WO2006022226A1 - 生体パラメータ出力装置およびプログラム - Google Patents
生体パラメータ出力装置およびプログラム Download PDFInfo
- Publication number
- WO2006022226A1 WO2006022226A1 PCT/JP2005/015209 JP2005015209W WO2006022226A1 WO 2006022226 A1 WO2006022226 A1 WO 2006022226A1 JP 2005015209 W JP2005015209 W JP 2005015209W WO 2006022226 A1 WO2006022226 A1 WO 2006022226A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- information
- biological parameter
- waveform information
- action potential
- waveform
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
Definitions
- the present invention relates to a biological parameter output device or the like that is a device for estimating a biological parameter having an effect or the like due to drug injection or the like using action potential simulation by giving a change in an action potential waveform of a cell membrane as an input. Is.
- the powerful simulation method is a method of simulating the diffusion of a specific substance in the living body using the finite element method, and the finite element method is used without using the finite element method by using a part of the tissue from which the biological force is also separated.
- Determine the standard diffusion characteristic constant in the living body set the standard diffusion characteristic based on the reference diffusion characteristic constant, and determine the biological structure to be analyzed based on the finite element method.
- the diffusion characteristic constant is used to calculate the diffusion in the determined biological structure based on the finite element method, and the calculation diffusion characteristic and the finite element method according to the calculation result based on the finite element method of diffusion in the living body.
- the standard diffusion characteristic constant is corrected so that the deviation between the calculated diffusion characteristic and the reference diffusion characteristic is minimized, and the optimum diffusion characteristic coefficient based on the finite element method is calculated. To do Which is a simulation method of the raw body diffusion characterized.
- Non-Patent Document 1 There is a simulation device that obtains action potential waveform information by uresing (see Non-Patent Document 1).
- Patent Document 1 Japanese Patent Laid-Open No. 08-016551 (1st page, Fig. 1 etc.)
- Patent Document 2 JP-A-61-119252 (1st page, Fig. 1 etc.)
- Patent Document 3 Japanese Patent Laid-Open No. 03-015439 (1st page, Fig. 1 etc.)
- Non-Patent Literature 1 Nobuaki Sarai and Akinori Noma “simBio: Biological Dynamic Model Development Platform” The Journal of the Japan Society of Chemistry BME, vol. 18, No. 2, p. 3— 11, 2004 (2004 2 (Monthly issue)
- the simulation method in Patent Document 1 is a method for analyzing a diffusion phenomenon of a drug in a living tissue, and is not a method for estimating a biological parameter indicating an effect such as drug injection.
- Patent Documents 2 and 3 are techniques for measuring the degree of arteriosclerosis, and it is not possible to evaluate the influence of an input drug on biological parameters.
- the age determination means in Patent Documents 2 and 3 must previously store a plurality of reference patterns according to the age.
- the present invention measures the action potential waveform change at the time of drug administration by cultured cells or animal experiments, etc., and uses this to evaluate the action of the input drug on each channel of the cell. Aim to provide a method to evaluate the effect on parameters
- the first invention provides a biological parameter identifier for identifying a biological parameter and the biological parameter.
- a waveform having action parameter waveform information which is information indicating a corresponding action potential waveform and a corresponding action parameter waveform, including a set of one or more signs of a living body parameter value that is a value of a living body parameter value identified by a parameter identifier.
- the waveform information storage unit that stores one or more information
- the waveform information reception unit that receives input of action potential waveform information, and the waveform information that is closest to the action potential waveform information received by the waveform information reception unit
- a biological parameter information acquisition unit that identifies and acquires a biological parameter set including one or more biological parameter information
- a biological parameter information output unit that outputs the biological parameter set acquired by the biological parameter information acquisition unit. Is a biological parameter output device
- the second invention is a biometric parameter set of the waveform information stored in the waveform information storage unit is input information to the first invention, and the waveform information storage
- the action potential waveform information among the waveform information stored in the unit is information obtained by using biological simulation for the input biological parameter set.
- the action potential waveform information is information characterizing action potential waveforms of APD30, APD60 and APD90, and is a biological parameter.
