CN113470130A - Apparatus and method for extracting components related to specific physiological phenomena and reconstructing EIT data - Google Patents
Apparatus and method for extracting components related to specific physiological phenomena and reconstructing EIT data Download PDFInfo
- Publication number
- CN113470130A CN113470130A CN202010244158.9A CN202010244158A CN113470130A CN 113470130 A CN113470130 A CN 113470130A CN 202010244158 A CN202010244158 A CN 202010244158A CN 113470130 A CN113470130 A CN 113470130A
- Authority
- CN
- China
- Prior art keywords
- data
- eit
- electrodes
- electrode
- specific
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 59
- 238000005259 measurement Methods 0.000 claims abstract description 92
- 238000003384 imaging method Methods 0.000 claims abstract description 10
- 230000008859 change Effects 0.000 claims description 38
- 238000012880 independent component analysis Methods 0.000 claims description 27
- 230000017531 blood circulation Effects 0.000 claims description 22
- 238000000513 principal component analysis Methods 0.000 claims description 22
- 239000000284 extract Substances 0.000 claims description 13
- 210000004072 lung Anatomy 0.000 claims description 11
- 210000002345 respiratory system Anatomy 0.000 claims description 6
- 238000002593 electrical impedance tomography Methods 0.000 claims 31
- 230000000241 respiratory effect Effects 0.000 description 10
- 238000002347 injection Methods 0.000 description 9
- 239000007924 injection Substances 0.000 description 9
- 210000000038 chest Anatomy 0.000 description 5
- 239000002131 composite material Substances 0.000 description 5
- 239000004020 conductor Substances 0.000 description 5
- 208000031481 Pathologic Constriction Diseases 0.000 description 4
- 230000029058 respiratory gaseous exchange Effects 0.000 description 4
- 208000037804 stenosis Diseases 0.000 description 4
- 230000036262 stenosis Effects 0.000 description 4
- 210000001715 carotid artery Anatomy 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 210000000115 thoracic cavity Anatomy 0.000 description 3
- 208000008589 Obesity Diseases 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 210000004373 mandible Anatomy 0.000 description 2
- 235000020824 obesity Nutrition 0.000 description 2
- 206010067775 Upper airway obstruction Diseases 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000000205 computational method Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 239000013013 elastic material Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000005247 gettering Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000036387 respiratory rate Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/053—Measuring electrical impedance or conductance of a portion of the body
- A61B5/0536—Impedance imaging, e.g. by tomography
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2134—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on separation criteria, e.g. independent component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
Abstract
Disclosed herein is an apparatus and method for extracting components associated with a specific physiological phenomenon based on measurement of electrical characteristics, and reconstructing electrical impedance imaging (EIT) data by using the extracted components. According to an embodiment of the present disclosure, an apparatus for extracting a specific component and reconstructing data based on an EIT may include: an electrode unit including a plurality of electrodes to be attached to a measurement site of a subject; an electrical characteristic measurer configured to measure a plurality of electrical characteristics of the object according to elapsed time through the attached plurality of electrodes; an EIT data generator configured to generate EIT data based on the measured changes in the plurality of electrical characteristics; a pattern extractor configured to extract specific pattern data associated with a specific component caused by a specific physiological phenomenon of the subject from the generated EIT data; and an EIT data reconstructor configured to reconstruct the generated EIT data into EIT data corresponding to the specific component based on the extracted specific pattern data.
Description
Technical Field
The present disclosure relates to a technical concept of extracting components associated with a specific physiological phenomenon based on measurement of electrical characteristics and reconstructing electrical impedance imaging (EIT) data by using the extracted components, and in particular, to an apparatus and method for extracting only components of a specific physiological phenomenon from a composite signal affected by a change in internal electrical characteristics of a human body according to a plurality of physiological phenomena based on EIT and reconstructing EIT data using the extracted components.
Background
When measuring voltage after injecting current into a human body or similar volume conductor or measuring current after injecting voltage into a human body or similar volume conductor, the measured data may vary with internal electrical characteristics (e.g., conductivity and permittivity distribution), the size and shape of the volume conductor, and the position, size and shape of the electrodes.
Furthermore, there are Principal Component Analysis (PCA) or Independent Component Analysis (ICA) techniques to extract only components that respectively correspond to changes of a specific cause.
Here, PCA is used as a method of reducing the dimension by representing an original signal by using a linear combination of principal components having high energy.
Further, ICA refers to a computational method that separates a multivariate signal into statistically independent subcomponents, where the components include statistically independent components like non-gaussian signals, and can be used for blind signal separation that requires only statistical independence of each signal.
However, the prior art does not at all take into account that the size and shape of the volume conductor and the position, shape and size of the electrodes do not change over time, but rather that the internal electrical properties of the volume conductor change over time.
Therefore, there is a need to propose a technique of extracting a component associated with a specific physiological phenomenon while taking into account a change in electrical characteristics in a state where the position and shape of an electrode are unchanged with respect to a specific subject.
In addition, objects to be subjected to EIT include persons of various age groups (e.g., infants, children, adults, elderly people, etc.), men and women, and persons of various ethnic groups, and the size and shape of a portion to be imaged may generally be greatly varied according to age and obesity degree.
Therefore, there is a need for selecting a measurement method based on the degree of obesity, and a technique of extracting components associated with a specific physiological phenomenon from signals affected by many physiological phenomena must be considered.
Here, the EIT technique generates an image by: a plurality of electrodes are attached to a surface of a target object to be measured, an impedance of the target object is detected by the plurality of electrodes, and the detected impedance is converted into a conductivity and a dielectric constant of the target object.
EIT techniques are used to generate images of specific parts of the interior of the human body and have been widely used in the medical field.
Disclosure of Invention
The present disclosure extracts only components of a specific physiological phenomenon from a composite signal affected by a change in electrical characteristics inside a human body according to a plurality of physiological phenomena.
The present disclosure extracts components from electrical impedance imaging (EIT) that are respectively caused by air changes inside the upper respiratory tract, blood flow changes inside the carotid artery, neck movement while breathing, tongue movement, air changes inside the lungs, or chest blood flow changes.
The present disclosure restores an image based on components associated with a particular physiological phenomenon.
The present disclosure flexibly sets a measurement range of a voltage or a current by changing a method of injecting a current or a voltage in consideration of a size and a shape of a portion to be imaged.
The present disclosure determines an electrode pair for injecting a current or a voltage based on a circumference of a site to be imaged, thereby flexibly setting a measurement range of the voltage or the current.
When the measurement range of the voltage or the current is flexibly set, the present disclosure improves the quality of the restored image by increasing the number of voltages that can be distinguished from noise.
