TWI270363B - Systems and methods for automated ventilator waveform recognition and measure based on ontologies - Google Patents

Abstract

Methods for automated ventilator waveform recognition and measure based on ontologies are provided. A first instant and a first pressure of a first significant point corresponding to an actual ventilator waveform are provided. A second instant and a second pressure of a second significant point corresponding to the actual ventilator waveform are provided. A slope between the first and second significant points is accordingly calculated. A degree of slope possibility distribution corresponding to the calculated slope is acquired according to information regarding a slope possibility distribution. The acquired degree of slope possibility distribution is displayed.

Description

1270363 策 九, invention description: [Technical field of invention] This invention is a computer-aided technology for medical treatment, in particular, an automatic breathing waveform interpretation and measurement method and system based on knowledge ontology. [Prior Art] The pressure, time, flow rate_time, volume_time, and grain-pressure map displayed on the respirator monitoring screen have become an indispensable information for the diagnosis of respiratory therapy. At present, the thoracic specialists are diagnosed with the patient's respiratory related symptoms by auscultation with the respiratory parameter _ breathing parameter value, but this is not easy to be accurate for the severity of the patient's respiratory disease (relative to the normal condition). The determination of the value of 畺, so this patent proposes a respiratory waveform interpretation, measurement, mechanism and system based on the knowledge ontology, which can interpret the respiratory airway pressure, respiratory time and respiratory waveform slope probability distribution of a complete cycle of respiratory waveforms, and The degree of difference from the normal waveform is measured to quantify its deviation from normal severity, providing the physician with a more accurate judgment. SUMMARY OF THE INVENTION Because of the large number of respiratory patients, the current pressure-time, flow-time, volume-time and volume_pressure maps displayed on the respirator monitoring surface have become an indispensable part of the diagnosis of respiratory therapy. Capital. For example, the thoracic specialists diagnose the respiratory-related conditions of the patient by auscultation with the values of the respiratory parameters measured by the respirator, but this is not easy to accurately quantify the severity of the respiratory condition of the patient (relative to the normal condition). The determination of the value. The object of the present invention is to solve the problem that the upper it is based on fuzzy logic, and then construct a set of intelligent respiratory wave sputum judgment mechanism and system based on knowledge ontology to save medical resources. By establishing a respiratory airway pressure probability distribution' and a breathing time probability distribution, and then using the fuzzy waveform slope construction algorithm (Fuzzy Wavefonn 'SlQpe e()n_etic)n Algorithm: FWSCA) to infer the respiratory airway pressure versus breathing time The respiratory waveform slope probability distribution is further calculated to further calculate the likelihood that the input respiratory waveform is a normal waveform. According to the above object, an embodiment of the present invention discloses an automatic breathing wave based on the knowledge ontology Chenfs Docket N〇.: ACI94022 s Docket No:0213-A40656-TW/Final/Jonah/20051117 5 1270363 - Shape · cum green, by - In the department of the department, the branch includes: the first position in the actual call form - the breathing time _ and the first - respiratory airway pressure, and the second characteristic point corresponding to the actual respiratory waveform The second beer suction time point and the second respiratory airway pressure 2 are based on the first-breathing time point, the first-breathing airway pressure, the second breathing time point and the second respiratory airway pressure, and the beta-characteristic-characteristic point and the second characteristic point The slope of the respiratory waveform; the degree of membership of the respiratory waveform minus the slope of the respiratory waveform is obtained based on the information of the slope of the respiratory waveform; and the degree of membership of the respiratory waveform is displayed. According to another embodiment of the present invention, a brain-reading bribery medium is used for storing a computer program, and a brain program is used to carry a person to an electric age towel and enable the electronic age system to perform the automation based on the knowledge ontology as described above. Respiratory waveform interpretation and measurement method. The embodiment of the invention further discloses an automatic breathing waveform interpretation and measurement system based on the knowledge ontology, comprising an output unit and a processing unit. The processing unit is coupled to the output unit for providing a first breathing time point corresponding to the first feature point in the actual respiratory waveform and the first respiratory airway pressure, and a second corresponding to the second characteristic point in the actual respiratory waveform a breathing time point and a second breathing airway pressure; calculating a Hulu between the first feature point and the second feature point according to the first breathing time point, the first breathing airway pressure, the second breathing time point, and the second respiratory airway pressure The slope of the waveform is absorbed; according to the probability distribution information of the slope of the respiratory waveform, the degree of membership of the respiratory waveform corresponding to the slope of the respiratory waveform is obtained; and the degree of membership of the respiratory waveform is displayed through the output unit. Among them, the probability distribution information of the slope of the respiratory waveform is obtained by using a training method. [Embodiment] FIG. 1 is a diagram showing a hardware structure diagram of an automatic breathing waveform judgment and measurement system based on an ontology according to an embodiment of the present invention, including a processing unit 11, a memory 12, a storage device 13, The output device 14, the input device 15, and the communication device 16 are connected together using the bus bar 17. In addition, those skilled in the art can implement this system on other computer system configurations, such as hand-held devices, multi-processor systems,