- the information acquisition unit acquires the action potential waveform information of APD30, APD60, and APD90 of the action potential waveform information, and includes one or more biological parameter information that matches or most approximates the three action potential waveform information acquired It is a biological parameter output device that acquires a biological parameter set.
- the powerful configuration makes it possible to acquire biological parameter sets at high speed and with low CPU power.
- the fourth invention is a living body that can reproduce waveform information closest to the action potential waveform information before and after the drug injection by using the biological simulation according to the configurations of the first and second inventions.
- a parameter set can be acquired, and the effect of drug input can be output as a biological parameter. The invention's effect
- the present invention can provide a device or the like that outputs a biological parameter indicating effects such as drug injection.
- Biological parameters include various cellular channels (eg, Na channel, Ca channel, K
- FIG. 1 is a block diagram of the biological parameter output device.
- the biological parameter output device includes a waveform information storage unit 11, a waveform information reception unit 12, a biological parameter information acquisition unit 13, and a biological parameter information output unit 14.
- the biological parameter information acquisition unit 13 includes waveform information comparison means 131 and biological parameter information generation means 132.
- the waveform information storage unit 11 includes one or more biological parameter information that is a set of a biological parameter identifier that identifies a biological parameter and a biological parameter value that is a value of the biological parameter identified by the biological parameter identifier. Stores one or more waveform information having parameter sets and action potential waveform information, which is information indicating action potential waveforms.
- the waveform information is usually obtained as follows by means not shown. That is, a device or the like (not shown) that acquires waveform information is a biological parameter value that is a set of a biological parameter identifier that identifies a biological parameter and a biological parameter value that is identified by the biological parameter identifier.
- a biometric parameter set including one or more parameter information is received as input, and action potential waveform information corresponding to it is acquired.
- action potential waveform information may be obtained using a living body.
- device power to obtain waveform information Apply biological parameter sets to cell models that simulate cells, and use simulation to reconstruct action potential waveform information (hereinafter referred to as action potential waveform information obtained using simulation as appropriate).
- Action potential waveform information may be obtained.
- the biological parameter output device has a built-in device for acquiring waveform information, Simulation results may be generated each time.
- the biological parameter output device may read action potential waveform information generated in advance from a database. Furthermore, the action potential waveform information may be in the form of a graph or a record.
- the data structure of the action potential waveform information does not matter.
- the waveform information storage unit 11 is preferably a non-volatile recording medium, but can also be realized by a volatile recording medium.
- a storage medium that stores one or more biological parameter sets and one or more action potential waveform information corresponding thereto is a waveform information database (not shown).
- a simulation device an example of a device that acquires waveform information
- receives a biological parameter set as input, simulates a cell, and acquires action potential waveform information is known technology (above, Non-patent document 1).
- the waveform information receiving unit 12 receives input of action potential waveform information that is information related to the action potential waveform.
- the action potential waveform information is usually information obtained by measuring vital force of individuals, organs, tissues, cells, and the like.
- the action potential waveform information is, for example, information on the action potential waveform of the cell before and after drug administration, and information on the action potential waveform obtained from the cell force of the gene knockout animal or disease model animal.
- the action potential waveform information may be all time series data of the membrane potential (a set of information of points constituting the waveform) or not all. In other words, the action potential waveform information may be the value of APD30, the value of APD60, the value of APD90, etc. in the waveform.
- the values of APD30, APD60, and APD90 are the values shown in FIG. In other words, in Fig. 2, when the height from the highest potential (point a) to the lowest potential (point b) is 100, the width of the waveform at the height 30 points below point a is APD30. Similarly, assuming that the height from the highest potential (point a) to the lowest potential (point b) of the waveform is 100, the waveform width is APD60, APD90 at the height of a point 60 below and 90 below. .
- the action potential waveform information can be input by any means such as a scanner, keyboard, mouse or menu screen.
- the action potential waveform information may be information output from another device, for example, a measurement device.
- the waveform information receiving unit 12 can be realized by a device driver of an input means such as a scanner or a keyboard, control software for a menu screen, or the like.
