BME 3113, Dept. of BME Lecture on Introduction to Biosignal Processing

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1 What is a signal? A signal is a varying quantity whose value can be measured and which conveys information. A signal can be simply defined as a function that conveys information. Signals are represented mathematically as functions of one or more independent variables. Example: temperature, T=f(t) It can vary over time We can measure it using a thermometer It conveys information : knowing the temperature outside will inform our decision as to which clothes to wear In digital signal processing system, signal is represented as a sequence of numbers either on a computer or in digital hardware Example: we could store the temperature at various times of the day as a sequence of numbers in an array on a computer: each reading might be a temperature reading in Celsius Examples of Signal Signals are functions of one or more variables (independent variables) that carry/convey information. For example: Electrical signals - voltages and currents in a circuit, power, electric field strength Thermal signals temperature Light signals light intensity, Mechanical signals force, torque, pressure Acoustic signals ---audio or speech signals (analog or digital) such as human voice, a dog s bark, bird s song, Video signals ---intensity variations in an image (e.g. a CAT scan, MRI data) Biological signals ---sequence of bases in a gene Brain signal (Electro-encephalogram or ECG signal) Stock market data Domain and Range of a Signal Domain is the number of independent variable of a signal A signal uses time as the independent variable (i.e., the parameter on the horizontal axis), is said to be in the time domain, or temporal domain Signal uses frequency as the independent variable, resulting in the term, frequency domain. signals that use distance as the independent parameter are said to be in the spatial domain (distance is a measure of space). The independent variable of a signal Most common parameter: Time Others: Distance, x, Number Generic name: sample number Other name of independent variable horizontal axis x-axis, the domain, and the abscissa

Range of a Signal Dependent variable of a signal is the range Dependent variable of a signal Examples: Specific: voltage, light intensity, sound pressure, or an infinite number of other parameters

T=f(t) We say that domain of the signal is one-dimensional Range of the signal is one Black and white photo Domain of the signal is two-dimensional Range of the signal is one Color photo Domain of

or a contracting muscle. The electrical, chemical, and Mechanical activity that occurs during these biological events often produces signals that can be measured and analyzed.

2 Range of a Signal Dependent variable of a signal is the range Dependent variable of a signal Examples: Specific: voltage, light intensity, sound pressure, or an infinite number of other parameters Generic label: amplitude Other name of Dependent variable vertical axis y-axis, range, and ordinate Example: domain and range Temperature Temperature is a function of single real-valued variable, T=f(t) We say that domain of the signal is one-dimensional Range of the signal is one Black and white photo Domain of the signal is two-dimensional Range of the signal is one Color photo Domain of the signal is two-dimensional Range of the signal is three-dimensional Biological Signals or biosiganls Biosignals are space, time, or space time records of a biological event such as a beating heart or a contracting muscle. The electrical, chemical, and Mechanical activity that occurs during these biological events often produces signals that can be measured and analyzed. Contain useful information that can be used to understand the underlying physiological mechanisms of a specific biological event or system, and which may be useful for medical diagnosis. Biomedical signals means the bio-signals which are generated in biological systems only. Biomedical signals are observations of physiological activities of organisms, ranging from gene and protein sequences, to neural and cardiac rhythms, to tissue and organ images. Examples of biomedical signals: ECG (Electrocardiogram) signal, EEG (Electroencephalogram) signal, etc.

Determenistic signals are signals which can be determined and described exactly using mathematics or gaphics. Real world biosignals are never deterministic.

3 Describing biosignals Continuous signals are described by a continuous function s (t) which will show information at any time. *Most biomedical signals are continuous Descrete signals are described by a sequence s (m) which will show information exactly at a particular time. Determenistic signals are signals which can be determined and described exactly using mathematics or gaphics. Real world biosignals are never deterministic. Periodic signals belong to this group and are expressed by s(t)= s(t+nt) n is integer and T is period. Blood pressure could be characterized as a complex periodic signal. Stochastic signals cannot be expressed exactly but only in terms of probabilities. Stationary stochastic processes wil not change in time. The expectations of such a process is time independant. Most of them are non stationary. An example would be EEG (Electroencephalography) ECG signal The Electrocardiogram (ECG) represents the electrical activity of the heart. It is characterized by a number of waves P, QRS, T related to the heart activity. Another wave, called U wave is also present but its importance is not yet identified. EEG Signal The Electroencephalogram (EEG) is a recording of electrical activity originating from the brain. It is recorded on the surface of the scalp using electrodes, thus the signal is retrievable non-invasively. Signal varies in terms of amplitude and frequency Normal frequency range: 0.5Hz to50 Hz. Sources of Biomedical signals ENG: Electroneurogram - Signals from nerves EMG: Electromyogram- Signals from muscles ECG: Electrocardiogram- Signals from Heart ERG: Electroretinogram- Signals from retina of an eye EOG: Electrooculogram- Signals from cornea and retina of an eye EEG: Electroencephalogram- Signals from brain MEG: Magneto encephalogram- Signals from brain using magnetic field USG: Ultra sonogram- Imaging from ultra sound reflection from the internal organs of the body

