment found in a hospital
  including:
 Magnetic resonance imaging (MRI)
 Projection Radiography such as X-rays and CT
  scans
 Tomography
 Ultrasound
 Electron Microscopy
Medical Imaging
Computers are applied in medical imaging to:

   construct an image from measurements.

   identify  quantitative    parameters   of
    clinical  interest    such   as   certain
    distances, densities, etc

   improve    image   quality by  image
    processing,       compensate      for
    imperfections in the image-generating
    system, and reduce noise
Medical Imaging
  store and retrieve images

  reduce the amount of storage required
   and the transmission time via image
   compression techniques

  indirectly improve patient cares
Implants
 An implant is a kind of medical device made to
  replace and act as a missing biological
  structure (as compared with a transplant,
  which indicates transplanted biomedical
  tissue). The surface of implants that contact
  the body might be made of a biomedical
  material such as titanium, silicone or apatite
  depending on what is the most functional. In
  some cases implants contain electronics e.g.
  artificial pacemaker and cochlear implants.
  Some implants are bioactive, such as
  subcutaneous drug delivery devices in the form
  of implantable pills or drug-eluting stents.
Bioelectric Signals
Bioelectrical signal measurements from the
heart (electrocardiogram/ECG);
muscles (electromyograph/EMG);
skin (Galvanic skin response/GSR);
scalp (electroencephalograph/EEG);
eyes (electrooculogram/EOG
These bioelectrical signals are typically very small in amplitude and
   require amplification to accurately record, display and analyze
   the signals. Depending on the hardware and software used, the
   biological amplifier serves not only to amplify the signal but
   also to apply a range of filtering options for the removal of
    unwanted signal artifacts.
Importance of Biosignals
 Diagnosis



 Patient monitoring



 Biomedical research
Characteristics of
Biosignals
 Often hidden in a background of
  other signals and noise components.

 Generated by highly complex and
  dynamic biological processes with
  parameters usually more than a few
  and varying continuously
Issues in biosignal acquisition
 Signal Conditioning
Amplification,
Isolation,
Filtering
 Sampling
Selection of sampling rate
 Selection of Software and Hardware
Signal Conditioning
 Amplification
 Amplification    is  the    set   of
  techniques used to boost a signal's
  strength to better match the
  analog-to-digital converter (ADC)
  range
 Increases      the    measurement
  resolution and sensitivity.
 Improves the signal-to-noise ratio.
Isolation
 Isolated signal conditioning devices pass the signal
  from its source to the measurement device without
  a physical connection.



 Benefits of isolation include:
  a). Protection for expensive equipment, the user,
       and data from transient voltages
  b). Improved noise immunity
   c).Ground loop removal
   d).Increased common-mode voltage rejection
Isolation Techniques



                   Inductive Coupling




Optical Coupling
                                        Capacitive Coupling
Multiplexing




 Multiplexing is Transmission of multiple signals over a
                     single medium
Filtering
 Filtering is the process to reject unwanted
  noise within a certain frequency range.

 All data acquisition applications are
  subject to some level of 50 or 60 Hz noise
  picked up from power lines or machinery.

 Most signal conditioners include the filters
  specifically designed to provide maximum
  rejection of 50 to 60 Hz noise.
Nyquist Sampling Theorem
 To reconstruct an analog signal waveform
  without error from sample point taken at
  equal   time    intervals, the  sampling
  frequency (Fs) must be greater than or
  equal to twice the highest frequency(Fm)
  component in the analog signal or
  bandwidth or B.

                        Fs ≥ 2Fm or B
 Nyquist Rate
Sampling of Analog Signal
Sampled Analog Signal




        When Fs ≥ 2Fm
DAQ Hardware
 DAQ hardware acts as the interface
  between the computer and the outside
  world.
 It digitizes incoming analog signals so that
  the computer can interpret them
 DAQ hardware includes
  Analog I/O, Digital I/O
  Counters/Timers
  Multifunctional:- combination of analog,
  digital, and counter operations on a single
  device.
Driver Software
 Basic driver software allows us to:
    a). Bring data on to and get data off of the
         board.
    b). Control the rate at which data is acquired.
     c). Integrate the DAQ hardware with computer
         resources such as processor interrupts,
         DMA and memory.
    d). Integrate the DAQ hardware with signal
          conditioning hardware.
    e). Access multiple subsystems on a given
         DAQ.
    f). Access multiple DAQ boards
Biosignal Processing
 In order to derive the required information
  from the bio signals:

  -Disturbance should be filtered out

  -The amount of data should be reduced by
  discriminating only the most significant
  ones related with the required information
Stages of Biosignal
Processing
  Signal acquisition
  Transformation and reduction of the
   signals
  Computation of signal parameters that
   are diagnostically significant
  Interpretation or classification of the
   signals
Stages of Biosignal
Processing
Signal transformation
 Noise component:
   due to the electronics in the measuring
    device,
   artifacts   related  to   the  patient’s
    movements, or
   other    background   signals  recorded
    simultaneously

 More data than actually needed to derive
  parameters offering semantic information
Stages of Biosignal
Processing
Parameter selection
 Usually, relevant information is not
  the direct result of a sample or
  recording of a signal.
 Parameters bearing resemblance to
  the signs and symptoms that are
  used    to   make     diagnosis are
  extracted from the signal.
Stages of Biosignal
Processing
Signal classification
 the interpretation stage
 derived     features of selected
  relevant     parameters used for
  human      or    computer-assisted
  decision     making by means of
  decision   support methods
Application Areas of
Biosignal Analysis
 in ICUs
   integrating signals from multiple sources
   presenting information in the most
    appropriate form
   interpreting variations over prolonged
    time periods
   learning and recognizing profiles
   triggering “intelligent” alarms
Application Areas of
Biosignal Analysis
 Biosignals offer parameters that
  support     medical     decision
  making and trend analysis.

 Bio signal analysis techniques
  help     to     extract    these
  parameters accurately, analyze
  and interpret them objectively.
  Biomedical Instrumentation
 Biomedical instrumentation contributes in
                following ways
 Accurate measurement
 Long Term monitoring
 Understanding, Diagnosis and
  management of disease
 Research
Biometrics
 Automated methods of verifying
  the identity of a person based on
  physiological behavioral
  characteristics
Types of Biometrics
Biometric System
Salient Features of
Biometrics
 Biometric     makes      use     of    those
  characteristics, which are universal, that
  is, found in each and every human being.
  For instance, fingerprints, voice, face print
  and so on.
 Distinct body odours, handwriting skills and
  other attributes are being included in
  biometrics       analysis,     as      these
  characteristics don’t change with growing
  age of individuals.
Salient Features of
Biometrics
 The characteristics involved in biometrics
  analysis can’t be stolen or copied. So, you
  can’t expect anyone to steal your face or
  eye vessels to use them for illegitimate
  access.
 Interestingly, even if someone is able to
  replicate your fingerprints and use it for
  biometrics analysis, these systems can
  instantly differentiate between a human
  body and a plastic cast, on the basis of
  body heat, temperature, blood flow and so
  on.
Applications of Biometrics
 Biometric systems can be used as physical
  access granting systems. The biometric
  identifier serves as the key to open doors
  to buildings and vehicles or to gain access
  to computers and other devices.
 Secondly, biometric systems can be used
  to establish entitlement to services and
  rights that are restricted to a certain group
  of individuals. In this case, the service or
  right in question is only provided or granted
  to individuals that are identified as
Applications of Biometrics
belonging to the group of recipients and rights
   holders. Examples include social services
   (prevention of welfare fraud), the right to
   vote (voter registration), right of abode and
   work (immigration), and all kinds of private
   membership services or contractual rights.
 Biometric systems can be used for the
   recording and association of facts. Such
   uses    include     employee       attendance
   monitoring, surveillance of public places,
   forensics, archiving and retrieving personal
   information such as health records.
                  Applications of EMG




Bio-Electric Signal                     48
Processing Lab
              Applications of EMG in
                   Ergonomics


          ► ANALYSIS OF DESIGN.

          ► RISK PREVENTION.

          ► ERGONOMIC DESIGN.

          ► PRODUCT CERTIFICATION.