Client's Docket No.: ACI94022 TT^ Docket No:0213-A40656-TW/Final/Jonah/20051117 8 1270363 Λ Microprocessor-based or programmable consumer electronics (miCr〇process〇r_baSed οι* consumer Electronics), network computers, mini computers, mainframes and similar devices. The processing unit 11 may comprise a single central processing unit (central_pr〇cessing_cpu) or a plurality of flat 5 line processing units associated with the parallel computing environment __processing. 3 Recalling body 12 contains read-only memory (1^〇11 to 11^111〇1^; 1^〇]^), flash memory (£^11〇]\4) and/or dynamic access memory体(聪(1〇1)1咖娜11^111()1^1^]^,$ to store program modules and data for processing single it11. In general, the program module contains the sequence (routines), program deduction (four), object (object), component (c〇mp〇nent), etc., for performing the e-learning sequence editing system function. The invention can also be implemented in a decentralized computing environment, • its computing work Executed by a remote processing device connected to the communication network. In a decentralized environment, the function of the automated breathing waveform interpretation and measurement system based on the knowledge ontology is performed, perhaps by local and multiple remote computer systems. The storage device 13 includes a hard disk device, a floppy disk device, a compact disk device or a flash drive device for reading a program module and/or data stored in a hard disk, a floppy disk, a compact disk, a flash drive, and the like. An exemplary breathing waveform knowledge ontology architecture diagram is provided according to an embodiment of the present invention. The respiratory waveform knowledge body 200 can Stored in the memory 12 (Fig. 1) or the storage device 13 (Fig. 1), an object consisting of the domain layer 210, the main class layer 23, the sub-category layer 250, and the concept layer 270. A guided knowledge ontology architecture. The main class layer 23 includes a pressure versus time waveform, a volume versus time waveform, a flow versus time waveform, a pressure vs. volume waveform, and a flow versus volume waveform. The subcategory layer 250 includes The respiratory time probability distribution, the respiratory airway pressure probability distribution, and the respiratory waveform slope probability distribution are sub-categories. The conceptual layer 27〇 is composed of a physiological parameter layer and a symptom layer 273. The physiological parameter layer 271 includes breathing time and respiratory airway pressure. , waveform slope, lung compliance, pulmonary physiology, respiratory work, arterial blood gas, analysis, etc. (c_ept), and the association between concepts (associati〇ns). Symptom layer 273 contains gas%, chronic bronchi Concepts such as inflammation, bronchiectasis, pneumoconiosis, pulmonary fibrosis, and the association between concepts.

Client 5s Docket N〇.:ACI94022 TT5s Docket No:〇213-A40656-TW/Final/J〇nah/20051117

(I 7 1270363 Fig. 3 shows a normal respiratory waveform according to an example of an embodiment of the present invention, including initial airway pressure, peak pressure plus pressure, plateau pressure (9) such as pressure), and end-expiration Pressure ^p〇skive end_expi plus ry pressure), inspiration time and exhalation time (eXpirati〇n time) and other information. Typically, each breathing waveform contains six feature points A through F. The automatic ontology waveform interpretation and measurement method based on the knowledge ontology of the invention is divided into two stages: interpretation training; and actual measurement. During the interpretation training phase, provide pressure versus time information corresponding to a training breath waveform (signiflcant points, such as A to F in Fig. 3), and a respiratory airway pressure probability distribution between any two feature points (8) Such as the distribution, or pressure membership (10)) and the distribution of the possibility of breathing time, or time membership function information, according to the calculation of the probability distribution of the respiratory waveform between any two feature points (sl〇 Pe p〇ssibmty distributi〇n, sinking membership function), and constructing the respiratory waveform ontology (also known as training ontology). In the measurement phase, pressure versus time information corresponding to a feature point of an actual respiratory waveform is provided. The actual respiratory waveform can be detected by a respiratory measuring instrument to represent the respiratory waveform of a patient or subject. Then, based on the respiratory airway pressure, respiratory time and respiratory waveform slope probability distribution information between any two feature points obtained during the training phase, the respiratory airway pressure and breathing time of any one of the actual respiratory waveforms are calculated and displayed. The degree of membership of the slope of the respiratory waveform between any two feature points. When the calculated degree of membership is closer to "1", the respiratory wave pressure between the respiratory airway pressure and the specific feature point of the specific feature point in the actual respiratory waveform is closer to the normal situation. Conversely, the more the degree of membership after the calculation deviates from "1", the more the respiratory wave pressure, the breathing time, and the slope of the respiratory waveform between the specific feature points representing the specific feature points in the actual respiratory waveform deviate from the normal situation. Please refer to the following instructions for implementation details in the two phases. Fig. 4 is a diagram showing an automatic breathing waveform interpretation and measurement interpretation training method according to an embodiment of the present invention. In step S411, a pressure pair corresponding to a feature point of a training respiratory waveform is provided