According to an embodiment of the present disclosure, an apparatus for extracting specific components and reconstructing data based on electrical impedance imaging (EIT) includes: an electrode unit including a plurality of electrodes to be attached to a measurement site of a subject; an electrical characteristic measurer configured to measure a plurality of electrical characteristics of the object according to elapsed time through the attached plurality of electrodes; an EIT data generator configured to generate EIT data based on the measured changes in the plurality of electrical characteristics; a pattern extractor configured to extract, from the generated EIT data, specific pattern data associated with a specific component caused by a specific physiological phenomenon of the subject; and an EIT data reconstructor configured to reconstruct the generated EIT data into EIT data corresponding to the specific component based on the extracted specific pattern data.
The pattern extractor may analyze one of energy and frequency of the generated EIT data by one of a signal-to-noise ratio, a Principal Component Analysis (PCA), or an Independent Component Analysis (ICA) in the generated EIT data, and extract specific pattern data associated with a specific component with respect to the frequency component, which is caused by a specific physiological phenomenon of the subject, based on the analyzed energy or frequency.
The EIT data reconstructor may reconstruct the generated EIT data into EIT data corresponding to the specific component based on a relative voltage change degree difference between the extracted specific pattern data and the generated EIT data.
An apparatus for extracting a specific component based on EIT and reconstructing data according to an embodiment of the present disclosure may further include an image restorer configured to restore an image associated with the specific component based on the reconstructed EIT data.
The plurality of measured electrical properties may include conductivity and permittivity distribution.
The specific component may include at least one of: changes in air within the respiratory tract or lungs of the subject, changes in blood flow within the body, changes in the component within the body, and changes in the motion of body parts.
According to an embodiment of the present disclosure, an apparatus for measuring an electrical characteristic based on an EIT includes: an electrode unit including a plurality of electrodes to be attached to a measurement site of a subject; and an electrical characteristic measurer configured to measure a plurality of electrical characteristics of the object through the attached plurality of electrodes. When the circumference of the measurement site is less than or equal to the measurement reference value, the electrical characteristic measurer determines adjacent first and second electrodes of the plurality of electrodes as a pair of supply electrodes; when the circumference of the measurement site is larger than the measurement reference value, the electrical characteristic measurer determines the first electrode and a third electrode as a supply electrode pair, the third electrode being farther from the first electrode than the second electrode; the electrical characteristic measuring device determines a plurality of supply electrode pairs having different distances according to a change in the circumferential length of the measurement portion.
The electrical characteristic measurer may supply a current or voltage to the determined pair of supply electrodes and measure a current or voltage induced by the current or voltage supplied through the attached plurality of electrodes.
When a current or voltage is induced by the supplied current or voltage, the electrical characteristic measurer may change a voltage gain or a current gain according to a circumference of the measurement portion.
According to an embodiment of the present disclosure, a method of extracting a specific component and reconstructing data based on EIT includes: measuring, by an electrical characteristic measurer, a plurality of electrical characteristics of the object according to elapsed time through a plurality of electrodes attached to a measurement site of the object; generating, by the EIT data generator, EIT data based on the measured changes in the plurality of electrical characteristics; extracting, by a pattern extractor, specific pattern data associated with a specific component caused by a specific physiological phenomenon of a subject from the generated EIT data; and reconstructing, by the EIT data reconstructor, the generated EIT data into EIT data corresponding to the specific component based on the extracted specific pattern data.
Extracting, from the generated EIT data, specific pattern data associated with a specific component caused by a specific physiological phenomenon of the subject may include: one of energy and frequency of the generated EIT data is analyzed by one of a signal-to-noise ratio, a Principal Component Analysis (PCA), and an Independent Component Analysis (ICA) in the generated EIT data, and specific pattern data associated with a specific component with respect to the frequency component, which is caused by a specific physiological phenomenon of the subject, is extracted based on the analyzed energy or frequency.
Reconstructing the generated EIT data into EIT data corresponding to the specific component based on the extracted specific pattern data may include: reconstructing the generated EIT data into EIT data corresponding to the specific component based on a relative voltage variation degree difference between the extracted specific pattern data and the generated EIT data.
According to an embodiment of the present disclosure, a method of measuring electrical characteristics based on EIT (in which a plurality of electrical characteristics of a subject are measured by a plurality of electrodes attached to a measurement site of the subject) may include: determining, by the electrical characteristic measurer, a first electrode and a second electrode adjacent to each other among the plurality of electrodes as a pair of supply electrodes when a circumference of the measurement site is less than or equal to a measurement reference value; determining, by the electrical characteristic measurer, the first electrode and a third electrode as a pair of supply electrodes when the circumference of the measurement site is greater than the measurement reference value, the third electrode being farther from the first electrode than the second electrode; and determining, by the electrical characteristic measuring device, a plurality of pairs of supply electrodes having different distances according to a change in the circumference of the measurement site.
According to an embodiment of the present disclosure, the method of measuring an electrical characteristic based on EIT may further include: supplying a current or a voltage to the determined pair of supply electrodes by the electrical characteristic measurer; measuring a current or voltage induced by a current or voltage supplied through the attached plurality of electrodes; and changing a voltage gain or a current gain according to a circumference of the measurement portion by the electrical characteristic measurer when a current or a voltage is induced by the supplied current or voltage.
Drawings
FIG. 1 shows elements of an apparatus for extracting specific components and reconstructing data based on electrical impedance imaging (EIT) according to an embodiment of the present disclosure;
FIG. 2 illustrates an embodiment relating to generating EIT data according to an embodiment of the disclosure;
3A-3G illustrate a method of extracting a particular component based on pattern data according to an embodiment of the present disclosure;
FIG. 4A illustrates elements of a pattern data processor according to an embodiment of the present disclosure;
FIG. 4B illustrates an embodiment relating to pattern data according to an embodiment of the present disclosure;
FIG. 5 illustrates an embodiment of restoring an image by a device for extracting specific components and reconstructing data according to an embodiment of the present disclosure;
FIGS. 6A and 6B illustrate embodiments relating to measurement of electrical characteristics according to embodiments of the present disclosure;
fig. 7 to 12 illustrate embodiments in which a combination of electrode pairs for injecting current is changed according to a circumference of a measured object;
FIG. 13 is a flow chart of a method of extracting specific components and reconstructing data according to an embodiment of the present disclosure; and
FIG. 14 is a flow chart of a method of measuring an electrical characteristic in accordance with an embodiment of the present disclosure.
Detailed Description
Hereinafter, various embodiments of the present disclosure will be described with reference to the accompanying drawings.