- the biological parameter information acquisition unit 13 includes one or more action potential waveform information received by the waveform information reception unit 12 and one or more of the waveform information stored in the waveform information storage unit 11.
- a biological parameter set including biological parameter information is identified and acquired.
- Various parameter search algorithms such as experimental design, genetic algorithm, steepest descent method, response phase method, etc. can be applied to obtain biological parameter information. Compared with the results of any simulation, it is possible to extract norames.
- the biological parameter information acquisition unit 13 can usually be realized by an MPU, a memory, or the like.
- the processing procedure of the biological parameter information acquisition unit 13 is usually realized by software, and the software is recorded on a recording medium such as a ROM. However, it can be realized with hardware (dedicated circuit).
- the biological parameter information output unit 14 outputs the biological parameter set acquired by the biological parameter information acquisition unit 13. Output is a concept that includes display on a display, printing on a printer, sound output, transmission to an external device, and the like.
- the biological parameter information output unit 14 may or may not include an output device such as a display or a speaker.
- the output unit can be realized by output device driver software or output device driver software and an output device.
- the waveform information comparison unit 131 determines the degree of approximation between the action potential waveform information acquired from the waveform information storage unit 11 and the action potential waveform information received by the waveform information reception unit 12.
- the waveform information comparing means 131 may acquire and compare action potential characteristic information such as APD30 as follows, for example. That is, it is assumed that the action potential waveform information received by the waveform information receiving unit 12 is a set of numeric strings of potential (mV) and time (ms) forming a waveform. In this case, the waveform information comparison unit 131 acquires two times (T, T) paired with the value of “the highest potential (the highest potential and the lowest potential) X O.3”. Next, the waveform information comparing means 131
- Waveform information comparison means 131 Calculate “TI” (the absolute value of the difference between T and T) as APD30. Waveform information comparison means 131
- the action potential waveform information received by the waveform information receiving unit 12 is the values of APD30, APD60, and APD90.
- the waveform information comparison unit 131 calculates the absolute value of the difference between the calculated APD30 and the APD30 received by the waveform information receiving unit 12, and the absolute value of the calculated difference between the APD60 and the APD60 received by the waveform information receiving unit 12.
- the sum of the absolute values of the differences between the received APD90 and the APD90 received by the waveform information receiving unit 12 is calculated.
- Adaptive Piecewis e Waveform data may be discretized using the Constant Approximation method, etc., and compared! /, a set of numerical digit sequences of potentials with respect to time may be directly compared using the sum of squares of differences in waveform information. Then, the Euclidean distance or the like may be measured and compared.
- the biological parameter information generation unit 132 includes one or more biological parameter information paired with the action potential information that the action potential waveform information compared by the waveform information comparison unit 131 matches or approximates most. A biometric parameter set is identified. The biometric parameter information generation unit 132 may check all the waveform information that can be acquired from the waveform information storage unit 11 in a brute force manner and extract a biometric parameter set that the waveform information that matches or most approximates. .
- the waveform information comparison unit 131 calculates the absolute value of the difference between the calculated APD30 and the waveform information receiving unit 12, and the calculated absolute value of the difference between the APD60 and the waveform information receiving unit 12
- the biometer information generating means 132 is paired with the action potential information having the smallest total value.
- the biometric parameter information is acquired from the waveform information storage unit 11.
- the biological parameter information generating means 132 may acquire one or more pieces of biological parameter information at high speed by an algorithm such as a sorted waveform information power binary search.
- the biological parameter information generating means 132 may extract biological parameter information using a technique such as a hybrid 'tree' index method, an experimental design method, a genetic algorithm, a sudden drop method, and a response phase method. .
- Step S301 The waveform information receiving unit 12 determines whether or not an input of action potential waveform information has been received. If the input of action potential waveform information is accepted, the process goes to step S302. If the input of action potential waveform information is not accepted, the process returns to step S301.
- Step S302 The biological parameter information generating means 132 substitutes 1 for the counter i.
- Step S303 The biological parameter information generation means 132 generates a new biological parameter set.
- the waveform information storage unit 11 may store one or more reconstructed action potential waveform information as a result of simulation in a biological simulation unit (not shown)!