Client’s Docket No·: ACI94022 TT5s Docket No:0213-A40656-TW/Final/Jonah/20051117 1270363

Time information. This information can be entered from a file or database, or it can be entered via a user interface (useri blood face, m). Figure 5 is a diagram showing the pressure versus time input interface of the feature points of the training breathing waveform according to the example of the present invention, including six sub-input areas 510 to 560, corresponding to the feature points as shown in Fig. 3, respectively. A to F, each sub-input area allows the user to enter information such as characteristics _pressure and _. In step (10), the respiratory airway pressure between the two feature points is provided. Any two features related to the airway pressure probability distribution information including the starting number of the fuzzy number of supporters (10) shoulder, starting core point (begin (four), BC), ending core point _ earning, EC) and ending support point _ P〇rt, ES). This information can be calculated from the information provided in the step, from a broadcast or database to the input or can be entered through a user interface. Fig. 6a is a diagram showing the embodiment of the invention, according to the embodiment of the present invention, the squadron A _ 3 _ ah airway fine, including four input barriers, 613, 615 and 617, the subdivision of the fuzzy number "Hu Weidao pressure" The starting domain point, the start _, and the end point are the bundle support points. In step S433, the respiratory time probability distribution between any two feature points is provided. L. Any two characteristic point-like breaths _ can be distributed, including the starting support point, the starting core point, and the ending core point of the flip number. End the support point. This information can be calculated from the information provided in step s4u, entered from the health record or database, or can be entered through a use surface. Figure 6b shows an exemplary feature point a to b according to an embodiment of the present invention (the third target: suction time likelihood distribution input interface 630, comprising four input shelves 631, 633 Μ%: 纪7, respectively To let the user input the fuzzy number, the breathing time, the starting support point, the starting core point, the social beam core point and the ending support point. The person "~ in step S451, according to the respiratory airway pressure and time probability distribution Information, Yu has served as the two characteristics of the respiratory waveform slope probability distribution information. Any fine characteristic waveform slope can be used to include the initial support point of the model, the starting core point, the social core point and the end support Point. This step can use the fuzzy waveform slope construction algorithm.

Waveform Slope Construction Algorithm) to calculate between any two feature points ^

Client’s Docket No···ACI94022 TT5s Docket No:0213-A40656-TW/Final/Jonah/20051117 9 1270363

Waveform slope probability distribution information, fuzzy waveform slope construction algorithm is shown below. Rounds · Pbs, Pbc, Pec, Pes, TBS, TBC, TEC, TES Round: ~,, ~ Step 1 : Calculate the four possible starting core points and ending core points of the respiratory waveform slope:

PbcITbc, pbcItec, PecItbc, Pecitec Step 2: Calculate the four possible starting and ending support points for the slope of the respiratory waveform:

PbS / ^BS 5 ^BS / TES ? PES / TBS , PES / TES Step 3 : Get the starting support point , starting core point , ending core point and ending support point of the respiratory waveform slope · · sBS Mm, PBS /TBS, pbsItes, pjTbs, pjTe" sBC =MIN(p,c/r5C5 pbc!tec, pec/tbc, pec/Tec) sEC =MAX{pbc/Tbc, pbc!tec, pec/Tbc, pec/Tec) sES -MAX(p^/r^5 pbsItes, pes/tbs^ pes/tes) Step 4: End the different input parameters of the different method, the table depends on the test, the ah, the gas, the support point P5C is the input parameter of the program, indicating the fuzzy number, the respiratory airway migration force, and the starting nuclear point; ~ is the input parameter of the program, indicating the fuzzy number ', the air pressure, and the ending core point; 7 is The program's input record, the table slightly _, 'Hu Wei touch force' read the bundle thief for the process of losing 4 numbers, indicating the fuzzy number, breathing time, the starting support point, the input parameter of the program The touch between the office is the program's wheelman parameter, which means that the fuzzy art fish, the end point of the 'day button' is the end of the program, the output parameter of the program, indicating the fuzzy number, and the respiratory wave is “σ support point”~ formula The output parameters indicate the modulus:,, the slope of the respiratory waveform, the starting core point of the husband, the output parameter of the program, the fuzzy number, the slope of the respiratory waveform, and the end of the cycle, such as ^ 6^1丝翻数,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 5 of ^