The embodiments and terms used herein are not to be construed as limiting the present disclosure to a particular form, and it is to be understood that various changes, equivalents, and/or substitutions may be effected in the embodiments.
In the following description, if the gist of the present inventive concept is influenced by the details of publicly known functions or features, they are omitted.
Also, terms used in the following description will be defined by considering functions of elements, but may be changed according to the intention or practice of a user, an operator, or the like. Therefore, the definition needs to be given based on the contents described in the following entire text.
With respect to the description of the figures, like numbers refer to like elements.
The singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
In the present disclosure, the terms "a or B," "at least one of a and/or B," and the like may include any possible combination of all of the listed items.
The terms "first," "second," and the like may be used herein to describe elements without regard to order or importance, and are used merely to distinguish one element from another and not to limit the elements.
It will be understood that when an element (e.g., a first) is referred to as being "connected" or "coupled" to another (e.g., a second) element (e.g., for functionality or communication), they may be directly connected or coupled to each other or connected or coupled to each other through the other (e.g., a third) element.
In the present disclosure, "configured to. (or set to.)" may be used interchangeably with "adapted.", "having.. capable", "modified.", "having.. such.", "enabled." or "designed.. such." depending on the particular situation, for example.
In some cases, "configured to.. a device" may mean that the device may be "capable" with another device or component.
For example, "a processor configured (or arranged) to perform A, B and C" may refer to a dedicated processor (e.g., an embedded processor) for performing operations, or may refer to a general-purpose processor (e.g., a Central Processing Unit (CPU) or an application processor) capable of performing operations by executing one or more software programs stored in a memory device.
Further, "or" means "may be accompanied or" rather than "exclusive or".
In other words, "x employs a or b" to mean one of the natural inclusive permutations, unless the context clearly dictates otherwise.
The terms ". section",.. unit "and the like as used herein refer to a unit that processes at least one function or operation, and it may be realized by hardware, software, or a combination of hardware and software.
Fig. 1 shows elements of an apparatus for extracting specific components and reconstructing data based on electrical impedance imaging (EIT) according to an embodiment of the present disclosure.
Referring to fig. 1, an apparatus 100 for extracting a specific component based on EIT and reconstructing data includes an electrode unit 110, an electrical characteristic measurer 120, an EIT data generator 130, a pattern extractor 140, and an EIT data reconstructor 150.
According to the present disclosure, the electrode unit 110 may include a plurality of electrodes to be attached to a measurement site of a subject.
For example, the plurality of electrodes may include at least one of a simple electrode or a combined electrode, and may include an EIT electrode to apply a current and measure impedance data for voltage measurement.
For example, the EIT electrode is disposed on one side of a substrate made of a flexible elastic material and attached to a measurement site of a subject. According to embodiments, the EIT electrodes may be shaped like a belt or vest.
In addition, the EIT electrode is used to inject a current having a relatively low value, such as a high-frequency current lower than or equal to 1mA, which cannot be felt by a subject, and to measure an induced voltage. The current-voltage data measured by the EIT electrodes can be used to detect internal patterns of the human body by imaging algorithms.
According to the embodiment of the present disclosure, the electrical characteristic measurer 120 measures a plurality of electrical characteristics of the object according to the elapsed time through a plurality of electrodes attached to the object.
For example, the electrical characteristic measurer 120 may determine a supply electrode pair from the plurality of electrodes based on the circumference of the measurement site, and supply a current or a voltage to the supply electrode pair. Here, the supply electrode pair may refer to an electrode pair for supplying current or voltage.
Further, the electrical characteristic measurer 120 may measure a current or voltage induced by a current or voltage of a measurement electrode pair in other electrodes than the supply electrode pair among the plurality of electrodes. Herein, the measurement electrode pair may refer to an electrode pair for measuring current or voltage.
For example, the plurality of electrical characteristics may include a conductivity and permittivity distribution of the induced current or voltage.
According to the embodiment of the present disclosure, when the circumference of the measurement site is less than or equal to the measurement reference value, the electrical characteristic measurer 120 may determine adjacent first and second electrodes as a supply electrode pair among the plurality of electrodes.
For example, when the circumference of the measurement site is larger than the measurement reference value, the electrical characteristic measurer 120 may determine the first electrode and the third electrode as the supply electrode pair among the plurality of electrodes. Here, the third electrode may refer to an electrode relatively farther from the first electrode than the second electrode.
According to an embodiment of the present disclosure, the measurement reference value may be based on at least one of a circumference of the measurement site, a maximum or minimum measurement value of the induced current or voltage, or a noise level.
For example, the measurement reference value may be set and changed by the user according to his needs.
In addition, the measurement reference value may be used as an index for determining a distance between electrodes forming an electrode pair for supplying current.
For example, the maximum and minimum measurements may increase as the distance between the two electrodes forming the supply electrode pair increases.
Further, when the distance between the two electrodes forming the supply electrode pair is reduced, the maximum measurement value and the minimum measurement value may be reduced.
According to the embodiment of the present disclosure, the electrical characteristic measurer 120 may measure a plurality of electrical characteristics within a voltage measurement range calculated by subtracting the minimum measurement value from the maximum measurement value.
In other words, according to the present disclosure, the method of injecting current or voltage is changed by considering the size and shape of the site to be imaged, and thus the range of measuring voltage or current is flexibly set.
According to the embodiment of the present disclosure, the electrical characteristic measurer 120 may supply a current or voltage to the pair of supply electrodes, and measure a current or voltage induced by the current or voltage supplied by the pair of measurement electrodes determined from the other electrodes than the pair of supply electrodes among the plurality of electrodes attached to the measurement site of the subject.
For example, the electrical characteristic measurer 120 may measure about 208 electrical characteristics by varying a combination between a supply electrode pair for injecting a current or a voltage and a measurement electrode pair for measuring a voltage or a current within 16 electrodes.
In more detail, the electrical characteristic measurer 120 may generate 208 pieces of time-series data by measuring 208 electrical characteristics over a certain period of time.
For example, a supply electrode pair may refer to an electrode pair for supplying current or voltage.
Further, the measuring electrode pair may refer to an electrode pair for measuring a current or voltage induced by a supplied current or voltage.
For example, the apparatus 100 for extracting a specific component based on the EIT and reconstructing data may include an apparatus (not shown) for measuring an electrical characteristic based on the EIT, the apparatus including an electrode unit 110 and an electrical characteristic measurer 120.
According to an embodiment of the present disclosure, the EIT data generator 130 may generate EIT data based on a change in a plurality of electrical characteristics. Here, the generated EIT data may also be referred to as measured EIT data.