- Step S304 The waveform information comparing means 131 determines whether or not the reconstructed action potential waveform information of the mesh exists. If it exists, go to step S305; otherwise, go to step S309.
- Step S 305 The waveform information comparison unit 131 calculates an approximation that is the degree of approximation between the action potential information acquired in Step S 301 and the i-th reconstructed action potential waveform information.
- the degree of approximation There are various methods for calculating the degree of approximation. A specific example of the method for calculating the degree of approximation will be described later.
- Step S306 The waveform information comparing means 131 temporarily stores the degree of approximation calculated in step S306 in association with the i-th reconstructed action potential waveform information.
- Step S307 The waveform information comparing means 131 increments the counter i by 1.
- Step S308 The waveform information comparing means 131 does not reach the specified number of times, and if the degree of approximation is lower than the predetermined degree of approximation (when the condition is met), the waveform information comparing unit 131 proceeds to step S303. Return. If the conditions are not met, go to step S309.
- the number of times is the number of times that covers all combinations of biological parameter sets.
- the biological parameter information generating unit 132 acquires a biological parameter set (one or more biological parameter information) having the highest degree of approximation.
- Step S310 The biological parameter information output unit 14 outputs the one or more biological parameter information acquired in step S309. Return to step S301.
- the waveform information storage unit 11 holds the reconstructed action potential waveform information shown in FIG.
- This reconstructed action potential waveform information is information indicating the relationship between the biological parameters identified by the three biological parameter identifiers “IKr”, “IK1”, and “IKs”, and the values of each biological parameter and the action potential information. It is.
- the value of the biological parameter identifier “IKr” is taken from “0” to “5.0”, and the value of “IK1” is taken from “0.2” to “2.00”.
- 1 is a numerical value indicating a normal state .
- this reconstructed action potential waveform information is the action potential waveform information that is usually obtained using biological simulation, and is the action potential information stored in the waveform information storage unit 11.
- the horizontal axis is the value of "IKr”
- the vertical axis is the value of "IK1”
- the color of the rectangle at the intersection indicates the value of APD30.
- the color density of the rectangle generally indicates the value of APD30.
- the meaning of the darkness of the horizontal, vertical, and rectangular colors is considered in the same way in other figures in Fig. 4.
- Figure 4 (b) shows the case where the value of the biological parameter identifier “IKs” is taken from “0” to “5.0” and the value of “IK1” is taken from “0.2” to “2.00”. It is a figure which shows the value of APD30.
- Figure 4 (c) shows the APD30 when the value of the biological parameter identifier “IKs” is taken from “0” to “5.0” and the value of “IKr” is taken from “0” to “5.0”. It is a figure which shows the value of.
- Figure 4 (d) shows the case where the value of the biological parameter identifier “IKr” is taken from “0” to “5.0” and the value of “IK1” is taken from “0.2” to “2.00”. It is a figure which shows the value of APD60.
- Figure 4 (e) shows the case where the value of the biological parameter identifier “IKs” is taken from “0” to “5.0” and the value of “IK1” is taken from “0.2” to “2.00”. It is a figure which shows the value of APD60.
- Figure 4 (f) shows the APD60 when the value of the biological parameter identifier “IKs” is taken from “0” to “5.0” and the value of “IKr” is taken from “0” to “5.0”. It is a figure which shows the value of.
- Figure 4 (g) shows the case where the value of the biological parameter identifier “IKr” is taken from “0” to “5.0” and the value of “IK1” is taken from “0.2” to “2.00”. It is a figure which shows the value of APD90.
- Figure 4 (h) shows the case where the value of the biological parameter identifier “IKs” is taken from “0” to “5.0” and the value of “IK1” is taken from “0.2” to “2.00”. It is a figure which shows the value of APD90.
- Figure 4 (i) shows the APD90 when the biological parameter identifier “IKs” is taken from “0” to “5.0” and the “IKr” is taken from “0” to “5.0”. It is a figure which shows the value of.
- FIG. 5 (a) is a table holding a plurality of records having “ID”, “IKs”, “IK1”, “APD30”, “APD60”, and “APD 90”.