Client’s Docket No·: ACI94022 wke(10)细.Α4·τ卿读_2_i7 10

Ci 1270363 is used to display the calculated fuzzy number "respiratory waveform slope", the initial support point, the end core point and the end support point, respectively. The starting core is in step S47; l, constructing the corresponding body corresponding to the respiratory waveform 2〇〇 (Fig. 2) Respiratory waveform knowledge base (kn〇wledge base). The knowledge base contains information on the distribution of beer inhalation and probability of any two feature points provided, and the construction of the slope of the profit_waveform The algorithm is different from the residual waveform of the respiratory waveform between the two feature points. The seventh _ represents the actual == method of the automatic respiratory waveform interpretation and measurement according to the embodiment of the present invention. ^ Step S7U, A pressure "between ring" corresponding to a characteristic point of an actual respiratory waveform is provided. For example, the characteristic points (Z7,...,jr„) of the respiratory waveform provided, especially = household 7, where Ρι,·.·, ρ" represent the respiratory airway of a particular feature point ( = "And 'U' - the representative - (four) fixed feature points, 瞒 。. This Wei can be entered by a standard or database, or can be input through a user interface. For example _ : Ben In the embodiment of the invention, the characteristics of the actual call-reading form are as follows: the pressure input device (10) (the basin: the sub-input areas 811, 813, 815 and 817, the pressure and time of the 可 疋 疋 每 每 每 每 每 每 每 每 每 每 疋 疋 疋 输入For information, refer to Section 7®, in step S731, according to any two features corresponding to the I energy distribution information (shown in step (10) in Figure 4), take _ = 1 meaning - a characteristic point of breathing The degree of subordination of airway diligence. In the step coffee, according to the data of the hand, the information on the possibility of breathing time between the two feature points (as shown in Figure 4), taking any of the features of the force versus time information The call of the point is in step S751, and the breathing between any two feature points in the time information is calculated (sl_, any The respiratory waveform between the two feature points is used as follows: ^ ^Step S753 'According to the domain __ Overview of the information (as shown in step 4 of the fourth wealth), take the suspension = the knives The degree of the respiratory wave rate between the points, any two of the money is opposite to the step S77; I, through the output unit 14 (the third

Client's Docket N〇.: ACI94022 TT^s Docket N〇:0213-A40656-TW/Final/J〇nah/20051117 1270363 'Figure' shows the calculation results of each degree of membership on a display. The Sb diagram shows the appearance of the reading surface 83G according to the present invention. The towel contains the characteristic point A (as shown in Fig. 2) of the respiratory airway pressure &gt;|gambling (3), point B (such as 帛2 _ pepper ah airway pressure ^ degree of membership 833, characteristic point a of the respiratory time of the degree of membership 835, feature point B of the beer owing between the sub-granularity 837 and the characteristic point a and B between the respiratory waveform slope Degree of membership, etc. - Beyond. Specifically, when the input respiratory waveform feature points A = (7 5, 〇 25) and the feature points b = (22 5, 〇 3), then the feature point A is threatened by this force. The degree of probability distribution of sexual distribution and time is 1. The degree of characteristic point B belongs to this Jianli can be distributed in time and the age of (4) is also #1 (refer to the picture as you figure) and the characteristic point A to the characteristic point B The slope formed, to the extent that this slope is likely to be distributed, is also referred to in Figure 6c. $ 9 ® Example of a computer-readable storage medium based on knowledge ontology for automated respiratory waveform interpretation and measurement. This storage medium is 9〇, which is used to store a computer program 92G. It is a description of the knowledge of the Society's automated magnetic reading and measurement methods (including Ji Na and Shi (4) Finance). The method and the button of the present invention, such as a school type or a part thereof, may be included in a physical medium such as a floppy disk, a CD, a hard disk, or any other machine (such as a computer). The storage medium is read, wherein when the code is accepted by the machine, 15, if the computer is loaded and executed, the machine becomes a device for participating in the present invention. The method and apparatus of the present invention may also be transmitted in a code format through some transmission medium such as a wire or a fiber, an optical fiber, or any transmission type, wherein when the code is loaded by the machine, such as electricity, When executed, the machine becomes a device for participating in the present invention. When the general-purpose processing unit (general-pu-ep-sing_implementation), the code-integrated processor provides a unique device that operates similarly to the application-specific logic circuit. Although the present invention has read the good-looking trace as above, And </ RTI> </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt;