For example, the EIT data generator 130 may generate EIT data from voltage measurement ranges.
In other words, the EIT data generator 130 may generate EIT data between the maximum voltage measurement and the minimum voltage measurement.
For example, EIT data may include variations in a number of electrical characteristics, noise, motion artifacts, and the like. In other words, EIT data may be affected by impedance changes associated with upper airway stenosis, respiratory motion, carotid blood flow, and irregular movement of the mandible and tongue.
According to an embodiment of the present disclosure, the pattern extractor 140 may determine at least one pattern data from the generated EIT data using a signal-to-noise ratio of the generated EIT data.
For example, the EIT data may include a plurality of signal-to-noise ratios that are different from each other based on a plurality of electrical characteristics.
In other words, the pattern extractor 140 can determine pattern data corresponding to 16 variations of the electrical characteristics with good signal-to-noise ratio from the 208 variations of the electrical characteristics of the EIT data.
For example, the pattern data may also be referred to as frequency pattern data associated with a scale change of the electrical characteristic.
Further, the pattern data may correspond to at least one frequency variation data according to a variation of the plurality of electrical characteristics within the EIT data.
According to the embodiment of the present disclosure, the pattern extractor 140 may extract pattern data corresponding to a specific component caused by a physiological phenomenon of a subject from at least one pattern data.
For example, the specific component may include at least one of: changes in the internal air of the respiratory tract or lungs of the subject, changes in the blood flow within the body, changes in the components within the body, and changes in the motion of body parts.
For example, the pattern extractor 140 may analyze one of energy or frequency in the EIT data using one of a signal-to-noise ratio, a Principal Component Analysis (PCA), or an Independent Component Analysis (ICA) in the EIT data.
Further, based on the analyzed energy or frequency, the pattern extractor 140 may extract specific pattern data associated with specific components relative to the frequency components, which are caused by specific physiological phenomena of the subject.
According to the present disclosure, only a component caused by a specific physiological phenomenon may be extracted from a composite signal affected by a change in an electrical characteristic inside a human body according to a plurality of physiological phenomena.
In other words, according to the present disclosure, components caused by air changes inside the upper respiratory tract, blood flow changes inside the carotid artery, neck movement during breathing, tongue movement, air changes inside the lungs, or chest blood flow changes, respectively, may be extracted from the EIT measurement data.
According to an embodiment of the present disclosure, the EIT data reconstructor 150 may reconstruct the EIT data into EIT data corresponding to a specific component based on the extracted pattern data.
For example, the EIT data reconstructor 150 may reconstruct the EIT data into EIT data corresponding to the specific component based on a relative voltage change difference between the extracted specific pattern data and the EIT data.
In other words, the EIT data reconstructor 150 may re-adjust the EIT data using a least squares error method, given the same difference between the relative sizes of the pattern data measured over a certain period of time.
According to an alternative embodiment of the present disclosure, the apparatus 100 for extracting a specific component based on the EIT and reconstructing data may further include an image restorer 160.
According to an embodiment of the present disclosure, the image restorer 160 may restore an image associated with a specific component based on the reconstructed EIT data.
For example, the image restorer 160 may restore an image associated with a specific component using EIT data divided based on the specific component.
For example, when the specific component is a component caused by air change in the lungs or chest blood flow change, the image restorer 160 may restore the image of air change in the lungs or the image of chest blood flow change separately.
An embodiment of separately restoring an image of air changes in the lungs or an image of changes in thoracic blood flow will be described later with reference to fig. 5.
According to the present disclosure, an image may be restored based on components associated with a particular physiological phenomenon.
In other words, according to the present disclosure, when the measurement range of the voltage or the current is flexibly set, the quality of the restored image can be improved by increasing the number of voltages distinguishable from noise.
Fig. 2 illustrates an embodiment related to generating EIT data according to an embodiment of the present disclosure.
In more detail, fig. 2 illustrates an embodiment of generating EIT data for a neck of a subject.
At operation 200, a method of extracting a particular component and reconstructing data includes attaching a plurality of electrodes to a region under a face of a subject.
At operation 210, the method of extracting specific components and reconstructing data includes measuring a plurality of electrical characteristics relating to component changes (e.g., respiratory related motion artifacts 211, blood flow 212, upper airway obstruction 213, etc.) through a plurality of electrodes attached to a lower portion of the subject's face.
At operation 220, the method of extracting the specific components and reconstructing the data may include measuring a plurality of electrical characteristics of the object according to the elapsed time. Here, the plurality of electrical characteristics to be measured may include noise 221 and noise caused by motion of the object.
At operation 230, the method of extracting the particular component and reconstructing the data may include generating EIT data 231 based on the changes in the plurality of electrical characteristics. Herein, EIT data may also be referred to as measured EIT data.
For example, EIT data 231 may be affected by impedance changes associated with upper airway stenosis, respiratory motion, carotid blood flow, and irregular motion of the mandible and tongue.
Fig. 3A to 3G illustrate a method of extracting a specific component based on pattern data according to an embodiment of the present disclosure.
Fig. 3A shows the results of EIT data generated by an EIT data generator according to an embodiment of the present disclosure using 16 electrodes, which involves changing 208 electrical characteristics through 208 channels. Here, the change in the electrical characteristic may show a change in a scale of the electrical characteristic with time. Further, the channels may be provided based on a combination of 16 electrodes.
Fig. 3B shows the results of a pattern extractor with a high signal-to-noise ratio (SNR) change of 16 electrical characteristics determined from 208 electrical characteristic changes using the signal-to-noise ratio according to an embodiment of the disclosure.
For example, the pattern extractor may select 16 voltage channels with the highest SNR from the 208 timing voltage channels as inputs to the ICA algorithm.
Fig. 3C shows the results of the pattern data corresponding to the 16 changes in electrical characteristics determined by the pattern extractor according to an embodiment of the present disclosure. For example, the determined pattern data may correspond to an ICA component.
Fig. 3D shows the result of the pattern extractor removing the noise pattern data 300 and the noise pattern data 301 from the 16 ICA components according to an embodiment of the present disclosure.
For example, when calculating the independent source signals S, the respiratory motion component and the blood flow component may be determined by spectral analysis.
When the fast fourier transform is applied to all the independent components of the independent source signals, the respiratory component having the fundamental frequency corresponding to the respiratory rate and the heart rate can be determined as the respiratory motion component and the blood flow component. The modified source signal U may be calculated based on the following expression 1.
[ expression 1]
In the expression 1 as well as in the expression 1,
it may be a modified mixing matrix that is,and is
May be an independent source signal.