Bio-Electric Signal                    49
Processing Lab
              Applications of EMG in
                   Ergonomics




Bio-Electric Signal                    50
Processing Lab
              Applications of EMG in
                   Ergonomics




Bio-Electric Signal                    51
Processing Lab
Applications of EMG in Medical
           Research

 ►EMG helps to
   improve the
   medical
   research
   studies by
   detecting
   activity levels in
   muscles and
   quickly
   identifying
   muscle
   dysfunction.
Bio-Electric Signal          52
Processing Lab
Applications of EMG in Medical
           Research

         ►FUNCTIONAL NEUROLOGY

         ►GAIT AND POSTURE ANALYSIS

         ►PROSTHETIC DEVICES

         ►ORTHOPEDICS

         ►SURGERY


Bio-Electric Signal                   53
Processing Lab
Applications of EMG in Medical
           Research
                      (FUNCTIONAL NEUROLOGY)




Bio-Electric Signal                            54
Processing Lab
                      Applications of EMG in
                        Medical Research
                      (GAIT AND POSTURE ANALYSIS)




Bio-Electric Signal                                 55
Processing Lab
        EMG For A Robotic Hand
 Figure shows the
  highly integrated
  approach to to use
  EMG recording of
  the human lower
  arm in order to
  control the opening
  and closing of
  three fingers of the
  hand.


Bio-Electric Signal              56
Processing Lab
             EMG Signal To Grasp
                  Objects
 The EMG interface
  can be well used to
  grasp objects.
 Since no force
  feedback is
  possible using this
  interface, the
  patient can use her
  visual feedback to
  interact with the
  object via the
  prosthetic hand.

Bio-Electric Signal                57
Processing Lab
               Applications of EMG in
                 Medical Research
                      (PROSTHETIC DEVICES)




Bio-Electric Signal                          58
Processing Lab
      EMG For Repetitive Strain
               Injury
 Electromyography
  (EMG) is commonly
  used for investigating
  musculoskeletal
  disorders
 To study muscle
  activation at the motor
  unit level through
  multi-channel EMG in
  order to develop
  diagnosis and training
  methods for muscle
  activation
  impairments.


Bio-Electric Signal               59
Processing Lab
                  EMG Biofeedback :
                 Treatment Of Tension
                      Headache
 Tension headache
  is generally
  described as a
  bilateral dull ache,
  pressure or cap-
  like pain that is
  usually located in
  the forehead, neck
  and shoulder
  regions.


Bio-Electric Signal                     60
Processing Lab
  Applications of EMG in Sports
             Science
                      (BIOMECHANICS)




      ► Biomechanics is
        the scientific
        study of forces
        and the effects of
        those forces on
        and within the
        human body.


Bio-Electric Signal                    61
Processing Lab
  Applications of EMG in Sports
             Science
                      (MOVEMENT ANALYSIS)




 ► Monitor how
   muscles are
   utilized during
   movement.




Bio-Electric Signal                         62
Processing Lab
Micro/Nano applied to BME
     Micro/Nano applied to BME
Balloon Angioplasty

Stent Procedure




                                                                   Stent Procedure
and




                                                                   Balloon Angioplasty
                      http://www.med.umich.edu/1libr/aha/aha_dil   http://www.mdmercy.com/vascular/discoveri
                      ation_art.htm                                es/balloon_stent_gif_big.html
Examples
Automation in Biomedical




            SLIET, Longowal
Electroencephalography (EEG)
Interpretation and Automated
Anesthesia Delivery
 Aspect Medical Systems (Natick, MA) has
  developed monitors to assess the depth of the
  anesthesia state based on the statistically
  derived Bispectral Index (BIS) reflecting the
  level of sedation. Community Hospitals
  Indianapolis is successfully employing the BIS
  monitor to improve the administration of
  anesthesia during surgery and has found that
  this technology contributes to improved patient
  care and reduced costs. The Automated BIS
  Controller, in development at the University of
  Pittsburgh Medical Center, controls the rate of
  anesthetic drug infusion using the BIS as a
  feedback control.
Fuzzy Support Vector Machine for EMG
Pattern Recognition and Myoelectrical
Prosthesis Control
 For the optional control to the trans-femoral
  prosthesis and natural gait, an ongoing investigation
  of lower limb prosthesis model with myoelectrical
  control was presented. In this research, the surface
  electromyographic signals of lower limb were
  extracted to be switch signal, and translate into
  movement information. Considering every muscle’s
  different physiologic tendency, fuzzy support vector
  regression method was applied to establish an
  intelligent black box that can interpret the
  physiological signals to accurate information of knee
  joint angle. It achieves a comparable or better
  performance than other methods, and provides a
  more native gait to the prosthesis user.

                       SLIET, Longowal
QUESTIONS ?
Thanks

				
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