Clienfs Docket No. :ACI94022 TT s Docket No:0213-A40656-TW/Final/Jonah/20051117

12 1270363 • Fig. 1 is a diagram showing the hardware structure of the automatic respiratory waveform judgment and reading based on the knowledge ontology according to an embodiment of the present invention; and Fig. 2 is a diagram showing an example respiratory waveform knowledge ontology according to an embodiment of the present invention. FIG. 3 is a diagram showing a normal respiratory waveform according to an example of an embodiment of the present invention; FIG. 4 is a diagram showing an automatic breathing waveform interpretation and measurement interpretation training method according to an embodiment of the present invention; Example of the embodiment of the invention trains the pressure versus time input interface of the feature points of the respiratory waveform; #图 6a shows the respiratory airway pressure probability distribution input interface between the example feature points A to B according to an embodiment of the invention; The breathing time likelihood distribution input interface between the example feature points a to B according to the embodiment of the present invention is shown; the brother 6c diagram shows the probability distribution of the beer suction waveform slope between the example feature points a to B according to the embodiment of the present invention. Display interface; Figure 7 shows an actual measurement method for automatic respiratory waveform interpretation and measurement according to an embodiment of the present invention; Figure 8a shows The pressing force versus time input interface of the characteristic point of the actual respiratory waveform according to the embodiment of the present invention; the 8b is an example calculation result display interface according to an embodiment of the present invention; and the ninth figure is the embodiment according to the embodiment of the present invention. A schematic diagram of a computer readable storage medium based on knowledge ontology for automated respiratory waveform interpretation and measurement. [Main component symbol description] 10~Automatic respiratory waveform interpretation and measurement system; 11~ processing unit; 12~memory; 13~ storage device; 14~output device; 15~ input device; 16~ communication device; Row; 200~ respiratory waveform knowledge ontology; 210~ domain layer; 230~ main category layer; 250~ sub-category layer; 270~ phase non-layer; 271~ physiological parameter layer; 273~ symptom layer; A, B, C, D, E, F ~ feature points; S411,

Client's Docket N〇.: ACI94022 13 TT5s Docket No:0213-A40656-TW/Final/Jonah/20051117 1270363 ... S43 Bu S433, S451, S47l~ method steps; 500~ feature point pressure versus time rounding interface; 510, 520, 530, 540, 550, 560~ sub-input area; 610~ respiratory airway pressure possibility distribution input interface; 611, 613, 615, 617~ sub-input field; 630~ breathing time possibility distribution input interface; 63 633, 635, 637~ sub-input field; 650~ respiratory waveform slope probability distribution display interface; 651, 653, 655, 657~ display field; S711, S731, S733, S751, S753, S771~ method step; ~ characteristic point pressure versus time input interface; 81丨, 813, 815, 817~ sub-input area; 830~ calculation result display interface; 831~ feature point A's degree of respiratory airway pressure; 833~ feature point B breath Degree of membership of airway pressure; 835~feature point a • degree of subordination of breathing time; degree of subordination of breathing time of 837~feature point B; 839 lust point • degree of membership of respiratory waveform slope between A and B; ~健存Media; 92〇~ Based on the knowledge ontology Automatic breathing waveform interpretation and measurement computer program.

Client’s Docket N〇_: ACI94022 TT5s Docket No:0213-A40656-TW/Final/Jonah/20051117

Claims (1)