The value can be obtained by replacing the column of the elements corresponding to the respiratory motion and the blood flow with 0
Fig. 3E illustrates the result of the pattern extractor extracting pattern data corresponding to a specific component 310 according to an embodiment of the present disclosure. For example, the particular component 310 may correspond to an upper airway signal.
Fig. 3F illustrates the result of the pattern extractor filtering the pattern data corresponding to the specific component 310 according to an embodiment of the present disclosure. Referring to fig. 3F, curve 320 corresponds to the particular component 310 and curve 321 corresponds to the upper airway signal passing through the low pass filter.
Here, 208 voltage data corresponding to upper airway stenosis may be restored to have an appropriate amplitude. Furthermore, a low pass filter may be used to reduce the residual noise of the recovered voltage data without distorting the pattern of upper airway stenosis.
Fig. 3G illustrates the result of an EIT data reconstructor that reconstructs EIT data based on the extracted pattern data, wherein the EIT data includes 208 changes in electrical characteristics corresponding to a particular component, according to an embodiment of the disclosure.
For example, the EIT data reconstructor may reconstruct EIT data that includes a change in 208 electrical characteristics based on [ expression 2] below.
[ expression 2]
Vj＝ajUUA+bj
In expression 2, VjMay be the voltage of the j-th channel, U may be the modified source signal, ajAnd bjMay be a constant corresponding to a difference between the plurality of voltage data.
In addition, the EIT data reconstructor may generate matrix data based on [ expression 3] below, and the generated matrix data may correspond to [ expression 4 ].
[ expression 3]
C＝(UUA TUUA)-1UUA TX
In [ expression 3], C may be reconstructed EIT data, U may be modified data, T may be time, and X may be initially generated EIT data.
[ expression 4]
In [ expression 4], C may be reconstructed EIT data, a and b may be constants corresponding to the voltage difference, and T may be time.
FIG. 4A illustrates elements of a pattern data processor according to an embodiment of the present disclosure.
Fig. 4A shows an operation process of the pattern data processor 400 including the pattern extractor.
Referring to fig. 4A, when the pattern data processor 400 receives the mixed signal 401, the BAR processor 410 removes the boundary artifact.
Further, the PCA processor 411 of the pattern data processor 400 extracts PCA pattern data 402 corresponding to the voltage principal component of the signal from which the boundary artifact is removed.
Meanwhile, the pattern data processor 400 extracts and outputs PCA pattern data 402 as data associated with the respiratory component.
Further, the L-curve detector 412 of the pattern data processor 400 extracts L-curve data from the PCA pattern data 402.
Further, the ICA processor 413 of the pattern data processor 400 detects ICA component data corresponding to the ICA component.
Further, the ICA selector 414 of the pattern data processor 400 may select and output the ICA pattern data 403 corresponding to a specific component among the ICA components.
Further, the source comparator 415 of the pattern data processor 400 may determine homogeneity between the PCA pattern data 402 and the ICA pattern data 403.
Finally, the pattern data processor 400 can use the PCA pattern data 402 and the ICA pattern data 403 to reconstruct EIT data, respectively.
Fig. 4B illustrates an embodiment relating to pattern data according to an embodiment of the present disclosure.
Referring to fig. 4B, there are shown frequency patterns of the mixed signal 401, PCA pattern data 402, and ICA pattern data 403.
For example, the mixed signal 401 includes PCA pattern data 402 and ICA pattern data 403.
Fig. 5 illustrates an embodiment of restoring an image by a device for extracting a specific component and reconstructing data according to an embodiment of the present disclosure.
Referring to fig. 5, the means for extracting the specific component and reconstructing the data generates EIT data 500 corresponding to the composite signal, extracts pattern data corresponding to the respiratory component 510, and extracts pattern data corresponding to the blood flow 511.
The means for extracting the particular components and reconstructing the data may use the respiratory component 510 to reconstruct the image data 520.
Further, the means for extracting the specific component and reconstructing the data may restore the image data 521 based on the blood flow 511.
In other words, the means for extracting the specific component and reconstructing the data may separate the component associated with the air change or the thoracic blood flow change in the lung from the EIT measurement data and separately restore the image based on the air change or the thoracic blood flow change in the lung using the separated EIT data.
Fig. 6A and 6B illustrate embodiments relating to measurement of electrical characteristics according to embodiments of the present disclosure.
Referring to fig. 6A, an electrode unit 600 including a plurality of electrodes may be attached to the perimeter of a subject.
For example, the plurality of electrodes may comprise a first electrode ε1To the sixteenth electrode ε16。
For example, the means for extracting a particular component and reconstructing data injects a current into the supply electrode pair 610 and measures a voltage through the measurement electrode pair 620.
The pair of supply electrodes 610 may include second electrodes epsilon adjacent to each other2And a third electrode epsilon3。
The measuring electrode pair 620 may include eighth electrodes epsilon adjacent to each other8And a ninth electrode ε9。
Referring to fig. 6B, an electrode unit 600 including a plurality of electrodes may be attached to the perimeter of the subject.
For example, the means for extracting a specific component and reconstructing data injects a current into the pair of supply electrodes 611 and measures a voltage through the pair of measurement electrodes 620.
The pair of supply electrodes 611 may include second electrodes epsilon that are not adjacent to each other2And a fourth electrode epsilon4。
Here, the pair of supply electrodes 611 may skip the third electrode ε3And comprises a fourth electrode epsilon4。
The measuring electrode pair 620 may also include eighth electrodes epsilon adjacent to each other8And a ninth electrode ε9。
Meanwhile, the maximum and minimum values of the induced voltage may vary according to the method of injecting the current.
In the "0-skip" method of injecting current between two adjacent electrodes, the internal current distribution is concentrated between the injection electrodes, and thus the internal voltage can be rapidly decreased as the distance from the current injection electrode increases.
In the "1-skip" method, in which not the directly adjacent electrode is selected but the next adjacent electrode is selected, the distance between two electrodes for injecting current can be increased.
The internal current then spreads spatially and slows down to the point of voltage reduction.
When all conditions of one patient are the same, "1-skip" increases the maximum and minimum values compared to "0-skip". In this case, the increment of the maximum value is larger than that of the minimum value, and thus the difference between the maximum value and the minimum value (i.e., the voltage range) may relatively increase.
Thus, when the voltage range is increased, the preset number of voltages distinguishable from noise is increased, thereby improving image quality.
When the distance between the two electrodes for injecting current is further increased, such as "2-skip", "3-skip", etc., the voltage range can be more effectively increased.
This is because the internal current is more diffused as the distance between the two electrodes for injecting current increases.