- ID is information for identifying a record and exists for record management in the table.
- IKs identifies biological parameters Child “IKs” value
- IK1 is the value of the biological parameter identifier
- IK1 is the value of the biological parameter identifier
- FIG. 5 (b) is a table showing the relationship between the values of the biological parameter identifiers “IKs” and “IK1” and “APD30”, “APD60”, and “APD90”.
- FIG. 5 (c) is a table showing the relationship between the values of the biological parameter identifiers “IKs” and “IKr” and “APD30”, “APD60” and “APD90”.
- FIG. 4 is a view displayed by acquiring the information of FIG. It is possible to obtain the values of APD30, APD60, and AOD90 from the waveform by a known technique.
- action potential waveform information shown in FIG. 6 is input.
- the waveform information receiving unit 12 inputs the action potential waveform information shown in FIG.
- the waveform information comparison unit 131 acquires action potential information that is information indicating the action potentials of the APD 30, APD 60, and APD 90 in the action potential waveform information received by the waveform information receiving unit 12.
- the waveform information comparison unit 131 acquires 78 for APD30, 119 for APD60, and 123 for APD90.
- the waveform information comparison means 131 performs all the reconstructed action potential waveform information from the first to the acquired "APD30: 78", "APD60: 119", "APD90: 123” Find the degree of approximation of.
- the reciprocal of the sum of absolute values of the difference between the APD value of the reconstructed action potential waveform information and the acquired APD value is used as the approximation.
- a specific method for calculating the degree of approximation is shown below.
- the waveform information comparison unit 131 calculates the absolute value of the difference between the APD30 value “78” and the APD30 value in the reconstructed action potential waveform information, that is, “I 78-93
- the waveform information comparison means 131 Calculate the absolute value of the difference between the APD90 value “123” in the potential waveform information and the APD90 value.
- the approximation management table holds one or more records with “ID”, “IKr”, “IK1”, riKsj, “sum of differences”, and “approximation”.
- ID is information for identifying a record and exists for record management in the table.
- riKrJ ⁇ “IKs” is the value of each biological parameter.
- the “sum of differences” and “approximation” are the values obtained above.
- the waveform information comparing means 131 obtains the degree of approximation for all combinations of the values of “IKr”, “IK1”, and “I KsJ” altogether.
- the biological parameter information output unit 14 outputs the values of “IKr”, “IK1”, and “IKs”.
- Figure 8 shows an example of such output.
- the action potential waveform information obtained after the administration of the drug “ABC” is input, and the value of the obtained biological parameter is compared with the above, whereby the drug effect can be compared numerically.
- a biological parameter indicating an effect such as drug input is output.
- a biological parameter output device can be provided.
- a powerful biological parameter output device reduces the number of drug evaluation tests and enables quick evaluation of drug efficacy. Thus, the drug discovery process can be shortened.
- the value of the biological parameter when the drug “ABC” is introduced is output.
- the biological parameter output device is an activity of a patient suffering from a disease.
- the potential waveform information may be received, and the value of the vital patient's biological parameter may be output. This treatment has the effect of estimating the patient's illness and administering the appropriate drug.
- the operation of the biological parameter output device has been described using three types of biological parameters for the sake of simplicity.
- the biological parameters of interest are usually hundreds.
- the reconstructed action potential waveform information is evaluated omnially in order to determine the biological parameter.
- the values of the biological parameter are sorted.
- a search method such as narrowing down the reconstructed action potential waveform information to be searched at an early stage using an algorithm such as binary search.
- methods such as the hybrid 'tree' index method, experiment design method, genetic algorithm, re-steep descent method, and response phase method.
- the degree of approximation between the input action potential waveform information and the reconstructed action potential waveform information is obtained. It goes without saying that the degree of approximation between the input action potential waveform information and the reconstructed action potential waveform information may be obtained using other information in the table. However, it is preferable to use the three action potential information of APD30, APD60, and APD90 from the viewpoint of the characteristics of the action potential waveform and the speeding up of the processing.
