trends in bioelectric signal analysis by dr. ajat shatru arora principal, daviet, jalandhar...
TRANSCRIPT
Trends in Bioelectric signal analysis
ByDr. Ajat Shatru Arora
Principal, DAVIET, JalandharProfessor, 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 ImagingComputers 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 theheart (electrocardiogram/ECG); muscles (electromyograph/EMG); skin (Galvanic skin response/GSR); scalp (electroencephalograph/EEG); eyes (electrooculogram/EOGThese 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 ConditioningAmplification,Isolation,Filtering SamplingSelection 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 ProcessingSignal 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 Biometricsbelonging 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.
Bio-Electric Signal Processing Lab
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Applications of EMG
Bio-Electric Signal Processing Lab
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Applications of EMG in Ergonomics
► ANALYSIS OF DESIGN.
► RISK PREVENTION.
► ERGONOMIC DESIGN.
► PRODUCT CERTIFICATION.
Bio-Electric Signal Processing Lab
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Applications of EMG in Ergonomics
Bio-Electric Signal Processing Lab
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Applications of EMG in Ergonomics
Bio-Electric Signal Processing Lab
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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 Processing Lab
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Applications of EMG in Medical Research
►FUNCTIONAL NEUROLOGY
►GAIT AND POSTURE ANALYSIS
►PROSTHETIC DEVICES
►ORTHOPEDICS
►SURGERY
Bio-Electric Signal Processing Lab
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Applications of EMG in Medical Research
(FUNCTIONAL NEUROLOGY)
Bio-Electric Signal Processing Lab
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Applications of EMG in Medical Research
(GAIT AND POSTURE ANALYSIS)
Bio-Electric Signal Processing Lab
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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 Processing Lab
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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 Processing Lab
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Applications of EMG in Medical Research
(PROSTHETIC DEVICES)
Bio-Electric Signal Processing Lab
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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 Processing Lab
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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 Processing Lab
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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 Processing Lab
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Applications of EMG in Sports Science
(MOVEMENT ANALYSIS)
► Monitor how muscles are utilized during movement.
Micro/Nano applied to BME
Micro/Nano applied to BME
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Balloon Angioplasty
Examples
SLIET, Longowal
Automation in Biomedical
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.
SLIET, Longowal
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.
QUESTIONS ?
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