Meanwhile, when the conductivity on a specific portion changes, high sensitivity to the change is advantageous for generating a high-resolution image based on the change. In other words, "0-skip" may be most advantageous in terms of spatial resolution.
Fig. 7 shows an embodiment in which the current injection pair is changed according to the circumference of the object to be measured.
In more detail, fig. 7 shows that the voltage and the number of channels vary with the change in the circumference of the subject and the change in the combination of the pair of supply electrodes.
Data 703 indicates that when the circumference of the subject is 170cm, one unused electrode is included between the electrodes that are combined to form the supply electrode pair.
In other words, when one unused electrode is included between the electrodes combined to form the supply electrode pair, the number of channels and the voltage measurement range can be increased.
Further, when the circumference of the object increases, the number of channels may increase and the voltage measurement range may decrease.
Fig. 8 shows an embodiment in which the combination of electrodes forming a current injection pair varies according to the circumference of the measured object.
Referring to fig. 8, when adjacent electrodes are combined to form a supply electrode pair, data 800 may correspond to a voltage measurement range obtained by subtracting a minimum value from a maximum value.
The data 802 may correspond to a minimum value when adjacent electrodes combine to form a pair of supply electrodes.
When an unused electrode is included between the electrodes that are combined to form a supply electrode pair, the data 810 may correspond to a voltage measurement range obtained by subtracting a minimum value from a maximum value.
Fig. 9A shows an example in which the combination of electrodes forming a current injection pair varies according to the circumference of a measured object.
In more detail, fig. 9A shows the voltage and the number of channels measured based on the change in the combination of the breathing and supply electrode pairs of the subject.
Referring to fig. 9A, data 900 may correspond to a gettering when adjacent electrodes combine to form a supply electrode pair.
The data 901 may correspond to exhalation when adjacent electrodes combine to form a supply electrode pair.
Fig. 9B shows an embodiment in which the combination of electrodes forming a current injection pair varies according to the circumference of the object to be measured.
In more detail, fig. 9B shows the voltage and the number of channels measured based on the change in the circumference of the measured object and the change in the combination of the pair of supply electrodes.
Fig. 10 shows an embodiment in which the combination of electrodes forming a current injection pair varies according to the circumference of a measured object.
Referring to fig. 10, when adjacent electrodes are combined to form a supply electrode pair, data 1000 may correspond to a voltage measurement range obtained by subtracting a minimum value from a maximum value.
The data 1001 may correspond to a maximum value when adjacent electrodes are combined to form a supply electrode pair.
The data 1002 may correspond to a minimum value when adjacent electrodes combine to form a supply electrode pair.
For example, when adjacent electrodes are combined to form a supply electrode pair, this may also be referred to as "0-skip".
When an unused electrode is included between the electrodes that are combined to form the supply electrode pair, the data 1010 may correspond to a voltage measurement range obtained by subtracting a minimum value from a maximum value.
For example, when an unused electrode is included between the electrodes that are combined to form the supply electrode pair, this may also be referred to as "1-skip".
According to an embodiment of the present disclosure, an apparatus for measuring electrical characteristics measures a circumference of a patient at a site where an electrode is attached.
The means for measuring electrical characteristics may then estimate the maximum, minimum and range (i.e. maximum-minimum) from a graph or table given based on the measured perimeter. Here, the means for measuring the electrical characteristic employs "0-skip".
The means for measuring the electrical characteristic may determine the amplifier gain such that the product of the maximum value of the voltage and the amplifier gain can be equal to the maximum input voltage of an ADC used in the system.
Alternatively, when using the amplifier gain, the means for measuring the electrical characteristic may calculate the voltage range (i.e., maximum-minimum) corresponding to the measured circumference from a graph or table.
The means for measuring the electrical characteristic may calculate the number of distinguishable voltages by dividing the aforementioned voltage range by the noise level of the EIT system used.
The means for measuring electrical characteristics employs a "1-skip" when it is desired to increase the number of distinguishable voltages. However, when the number of voltages distinguishable even by using "1-skip" is not sufficient, the apparatus for measuring electrical characteristics may employ "2-skip".
At the same time, the apparatus for measuring electrical characteristics may repeat the above process to determine a minimum "skip" that ensures a distinguishable number of voltages.
Fig. 11 shows an example in which the combination of electrodes forming a current injection pair varies according to the circumference of a measured object.
In more detail, fig. 11 shows voltage gains for adjusting the maximum value of the voltage to the maximum input voltage of the ADC by "0-skip" and "1-skip".
Fig. 12 shows an embodiment in which the combination of electrodes forming a current injection pair varies according to the circumference of a measured object.
In more detail, fig. 12 shows that the number of voltages distinguishable under "0-skip" and "1-skip" varies as the circumference increases.
Fig. 13 is a flowchart related to a method of extracting a specific component and reconstructing data according to an embodiment of the present disclosure.
Referring to fig. 13, at operation 1301, a method of extracting a specific component and reconstructing data includes measuring an electrical characteristic of an object.
In other words, the method of extracting the specific component and reconstructing the data may include measuring a plurality of electrical characteristics of the object according to the elapsed time through a plurality of electrodes attached to the object.
At operation 1302, a method of extracting a particular component and reconstructing data can include generating EIT data.
In other words, a method of extracting a particular component and reconstructing data may include generating EIT data based on a change in a plurality of measured electrical characteristics.
At operation 1303, the method of extracting the specific component and reconstructing the data may extract specific pattern data from the EIT data.
In other words, the method of extracting a specific component and reconstructing data may analyze the energy or frequency of the generated EIT data using one of the signal-to-noise ratio, PCA and ICA in the generated EIT data.
Further, the method of extracting specific components and reconstructing data may extract specific pattern data associated with specific components with respect to frequency components caused by specific physiological phenomena of the subject based on the analyzed energy or frequency.
At operation 1304, the method of extracting the particular component and reconstructing the data may reconstruct EIT data based on the particular pattern data.
In other words, the method of extracting a specific component and reconstructing data may reconstruct the previously generated EIT data into EIT data corresponding to the specific component using the extracted specific pattern data.
In more detail, the method of extracting a specific component and reconstructing data may reconstruct previously generated EIT data into EIT data corresponding to the specific component using a relative voltage change degree difference between specific pattern data and previously generated EIT data.
FIG. 14 is a flow chart relating to a method of measuring electrical characteristics based on EIT according to an embodiment of the present disclosure.
Referring to fig. 14, at operation 1401, a method of measuring an electrical characteristic based on EIT includes comparing a circumference of a measurement site of a subject with a measurement reference value.