12703丨 k 94145529 September 22, 1995 X. Patent application scope: ^年? The monthly A-day repair (more) original ----- 1 1 · A secret knowledge of the body of the automatic breathing waveform interpretation and measurement method, is managed, the method includes the following steps: ,, provide the corresponding - in the actual respiratory waveform _ _ feature point - first - sucking time point and a first breathing airway S force ' and corresponding to one of the second characteristic point of the actual breathing waveform, a second breathing time point and a second breathing airway pressure; Calculating a sucking waveform between the first feature point and the second feature point according to the first breathing time _, the first breathing airway pressure, the second breathing time point, and the second breathing gas lag force ' Slope; according to the probability distribution information of the slope of the respiratory waveform, obtaining the degree of membership of the respiratory waveform corresponding to one of the slopes of the respiratory waveform; and displaying the degree of membership of the respiratory waveform, wherein the probability distribution information of the slope of the respiratory waveform is used A training method comes. 2. The automatic respiratory waveform interpretation and measurement method of the threat knowledge ontology described in the patent application item i, wherein when the degree of membership of the respiratory waveform slope deviates from, τ, represents the above-mentioned first corresponding to the actual respiratory trace - The slope of the above-mentioned respiratory waveform between the feature point and the second feature point deviates from the normal state. 3. The automatic breathing waveform interpretation and measurement method of the Hermitology ontology described in the first application of the patent, wherein the training method further comprises: providing one of the first characteristic points corresponding to the - training breathing waveform a third breathing time point and a second respiratory airway pressure, and a fourth breathing time point and a fourth respiratory airway pressure corresponding to the second characteristic point in the training breathing waveform; and according to the third breathing point, The feeding three shouts _ force, the fourth breathing time point and the fourth breathing temptation, and calculates the probability distribution information of the slope of the breathing waveform. 4. For example, the third paragraph of the patent scope is the automatic breathing waveform interpretation and measurement method of the knowledge body, in which the probability distribution of the slope of the upper injection waveform is calculated. #转转_, &amp;: Client's Docket No .:ACI94022 TT's Docket No:0213-A40656-TW/Finall/Jonah/20051117 15 1270363 providing a respiratory-respiratory contact between the first feature point and the second feature point corresponding to the above-mentioned training respiratory waveform a respiratory pressure initial pressure nuclear point, a respiratory airway pressure end core point and a respiratory airway pressure end support point; providing a representation corresponding to the first characteristic point in the training breathing waveform and the second contour point - Breathing_Starting support point, - Breathing time starting core point' - ah time ending core point and one breathing time ending support point; dividing the above instrumental pressure starting core point by the above breathing time starting core point Obtain a first possible slope core point; divide the above-mentioned respiratory airway pressure starting core point by the above-mentioned breathing time county core point to obtain a second possible slope core point; Get a third to divide the above-mentioned respiratory airway pressure end core point by the above-mentioned breathing time start nuclear possible slope core point; heart, point to obtain a fourth to divide the above-mentioned respiratory airway pressure end core point by the above breathing time to end the nuclear possible Slope core point; person obtains a first · divide the above-mentioned respiratory airway pressure starting support point by the above breathing time starting support point with a possible slope support point; divide the above beer inhalation from the initial support point by the above beer suction time End point to obtain a first. Divide the above respiratory airway pressure end support point by the above breathing time to support the possible slope support point; Possible =:: Face force end finely divided by the caller Pointing to the first of the first, second, third, and fourth possible slope support points as the starting point of the respiratory waveform slope support point; the above-mentioned -n and fine-decide rate core-doping waveform Starting core point; this oblique sheep core ~ Zhantian Clienfs Docket N〇.: ACI94022 TTJs Docket No:0213-A40656-TW/Finall/J〇nah/20051117 16 1270363 I, Shangyu*Α- . The largest possible slope core point of the younger, second, third, and fourth possible slope core points as the -respiration waveform slope ends the core point; 'the second, third, and fourth possible slopes support the maximum possible slope support of the towel Point t do - breath waveform slope end support point, ,, ', the above call and waveform slope start support point, the above respiratory waveform slope start core point, the above breathing, skewed miscellaneous heart to the above breath Na na end Yao minus The probability distribution information of the above-mentioned respiratory waveform slope. The automatic breathing waveform interpretation and quantity Φ measuring method of the knowledge ontology described in the fourth aspect of the patent scope, wherein the training method further comprises: -, corresponding to the first characteristic point in the above-mentioned Weng respiratory waveform and the above The above-mentioned respiratory airway pressure initiation support point between the two feature points, the respiratory airway pressure initiation core point, the above-mentioned respiratory airway pressure end core point and the above-mentioned Huweilai force end support point are stored in one knowledge corresponding to a respiratory waveform knowledge ontology In the library; corresponding to the above-mentioned breathing point in the above-mentioned training breathing waveform and the above-mentioned second feature point, the above-mentioned breathing_starting_buying__core point, the core point of the bribe and the above breathing time Ending the support point, storing in the knowledge base; and, corresponding to the above-mentioned first feature point in the training breathing waveform and the second feature point, the respiratory waveform slope starting support point, and the respiratory waveform The slope start core point, the above-mentioned respiratory waveform slope end core point, and the above-mentioned respiratory waveform slope end support point are stored in the above In the knowledge base. 6. The automatic respiratory waveform interpretation and measurement method of the threat knowledge ontology according to claim 5, wherein the respiratory waveform knowledge body comprises a domain layer, a member layer, a primary category layer and a concept layer, The concept layer includes a parameter layer and a symptom layer. 7. If you apply for a patent fine! The method for measuring the ontology of the subject mentioned in the item further includes: 'Based on the record of the callable mine, the first respiratory airway pressure of the above-mentioned first respiratory airway pressure Degree; Client's Docket N〇.:ACI94022 TT^s Docket No:0213-A40656-TW/Finall/J〇nah/200511l7 17 "1270363 i«依啊罐力可纽纲,力力力——第nt递The degree of subordination of the force; , +3⁄41⁄23⁄4, the distribution of the poor news, obtained corresponding to the above-mentioned 帛n stomach &amp; beer time - the first degree of breathing time; according to the above-mentioned breathing time of the distribution information 'obtained corresponding to the second One of the characteristic points' one of the suction time and the second breathing time membership degree; and - the above-mentioned first-breathing airway subordinate degree, the second beer inhalation tract subordinate degree, the above-mentioned first breathing time subordinate degree and the second Breathing time membership degree, The information on the distribution of the possibility of the above-mentioned respiratory qi force includes a respiratory airway pressure starting support point, a respiratory airway pressure starting core point, a respiratory airway pressure ending core point and an aerobic force knot, and the town speaks to breath. The probability of losing the time is _ contains - the initial support point of the paste, _ beer start time start _, - breath _ end batch point and - Huer line support point. 8. The automatic respiratory waveform interpretation and measurement method of the threat knowledge ontology described in claim 7 wherein, when the degree of sub-respiratory airway pressure membership is deviated from,, Γ, represents a corresponding actual respiratory waveform The more the first respiratory airway pressure of the above-mentioned first feature point deviates from the normal situation, the more the second respiratory airway pressure deviates from the second characteristic point when the first respiratory force is more than the lion. In a normal case, when the first breathing time membership degree deviates from "1", the first breathing time corresponding to the first characteristic point of the actual breathing waveform is deviated from the normal state, and the second The more the respiratory time membership degree deviates from "”", the more the second breathing time corresponding to the second characteristic point of the actual respiratory waveform is deviated from the normal situation. 9. A computer readable storage medium for storing a a computer program for loading into a battery system and causing the computer system to perform an automated breathing based on the knowledge ontology a method for determining a reading and measuring method, the method comprising: providing a first breathing time point and a first breathing airway pressure corresponding to a first characteristic point in an actual breathing waveform, and corresponding to one of the actual breathing waveforms One of the second feature points, the second breath Client's Docket N〇.: ACI94022 TT^ Docket No:0213-A40656-TW/Finall/Jonah/20051117 18 1270363 — time point and - second respiratory airway pressure; 匕, 龙笛一, the first respiratory day custodial point, the above-mentioned first-breathing airway pressure, the second breathing time point and the oblique ^·breathing force lag force' different respiratory waveforms between the first feature point and the second feature point According to the possibility distribution information of the slope of the respiratory waveform, one of the slopes corresponding to the respiratory waveform is obtained - the degree of membership of the respiratory waveform slope; and the degree of membership of the respiratory waveform is displayed, and the probability distribution information of the slope of the respiratory waveform is used The training method is derived. _ 1G·-Automated Respiratory Waveform Interpretation and Volume Exposure System, comprising: a round-out unit; and • a processing unit coupled to the output unit to provide a corresponding feature in the actual breathing waveform, , the first-breeding point and a first respiratory airway pressure, and one of the first characteristic points corresponding to the actual beer, the second respiratory time point and a second respiratory airway Pressure, according to the above-mentioned control and the day-to-day stagnation point, the first respiratory airway pressure, the second respiratory time point, and the second respiratory airway divergence, one of the first feature points and the second feature point The slope of the respiratory waveform; according to the monthly b-spot distribution of the slope of the wave and the slope of the wave, obtaining the slope of the waveform corresponding to one of the slopes of the neutral wave and the slope of the waveform, and displaying the slope of the respiratory waveform through the output unit Degree, where 'the probability distribution information of the above-mentioned respiratory waveform slope is obtained using a training method. 11. The automated respiratory waveform interpretation and measurement system of claim 10, wherein when the degree of subordination of the respiratory waveform slope deviates from,, Γ, represents the first characteristic point corresponding to the actual respiratory waveform. The slope of the above-mentioned respiratory waveform between the second feature points and the above is deviated from the normal state. The automatic breathing waveform interpretation and measurement system of claim 10, wherein the training method performed by the processing unit further comprises: providing the first feature point corresponding to a training breathing waveform a third breathing time point and a second breathing airway pressure, and a fourth breathing time point and a fourth breathing airway pressure corresponding to the second characteristic point in the training beer suction wave opening: and Client's Docket No ·: ACI94022 TT^ Docket Νο:0213-A40656-TW/Finall/Jonah/20051117 19 1270363 According to the above third call __, the above third ah airway pressure, the above fourth breathing time point and the above fourth ambition Calculating the probability distribution of the slope of the respiratory waveform described above. 13. The automatic call according to item 12 of the patent application scope;: calculating the probability distribution information of the slope of the respiratory waveform described above, in the step of gamma, where is represented by The first feature in the above training _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ One of the beer _ touch support, _ call _ start heart point ^ point one breath time end support point; Dingmen,,, mouth east core point and a above respiratory airway pressure start core point divided by the above breathing time start Nuclear gamma information. • Possible slope core point; divide the above-mentioned call airway pressure starting core point by the above-mentioned breathing time end to pull the second possible slope core point; divide the above-mentioned respiratory airway pressure knot_heart, point by the above breathing time starting core point to three Possible slope core point; mouth/", the factory divides the above-mentioned respiratory airway pressure end core point by the above-mentioned breathing time end core point four possible slope core points; - the above respiratory airway pressure starting support point is divided by the above breathing time Start support point ~ a possible slope support point; the above-mentioned caller pressure start support point is divided by the end point of the call to find the second possible slope support point; ^ the above breath_force end support point is divided by the above Inter-start support point - three possible slope support points; divide the above-mentioned respiratory airway pressure end support point by the above-mentioned breathing time end support point to obtain ~ four possible slope support points; extend a first heart point to obtain a first one The first first Client's Docket No.: ACI94022 TT^ Docket Νο:〇213-A40656-TW/Finall/J〇nah/20051117 20 1270363 With the finest possible slope, the core of the core can be the most confusing point of view - fine _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ oblique axis core point, the above == core point and the above end of the fine composition of the suction waveform slope «==嶋13 tearing lion cryptosystem, where the upper call: ==::= force: the above - In a knowledge base; 呼:==::r:, __u describes the end of the breathing time branch, stored in the upper = two wide end nuclear _ upper (four) increased - gas mixed increase: the above-mentioned respiratory waveform slope start The support point, the start of the respiratory waveform slope starting point, the middle and the beam core point, and the end of the respiratory waveform slope support point are stored in the knowledge base. 15. The automatic respiratory waveform interpretation as described in claim 14 Cum measurement system ==:: layer,, one-, above Client's Docket No.: ACI94022 TT5s Docket No:0213-A40656-TW/Finall/Jonah/20051117 21 ! 1270363 16. As described in claim 10 The automatic breathing waveform is interpreted as a butterfly m, and the butterfly is tender and increased. One of the forces - the respiratory airway is the degree of subordination; according to the distribution information of the above-mentioned respiratory airway art, the degree of the second middle Weidao pressure corresponding to the above-mentioned * two characteristic points is obtained. Breathing _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ One of the second breathing time points = the degree of subsistence of the breathing time; and the degree of membership of the first respiratory airway pressure, the degree of membership of the second respiratory gas force, the degree of membership of the first breathing time, and the second, The suction time belongs to the process, wherein the information about the possibility of the respiratory airway pressure includes a respiratory gas, a force start, a hold point, a second respiratory airway pressure, a starting nuclear d-wee, a force, a knot, and a thief. Surname bundle support point 'The above-mentioned breathing time probability distribution information includes - breathing time starting support point, - call: intervening starting core point, one breathing time ending core point and one Suction time ends support point. Π 。 。 。 。 。 。 。 。 。 。 。 。 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼 啼The more the first respiratory power of the first feature point deviates from the normal state, the more the second respiratory airway pressure membership degree deviates from "1", which represents the second characteristic point corresponding to the actual respiratory waveform. The more the second respiratory airway pressure deviates from the normal situation, the more the first respiratory time is deviated from "1" when the above-mentioned first-breathing time membership degree deviates from "1"", the more the first breathing time corresponding to the first characteristic point of the actual respiratory waveform is deviated from the normal state, In addition, when the degree of membership of the second breathing time deviates from "丨,", the second breathing time corresponding to the second characteristic point corresponding to the above-mentioned actual corpse sacrifice waveform is deviated from the normal situation. Client's Docket N〇 .:ACI94022 TT^ Docket No:0213-A40656-TW/Finall/Jonah/20051117 22