4 Brief Description of Origin /Sources of Biosignals Bioelectric Signals Generated by nerve and muscle cells as a result of electrochemical changes within and between cells Can be measured with intracellular or extracellular electrodes Examples: ECG, EGG, EEG, and EMG are results of the Bioelectric signals taken from the human body Biomagnetic Signals Different organs (heart, lungs & brain) generate weak magnetic fields Measured from specific physiological activity that is linked to an accompanying electric field from a specific tissue or organ Uses very precise magnetic sensors or SQUID magnetometers (Superconducting Quantum Interference Device) Example: Magnetic field in the head when listening music Magnetoencephalography (MEG) - monitor magnetic activity from the brain Magnetoneurography (MNG) monitor peripheral nerves Magnetogastrography (MGG) monitor gastrointestinal tract Magnetocardiography (MCG) monitor the heart Biochemical Signals Contain information about changes in concentration of various chemical agents in the body Oxygen concentration Determine levels of glucose, lactate and metabolites Provides information about the function of various physiological systems Biomechanical Signals Produced by the mechanical functions of biological signals such as: motion, displacement, tension, force, pressure, and flow Blood pressure measurement Bioacoustic Signals Are special subset of biomechanical signals that involve vibrations (motion) Respiratory system, joints, and muscles generate distinct bioacoustic signals Often measured at the skin using acoustic transducers such as microphones and accelerometers Examples: Biological sounds, such as lung sounds, heart sounds, bowel sounds, and joint sounds, flow of blood in the heart or through vessels, the flow a air in the lungs and airways, in the joints and in the digestive tract etc. Biooptical Signals: Bio-optical signals are the result of the optical functions of the biological systems, occurring naturally or induced by the measurement. Generated by the optical, or light-induced, attributes of biological systems May occur naturally or signals can be introduced to measure a biological parameter using an external light medium Example: human skin tissue Bio-impedance signals: tissue impedance provides information about composition, blood volume and distribution, endocrine activity, etc. Test sinusoidal currents may be injected into the tissue using a frequency range (50KHz-1MHz) to minimize electrode polarizations problems and low

5 current (20MicroA to 20mA) to avoid tissue heating. The voltage drop due to the current and tissue impedance is measured. Bioimpedance signal Example: breath signal Gastric bioimpedance signal Thermal Biosignals: continuous or discrete carry information about the temperature of the body core or temperature distribution on the surface. The temperature measurement reflects physical and biochemical processes proceeded in organism. The measurement is usually performed by a contact method using a variety of thermometers. In special cases it is used 2D thermographic camera. Importance of Biomedical Signal Analysis Diagnosis of diseases Patient monitoring Biomedical research Classifications Since there are many Biosignals it is very hard to find a unique way of classifying them. Classification by existence Permanent biosignals They can exist without an artificial trigger and are available at any time. The source for those Biosignals is already inside the body.

6 Induced biosignals are artifically triggered or induced and last only during the time of excitation. Classification by dynamic nature A static biosignal carries information in its steadystate level which may exhibit relatively slow changes over time. Dynamic biosignals yield extensive changes in the time domain, with dynamic processes conveying the physiological information of interest. Classification by origin Magnetic biosignals These signals include motion and displacement signals, pressure and tension and flow signals, and others. Optic biosignals are the result of optical functions of the biologic system, occurring naturally or induced by the measurement (Blood oxigination) Acoustic biosignals Many physiological phenomina create noise like the flow of blood in the heart or throuhg blood vessels also the flow or air through the airways creates acoustic sounds. Chemical biosignals reflect chemical composition and its temporal changes in body solids, liquids, and gases. Examples are measuring the concentration of various ions and vicinity of a cell by means of specific ion electrodes Thermal Biosignals Temperature measurement shows physical and biochemical processes proceeded in organism.(heat loss, heat absorption)

7 According to signal source Bioelectric Signal Bioacoustics Signal Biomechanical Signal Biochemical Signal Bio-magnetic Signal Bio- optical signal Four stages of Biosignal processing Bandwidths, Amplitude Ranges, and Quantization of Some Frequently Used Biosignals

Biomedical Signals. Signals and Images in Medicine Lecture 1 Dr Nabeel Anwar

Biomedical Signals. Signals and Images in Medicine Lecture 1 Dr Nabeel Anwar Biomedical Signals Signals and Images in Medicine Lecture 1 Dr Nabeel Anwar Books 1. The Scientist and Engineer's Guide to Digital Signal Processing By Steven W. Smith, Ph.D. This book is written in simple