At operation 1402, a method of measuring an electrical characteristic based on EIT may include: when the circumference of the measurement site is less than or equal to the measurement reference value, the first electrode and the second electrode are determined as a supply electrode pair. Here, the first electrode and the second electrode may be adjacent to each other.
On the other hand, when the circumference of the measurement site is greater than the measurement reference value, the method of measuring electrical characteristics based on EIT performs operation 1403.
At operation 1403, the method of measuring electrical characteristics based on EIT compares the circumference of the measurement site of the subject with a measurement reference value.
At operation 1404, the method of measuring an electrical characteristic based on EIT may determine the first electrode and the third electrode as a supply electrode pair when a circumference of the measurement site is greater than the measurement reference value. Here, the third electrode is adjacent to the second electrode, but at a slight distance from the first electrode.
For example, the method of measuring an electrical characteristic based on EIT may further include: by repeatedly performing operations 1402 to 1404, a plurality of supply electrode pairs different in distance are determined according to a change in the circumference of the measurement site.
According to the present disclosure, only a component of a specific physiological phenomenon may be extracted from a composite signal affected by a change in an electrical characteristic inside a human body according to a plurality of physiological phenomena.
According to the present disclosure, components respectively caused by air changes inside the upper respiratory tract, blood flow changes inside the carotid artery, neck movement while breathing, tongue movement, air changes inside the lungs, or chest blood flow changes may be extracted according to electrical impedance imaging (EIT).
According to the present disclosure, an image may be restored based on components associated with a particular physiological phenomenon.
According to the present disclosure, it is possible to flexibly set a measurement range of voltage or current by changing a method of injecting current or voltage in consideration of the size and shape of a site to be imaged.
According to the present disclosure, it is possible to determine the electrode pair for injecting current or voltage based on the circumference of the site to be imaged, thereby flexibly setting the measurement range of voltage or current.
According to the present disclosure, when the measurement range of the voltage or the current is flexibly set, the quality of the restored image can be improved by increasing the number of voltages distinguishable from noise.
The method according to the embodiment may be implemented in the form of program instructions that are implemented by various computer means and recorded in a computer-readable medium. The computer readable medium may include separate program instructions, data files, data structures, etc., or a combination thereof.
The program instructions recorded in the medium may be specially designed or configured for the embodiments, or may be well known and available to those having ordinary skill in the computer software arts. The computer-readable recording medium may include, for example, magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROM and DVD; magneto-optical media such as soft magnetic discs; and ROM, RAM, flash memory, and the like, that are specially configured to store and execute program instructions.
The program instructions may include, for example, not only machine language codes generated by a compiler but also high-level language codes executed by a computer through an interpreter or the like. A hardware device may be configured to operate one or more software modules to perform operations according to embodiments, and vice versa.
Although some embodiments have been described using illustrative examples and drawings, various changes and modifications can be made by one skilled in the art in light of the foregoing description. For example, appropriate results may also be produced in the following cases: performing the described techniques in an order different from the order of the described methods; and/or elements described (e.g., systems, structures, devices, circuits, etc.) coupled or combined in a manner different from that described, or replaced with other elements or equivalents.
Accordingly, other implementations, embodiments, and equivalents of the claims are also within the scope of the following claims.
Claims (14)
1. An apparatus for extracting specific components and reconstructing data based on electrical impedance imaging (EIT), the apparatus comprising:
an electrode unit including a plurality of electrodes to be attached to a measurement site of a subject;
an electrical characteristic measurer configured to measure a plurality of electrical characteristics of the object according to elapsed time through the attached plurality of electrodes;
an EIT data generator configured to generate EIT data based on the measured changes in the plurality of electrical characteristics;
a pattern extractor configured to extract, from the generated EIT data, specific pattern data associated with a specific component caused by a specific physiological phenomenon of the subject; and
an EIT data reconstructor configured to reconstruct the generated EIT data into EIT data corresponding to the specific component based on the extracted specific pattern data.
2. The apparatus of claim 1, wherein the pattern extractor analyzes one of energy and frequency of the generated EIT data by one of a signal-to-noise ratio, a Principal Component Analysis (PCA), or an Independent Component Analysis (ICA) in the generated EIT data, and extracts specific pattern data associated with specific components relative to the frequency components, which are caused by a specific physiological phenomenon of the subject, based on the analyzed energy or frequency.
3. The apparatus of claim 1, wherein the EIT data reconstructor reconstructs the generated EIT data into the EIT data corresponding to the specific component based on a relative voltage variation degree difference between the extracted specific pattern data and the generated EIT data.
4. The apparatus of claim 1, further comprising an image restorer configured to restore an image associated with the particular component based on the reconstructed EIT data.
5. The apparatus of claim 1, wherein the plurality of measured electrical characteristics includes conductivity and permittivity distribution.
6. The apparatus of claim 1, wherein the particular component comprises at least one of: changes in air within the respiratory tract or lungs of the subject, changes in blood flow within the body, changes in components within the body, and changes in movement of body parts.
7. An apparatus for measuring electrical characteristics based on Electrical Impedance Tomography (EIT), the apparatus comprising:
an electrode unit including a plurality of electrodes to be attached to a measurement site of a subject; and
an electrical characteristic measurer configured to measure a plurality of electrical characteristics of the object by the plurality of electrodes attached;
when the circumference of the measurement site is less than or equal to a measurement reference value, the electrical characteristic measurer determines adjacent first and second electrodes of the plurality of electrodes as a supply electrode pair; when the circumference of the measurement site is larger than a measurement reference value, the electrical characteristic measurer determines the first electrode and the third electrode as a supply electrode pair, wherein the third electrode is farther from the first electrode than the second electrode; and the electrical characteristic measuring device determines a plurality of supply electrode pairs having different distances according to a change in the circumference of the measurement portion.
8. The apparatus according to claim 7, wherein the electrical characteristic measurer supplies current or voltage to the determined pair of supply electrodes and measures current or voltage induced by current or voltage supplied through the attached plurality of electrodes.
9. The apparatus according to claim 7, wherein the electrical characteristic measurer changes a voltage gain or a current gain according to a circumference of the measurement portion when a current or a voltage is induced from the supplied current or voltage.
10. A method of extracting specific components and reconstructing data based on electrical impedance imaging (EIT), the method comprising:
measuring, by an electrical characteristic measurer, a plurality of electrical characteristics of the object according to elapsed time through a plurality of electrodes attached to a measurement site of the object;
generating, by the EIT data generator, EIT data based on the measured changes in the plurality of electrical characteristics;
extracting, by a pattern extractor, specific pattern data associated with a specific component caused by a specific physiological phenomenon of a subject from the generated EIT data; and
reconstructing, by an EIT data reconstructor, the generated EIT data into EIT data corresponding to the specific component based on the extracted specific pattern data.