- the reconstructed action potential waveform information is a biometric parameter set including one or more biometric parameter sets as input, and is information acquired using simulation. For example, input manually It may be information. Further, the reconstructed action potential waveform information may be information acquired by a simulator or an experimental measurement device that the biological parameter output device does not have. In addition, the above-described biological parameter output device has an action potential wave. Instead of the shape, the time series value indicating the behavior of an arbitrary living body may be input as actual waveform data, and the biological parameter may be output using an arbitrary simulation that can reproduce the waveform input as the living body simulation. That is, the information from which the biological parameter is acquired is not limited to action potential waveform information.
- the waveform information storage unit is a biological parameter identifier that identifies a biological parameter and a biological parameter value that is identified by the biological parameter identifier. It has one or more biological parameter information that is a set of parameter values, and real waveform data that is a time-series value indicating the behavior of an arbitrary biological body, and the waveform information receiving unit receives the information obtained from the biological force,
- the biological parameter information acquisition unit acquires one or more biological parameter information based on information received by the waveform information reception unit.
- time-series values indicating the behavior of an arbitrary living body are real waveform data. These are time-series data such as electrocardiogram waveforms, blood pressure time-series data, cardiac output time-series data, blood glucose levels and blood oxygen levels. Examples of biological parameters that affect these waveforms include myocardial contractility.
- the biological parameter output device in the case of applying power is different from the biological parameter output device described above in that the waveform information receiving unit receives arbitrary time-series value data indicating the behavior of the biological body, and the biological parameter
- the information acquisition unit is a biological parameter output device that acquires one or more pieces of biological parameter information based on information received by the waveform information reception unit.
- the method and the program accept arbitrary time series value data indicating the behavior of the living body in the waveform information accepting step with respect to the method and the program, and the biological parameter information obtaining step! And a method and program for acquiring one or more pieces of biological parameter information based on the information received in the waveform information receiving step.
- the following biological parameter output method may be realized. That is, this method includes a waveform information receiving step for receiving an input of action potential waveform information, which is information related to an action potential waveform, and biological parameter information for acquiring one or more pieces of biological parameter information based on the action potential waveform information.
- a biological parameter output method comprising: an acquisition step; and a biological parameter information output step for outputting one or more biological parameter information acquired in the biological parameter information acquisition step.
- the processing in the present embodiment may be realized by software. This software may be distributed by software download or the like. In addition, this software may be recorded and distributed on a recording medium such as a CD-ROM.
- the software that realizes the biological parameter output apparatus in the present embodiment is the following program.
- this program receives a waveform information receiving step for receiving an input of action potential waveform information, which is information related to action potential waveforms, and one or more pieces of biological parameter information based on the action potential waveform information and experimental information.
- the computer that executes this program may be a single computer or a plurality of computers. In other words, either centralized processing or distributed processing can be performed.
- each process may be realized by centralized processing by a single apparatus (system), or a plurality of apparatuses. It may be realized by being distributed by.
- the biological parameter output device has an effect of being able to estimate biological parameters indicating effects such as drug injection, and the like, a simulation device used for drug discovery, etc. Useful as.
- FIG. 1 is a block diagram of a biological parameter output device.
- FIG. 3 is a flowchart for explaining the operation of the biological parameter output device.
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/660,746 US7516017B2 (en) | 2004-08-26 | 2005-08-22 | Biological parameter output apparatus and program |
JP2006531894A JP4710021B2 (ja) | 2004-08-26 | 2005-08-22 | 生体パラメータ出力装置およびプログラム |
EP05780370A EP1783490A4 (en) | 2004-08-26 | 2005-08-22 | BIOPARAMETER OUTPUT DEVICE AND PROGRAM |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2004246134 | 2004-08-26 | ||
JP2004-246134 | 2004-08-26 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2006022226A1 true WO2006022226A1 (ja) | 2006-03-02 |
Family
ID=35967438
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2005/015209 WO2006022226A1 (ja) | 2004-08-26 | 2005-08-22 | 生体パラメータ出力装置およびプログラム |
Country Status (4)
Country | Link |
---|---|
US (1) | US7516017B2 (ja) |
EP (1) | EP1783490A4 (ja) |
JP (1) | JP4710021B2 (ja) |
WO (1) | WO2006022226A1 (ja) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2017138323A (ja) * | 2011-09-29 | 2017-08-10 | ウィリアム・ブレイクリー | バイオドシメトリパネルおよび方法 |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2010032132A1 (en) * | 2008-09-17 | 2010-03-25 | Med-El Elektromedizinische Geraete Gmbh | Stimulus artifact removal for neuronal recordings |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH08280644A (ja) * | 1995-03-29 | 1996-10-29 | Siemens Ag | 心臓の電気的活動の部位決定方法 |
JPH08289877A (ja) * | 1995-04-24 | 1996-11-05 | Toshiba Corp | 組織の興奮伝播過程のシミュレーション方法及びこの方法を使用した組織内電磁気現象診断装置 |
JPH10323335A (ja) * | 1997-05-26 | 1998-12-08 | Toshiba Corp | 心臓内電気現象の診断装置およびその診断方法 |
JP2000163397A (ja) * | 1998-11-26 | 2000-06-16 | Sony Corp | 情報処理装置および方法、並びに提供媒体 |
JP2002537008A (ja) * | 1999-02-03 | 2002-11-05 | フィジオム・サイエンスィズ・インコーポレーテッド | 心臓をコンピュータによってモデリングする装置および方法 |
JP2004508073A (ja) * | 2000-06-22 | 2004-03-18 | フィジオム・サイエンスィズ・インコーポレーテッド | 臓器でのタンパク質発現をモデル化するためのコンピュータ計算システム |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS61119252A (ja) | 1984-11-15 | 1986-06-06 | コーリン電子株式会社 | 動脈硬化度測定方法および装置 |
JPH0315439A (ja) | 1989-06-13 | 1991-01-23 | Koorin Denshi Kk | 生理年齢測定装置 |
JPH0816551A (ja) | 1994-07-04 | 1996-01-19 | Lion Corp | 生体内拡散のシミュレーション方法及び装置 |
US7266457B1 (en) * | 1999-05-21 | 2007-09-04 | Hesperos, Llc | High throughput functional genomics |
US20060089824A1 (en) * | 2002-05-30 | 2006-04-27 | Peter Siekmeier | Methods and systems for drug screening and computational modeling |
AU2003257703A1 (en) * | 2002-08-27 | 2004-03-19 | Dainippon Pharmaceutical Co., Ltd. | Vital sign display and its method |
-
2005
- 2005-08-22 WO PCT/JP2005/015209 patent/WO2006022226A1/ja active Application Filing
- 2005-08-22 US US11/660,746 patent/US7516017B2/en not_active Expired - Fee Related
- 2005-08-22 JP JP2006531894A patent/JP4710021B2/ja active Active
- 2005-08-22 EP EP05780370A patent/EP1783490A4/en not_active Withdrawn
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH08280644A (ja) * | 1995-03-29 | 1996-10-29 | Siemens Ag | 心臓の電気的活動の部位決定方法 |
JPH08289877A (ja) * | 1995-04-24 | 1996-11-05 | Toshiba Corp | 組織の興奮伝播過程のシミュレーション方法及びこの方法を使用した組織内電磁気現象診断装置 |
JPH10323335A (ja) * | 1997-05-26 | 1998-12-08 | Toshiba Corp | 心臓内電気現象の診断装置およびその診断方法 |
JP2000163397A (ja) * | 1998-11-26 | 2000-06-16 | Sony Corp | 情報処理装置および方法、並びに提供媒体 |
JP2002537008A (ja) * | 1999-02-03 | 2002-11-05 | フィジオム・サイエンスィズ・インコーポレーテッド | 心臓をコンピュータによってモデリングする装置および方法 |
JP2004508073A (ja) * | 2000-06-22 | 2004-03-18 | フィジオム・サイエンスィズ・インコーポレーテッド | 臓器でのタンパク質発現をモデル化するためのコンピュータ計算システム |
Non-Patent Citations (1)
Title |
---|
See also references of EP1783490A4 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2017138323A (ja) * | 2011-09-29 | 2017-08-10 | ウィリアム・ブレイクリー | バイオドシメトリパネルおよび方法 |
JP2020193983A (ja) * | 2011-09-29 | 2020-12-03 | ザ ヘンリー エム ジャクソン ファンデイション フォー ザ アドヴァンスメント オブ ミリタリー メディシン インコーポレイテッド | バイオドシメトリパネルおよび方法 |
JP7220185B2 (ja) | 2011-09-29 | 2023-02-09 | ザ ヘンリー エム ジャクソン ファンデイション フォー ザ アドヴァンスメント オブ ミリタリー メディシン インコーポレイテッド | バイオドシメトリパネルおよび方法 |
Also Published As
Publication number | Publication date |
---|---|
JP4710021B2 (ja) | 2011-06-29 |
EP1783490A1 (en) | 2007-05-09 |
EP1783490A4 (en) | 2012-01-04 |
US20070255504A1 (en) | 2007-11-01 |
JPWO2006022226A1 (ja) | 2008-05-08 |
US7516017B2 (en) | 2009-04-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Wager et al. | Optimization of experimental design in fMRI: a general framework using a genetic algorithm | |
JP2020530634A (ja) | 病状診断のための機械学習法などの機械学習法において使用する新規特徴の発見 | |
CN101297297A (zh) | 医疗风险分层方法和系统 | |
KR20210108376A (ko) | 콘텐츠를 특징화하기 위해 뇌 특성 활동 맵 데이터베이스를 활용하기 위한 장치 및 방법 | |
JP2007312923A (ja) | 生体器官の機能のシミュレーションシステム及びそのプログラム | |
JP2020530933A (ja) | 機械学習法において使用するゲノムの発見 | |
Skaar et al. | Estimation of neural network model parameters from local field potentials (LFPs) | |
CN108135520A (zh) | 从功能性大脑图像生成心理内容的自然语言表示 | |
Naranjo et al. | Addressing voice recording replications for tracking Parkinson’s disease progression | |
Gerling et al. | Computation predicts rapidly adapting mechanotransduction currents cannot account for tactile encoding in Merkel cell-neurite complexes | |
Piacentino et al. | Generating fake data using GANs for anonymizing healthcare data | |
Narayanan et al. | An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging | |
Procopio et al. | Experimental modeling and identification of cardiac biomarkers release in acute myocardial infarction | |
Caner et al. | The programmable ECG simulator | |
Sorochynskyi et al. | Predicting synchronous firing of large neural populations from sequential recordings | |
WO2006022226A1 (ja) | 生体パラメータ出力装置およびプログラム | |
JP5100979B2 (ja) | 生体シミュレーションシステム及びコンピュータプログラム | |
Dubey et al. | Predicting diabetic neuropathy risk level using artificial neural network and clinical parameters of subjects with diabetes | |
Naranjo et al. | Replication-based regularization approaches to diagnose Reinke's edema by using voice recordings | |
Boissel et al. | Modelling methodology in physiopathology | |
Moody | Approximate Entropy (ApEn) | |
Lopez-Chamorro et al. | Cardiac pulse modeling using a modified van der pol oscillator and genetic algorithms | |
Jin et al. | Estimating ectopic beat probability with simplified statistical models that account for experimental uncertainty | |
WO2007105420A1 (ja) | 生体パラメータ決定装置、およびプログラム | |
Procopio et al. | A combined simulation and machine learning approach to classify severity of infarction patients |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BW BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE EG ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KM KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NA NG NI NO NZ OM PG PH PL PT RO RU SC SD SE SG SK SL SM SY TJ TM TN TR TT TZ UA UG US UZ VC VN YU ZA ZM ZW |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): GM KE LS MW MZ NA SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LT LU LV MC NL PL PT RO SE SI SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
WWE | Wipo information: entry into national phase |
Ref document number: 2006531894 Country of ref document: JP |
|
WWE | Wipo information: entry into national phase |
Ref document number: 11660746 Country of ref document: US |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2005780370 Country of ref document: EP |
|
WWP | Wipo information: published in national office |
Ref document number: 2005780370 Country of ref document: EP |
|
WWP | Wipo information: published in national office |
Ref document number: 11660746 Country of ref document: US |