11. The method of claim 10, wherein extracting, from the generated EIT data, specific pattern data associated with a specific component caused by a specific physiological phenomenon of the subject comprises:
analyzing one of energy and frequency of the generated EIT data by one of a signal-to-noise ratio, a Principal Component Analysis (PCA), or an Independent Component Analysis (ICA) in the generated EIT data; and
based on the analyzed energy or frequency, specific pattern data associated with specific components relative to the frequency components, which are caused by specific physiological phenomena of the subject, are extracted.
12. The method of claim 10, wherein reconstructing the generated EIT data into EIT data corresponding to the particular component based on the extracted particular pattern data comprises:
reconstructing the generated EIT data into EIT data corresponding to the specific component based on a relative voltage variation degree difference between the extracted specific pattern data and the generated EIT data.
13. A method of measuring electrical properties based on Electrical Impedance Tomography (EIT), wherein a plurality of electrical properties of an object are measured by a plurality of electrodes attached to measurement sites of the object, the method comprising:
determining, by an electrical characteristic measurer, a first electrode and a second electrode adjacent to each other among the plurality of electrodes as a pair of supply electrodes when a circumference of the measurement site is less than or equal to a measurement reference value;
determining, by the electrical characteristic measurer, a first electrode and a third electrode as a supply electrode pair when the circumference of the measurement site is greater than the measurement reference value, wherein the third electrode is farther from the first electrode than the second electrode; and
the plurality of supply electrode pairs having different distances are determined by the electrical characteristic measuring device based on a change in the circumferential length of the measurement portion.
14. The method of claim 13, further comprising:
supplying, by the electrical characteristic measurer, a current and a voltage to the determined pair of supply electrodes;
measuring a current or voltage induced by a current or voltage supplied through the attached plurality of electrodes; and
when a current or voltage is induced by the supplied current or voltage, a voltage gain or a current gain is changed by the electrical characteristic measuring device in accordance with the circumference of the measurement portion.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010244158.9A CN113470130A (en) | 2020-03-31 | 2020-03-31 | Apparatus and method for extracting components related to specific physiological phenomena and reconstructing EIT data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010244158.9A CN113470130A (en) | 2020-03-31 | 2020-03-31 | Apparatus and method for extracting components related to specific physiological phenomena and reconstructing EIT data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113470130A true CN113470130A (en) | 2021-10-01 |
Family
ID=77865426
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010244158.9A Pending CN113470130A (en) | 2020-03-31 | 2020-03-31 | Apparatus and method for extracting components related to specific physiological phenomena and reconstructing EIT data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113470130A (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2853196A1 (en) * | 2013-09-27 | 2015-04-01 | Dräger Medical GmbH | Electro-impedance tomography apparatus and method |
| CN106037650A (en) * | 2016-06-13 | 2016-10-26 | 河北工业大学 | Hybrid variation bioelectrical impedance imaging method |
| CN109864712A (en) * | 2019-04-02 | 2019-06-11 | 北京华睿博视医学影像技术有限公司 | Electrical impedance imaging device and method |
| CN110035691A (en) * | 2016-11-18 | 2019-07-19 | 百来 | Method and apparatus for measuring sleep apnea |
-
2020
- 2020-03-31 CN CN202010244158.9A patent/CN113470130A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2853196A1 (en) * | 2013-09-27 | 2015-04-01 | Dräger Medical GmbH | Electro-impedance tomography apparatus and method |
| CN106037650A (en) * | 2016-06-13 | 2016-10-26 | 河北工业大学 | Hybrid variation bioelectrical impedance imaging method |
| CN110035691A (en) * | 2016-11-18 | 2019-07-19 | 百来 | Method and apparatus for measuring sleep apnea |
| CN109864712A (en) * | 2019-04-02 | 2019-06-11 | 北京华睿博视医学影像技术有限公司 | Electrical impedance imaging device and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Advancing hand gesture recognition with high resolution electrical impedance tomography | |
| Adler et al. | Impedance imaging of lung ventilation: do we need to account for chest expansion? | |
| Durka et al. | Multichannel matching pursuit and EEG inverse solutions | |
| EP2465429B1 (en) | System and method for determining physiological parameters based on electrical impedance measurements | |
| US9730607B2 (en) | Electrical impedance tomography device and process | |
| Estrada et al. | Improvement in neural respiratory drive estimation from diaphragm electromyographic signals using fixed sample entropy | |
| Langers et al. | Spectrotemporal features of the auditory cortex: the activation in response to dynamic ripples | |
| US10874324B2 (en) | Detection of physiological changes in impedance monitoring | |
| Estrada et al. | Onset and offset estimation of the neural inspiratory time in surface diaphragm electromyography: a pilot study in healthy subjects | |
| KR102234640B1 (en) | Apparatus and method of extracting component associated with specific physiological phenomenon by measuring electric property and of reconstructing eit data by using extracted component | |
| Wu et al. | Camera-based blood pressure estimation via windkessel model and waveform features | |
| CN113470130A (en) | Apparatus and method for extracting components related to specific physiological phenomena and reconstructing EIT data | |
| Artoni et al. | Selecting the best number of synergies in gait: preliminary results on young and elderly people | |
| US20210290097A1 (en) | Apparatus and method for extracting component associated with specific physiological phenomenon based on measurement of electric properties, and reconstructing eit data by using extracted component | |
| KR101744691B1 (en) | Method and Apparatus for Detecting Heartbeat using Ballistocardiogram | |
| JP6961261B2 (en) | A device and method for extracting components caused by a specific physiological phenomenon based on the measurement of electrical properties and reconstructing EIT data using the extracted components. | |
| GB2592366A (en) | Apparatus and method of extracting component associated with specific physiological phenomenon by measuring electric property and of reconstructing eit data | |
| McKeown et al. | Deterministic and stochastic features of fMRI data: implications for analysis of event-related experiments | |
| Benazzouz et al. | Knee pathology diagnosis based on muscle activation intervals detection and the relationship between knee flexion and surface EMG | |
| Ming et al. | Multiscale entropy analysis of attention ralated EEG based on motor imaginary potential | |
| Uguz et al. | A novel sensor design for amplitude modulated measurement of capacitive ECG | |
| Hahn et al. | Improvements in the image quality of ventilatory tomograms by electrical impedance tomography | |
| Holobar et al. | Surface EMG decomposition | |
| WO2022199619A1 (en) | Electrical impedance tomography based lung assessment | |
| Amin et al. | Comparison of data-driven respiratory signal extraction methods from cone-beam CT (CBCT) |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |