Methods, devices, media and equipment for identifying anesthetic gases

Abstract

This invention discloses a method, apparatus, medium, and device for identifying anesthetic gases. First, without introducing any anesthetic gas, reference signal values ​​are acquired from N recording channels during zeroing. Then, with the same unknown anesthetic gas introduced, channel signal values ​​and channel concentration values ​​are acquired from each of the N recording channels. Next, based on the acquired parameters, N-1 classification feature parameters and N-1 classification thresholds are calculated. These N-1 classification feature parameters and N-1 classification thresholds are compared, and finally, the category of the unknown anesthetic gas is determined based on the comparison results. This invention requires minimal preliminary preparation, primarily utilizing data detected by the recording channels, making it easy to implement and apply. Furthermore, this invention is widely applicable to the identification of different anesthetic gases and exhibits good identification results for all of them.

Description

Technical Field

[0001] This invention relates to the field of anesthetic gas technology, and in particular to a method, apparatus, medium, and device for identifying anesthetic gases. Background Technology

[0002] The five most commonly used anesthetic gases in clinical practice are desflurane (DES), isoflurane (ISO), halothane (HAL), sevoflurane (SEV), and enflurane (EN). Different anesthetic gases are suitable for different scenarios, therefore, the selection and determination of the type of anesthetic gas is very important.

[0003] Current gas detectors primarily utilize Lambert-Beer's law, which states that the concentration of a gas is reflected by the degree of attenuation of infrared light. However, the absorption spectra of common anesthetic gases in the infrared range of 7-12 μm are intertwined, making it difficult to distinguish different anesthetic gases simply by their absorption capacity in a specific band of infrared light. Summary of the Invention

[0004] Therefore, it is necessary to provide methods, devices, media, and equipment for identifying anesthetic gases in order to solve the problem of difficulty in identifying anesthetic gases.

[0005] A method for identifying anesthetic gases, the method comprising:

[0006] Under the premise that no anesthetic gas is introduced into N recording channels, the reference signal values ​​of N recording channels at zero calibration are obtained; wherein, different recording channels are illuminated with infrared light of different preset wavelengths;

[0007] Under the premise that the same unknown anesthetic gas is introduced into N recording channels respectively, the channel signal value and channel concentration value of N recording channels are obtained respectively; wherein, the unknown anesthetic gas is any one of N preset anesthetic gases;

[0008] Attenuation characteristic parameters are calculated based on the channel signal value, channel concentration value, and reference signal value in each recording channel to obtain attenuation characteristic parameters for N recording channels; wherein, the attenuation characteristic parameters are used to indicate the degree of attenuation of infrared light under different recording channels;

[0009] Classification feature parameters are calculated pairwise based on the attenuation feature parameters of the reference channel and each non-reference channel to obtain N-1 classification feature parameters; wherein, the reference channel is a preset channel among the N recording channels, and the non-reference channels are recording channels other than the reference channel among the N recording channels;

[0010] The classification threshold is calculated pairwise with the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds;

[0011] The N-1 classification feature parameters and the N-1 classification thresholds are compared, and the category of the unknown anesthetic gas is determined based on the comparison results.

[0012] In one embodiment, the formula for calculating the attenuation characteristic parameter is:

[0013]

[0014] In the above formula, L n PAD is the attenuation characteristic parameter of the nth recording channel. n This represents the channel signal value of the nth recording channel. PC is the reference signal value for the nth recording channel. n This represents the channel concentration value of the nth recorded channel.

[0015] In one embodiment, the formula for calculating the classification feature parameters is as follows:

[0016]

[0017] In the above formula, L A L b L indicates the classification feature parameters between the reference channel A and the non-reference channel b. A The attenuation characteristic parameter L of reference channel A. b L indicates the attenuation characteristic parameter of the non-reference channel b. B A set of attenuation characteristic parameters indicating non-reference channels.

[0018] In one embodiment, the step of calculating classification thresholds pairwise based on the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds includes:

[0019] Obtain a preset threshold coefficient between a reference anesthetic gas and each non-reference anesthetic gas; wherein, the reference anesthetic gas is one of the N preset anesthetic gases, and the non-reference anesthetic gas is a preset anesthetic gas other than the reference anesthetic gas among the N preset anesthetic gases;

[0020] Set the reference channel and each non-reference channel as a group to obtain N-1 groups;

[0021] Within each group, a classification threshold is calculated based on the reference signal value of the reference channel, the reference signal value of the corresponding non-reference channel, and the corresponding preset threshold coefficient to obtain N-1 classification thresholds.

[0022] In one embodiment, the formula for calculating the classification threshold is:

[0023]

[0024] In the above formula, Indicator reference anesthetic gas G A With non-reference anesthetic gas G b The classification threshold between G B Indicates the collection of all non-standard anesthetic gases. Indicator threshold coefficient, The reference signal value indicating reference channel A, Indicates the reference signal value of non-reference channel b.

[0025] In one embodiment, the comparison result between the classification feature parameters and the classification threshold includes:

[0026]

[0027] In the above formula, R Ab Indicates the use of reference anesthetic gas G A With non-reference anesthetic gas G b Subclassification results under group, G B The comparison results are composed of the set of all non-reference anesthetic gases and the subcategories of all groups. A L b Indicating the classification feature parameters between the baseline channel A and the non-baseline channel b, Indicator reference anesthetic gas G A With non-reference anesthetic gas G b The classification threshold between them;

[0028] Determining the category of the unknown anesthetic gas based on the obtained comparison results includes:

[0029] When the subclassification results of all groups are the reference anesthetic gas, the unknown anesthetic gas is confirmed as the reference anesthetic gas.

[0030] When any subclassification result is not the reference anesthetic gas, the unknown anesthetic gas is determined to be a subclassification result that is not the reference anesthetic gas.

[0031] In one embodiment, after acquiring the channel signal values ​​and channel concentration values ​​of N recording channels respectively, the method further includes:

[0032] The reference signal value and the channel signal value are subjected to mean filtering and semi-logarithmic compression.

[0033] The channel concentration values ​​are subjected to semi-logarithmic compression.

[0034] A device for identifying anesthetic gases, the device comprising:

[0035] The basic parameter acquisition module is used to acquire the reference signal values ​​of N recording channels at zeroing time, provided that no anesthetic gas is introduced into the N recording channels; wherein, different recording channels are irradiated with infrared light of different preset wavelengths; and to acquire the channel signal values ​​and channel concentration values ​​of the N recording channels respectively, provided that the same unknown anesthetic gas is introduced into each of the N recording channels; wherein, the unknown anesthetic gas is any one of the N preset anesthetic gases;

[0036] The feature parameter calculation module is used to calculate attenuation feature parameters based on the channel signal value, channel concentration value, and reference signal value in each recording channel to obtain attenuation feature parameters for N recording channels. The attenuation feature parameters indicate the degree of infrared light attenuation in different recording channels. Classification feature parameters are calculated pairwise based on the attenuation feature parameters of the reference channel and each non-reference channel to obtain N-1 classification feature parameters. The reference channel is a preset channel among the N recording channels, and the non-reference channels are recording channels other than the reference channel among the N recording channels.

[0037] The classification threshold calculation module is used to calculate the classification threshold pairwise based on the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds;

[0038] The gas identification module is used to compare the N-1 classification feature parameters and the N-1 classification thresholds, and determine the category of the unknown anesthetic gas based on the comparison results.

[0039] A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the above-described anesthetic gas identification method.

[0040] An anesthetic gas identification device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the anesthetic gas identification method described above.

[0041] This invention provides a method, apparatus, medium, and device for identifying anesthetic gases. First, without introducing any anesthetic gas, reference signal values ​​are acquired from N recording channels during zeroing. Then, with the same unknown anesthetic gas introduced, channel signal values ​​and channel concentration values ​​are acquired from each of the N recording channels. Next, based on the acquired parameters, N-1 classification feature parameters and N-1 classification thresholds are calculated. These N-1 classification feature parameters and N-1 classification thresholds are compared, and finally, the category of the unknown anesthetic gas is determined based on the comparison results. This invention requires minimal preliminary preparation, primarily utilizing data detected by the recording channels, making it easy to implement and apply. Furthermore, this invention is widely applicable to the identification of different anesthetic gases and exhibits good identification results for all of them. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] in:

[0044] Figure 1 This is a flowchart illustrating a method for identifying anesthetic gases in one embodiment;

[0045] Figure 2 This is a flowchart illustrating the calculation of the classification threshold in one embodiment;

[0046] Figure 3 This is a schematic diagram of the structure of an anesthetic gas identification device in one embodiment;

[0047] Figure 4 This is a structural block diagram of an anesthetic gas identification device in one embodiment. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0050] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] like Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for identifying anesthetic gases in one embodiment. The steps provided by the method for identifying anesthetic gases in this embodiment include:

[0052] S101, under the premise that no anesthetic gas is introduced into the N recording channels, obtain the reference signal values ​​of the N recording channels at the zero calibration.

[0053] Specifically, in the application scenario of this method, a light source, N filters, and N recording channels are set up, with one filter corresponding to one recording channel, and the parameters of different filters being different. After the light source emits infrared light, it passes through the different filters and illuminates each recording channel. Due to the parameter differences between the filters, different recording channels are illuminated with infrared light of different preset wavelengths. Then, under the premise that no anesthetic gas is introduced into any of the N recording channels, the reference signal values ​​of the N recording channels at zeroing time are obtained. Since the wavelengths of the infrared light illuminating different recording channels are different, these N reference signal values ​​are also different. Optionally, if N=5, the reference signal values ​​of recording channels 1-5 can be recorded separately as follows:

[0054] S102, under the premise that the same unknown anesthetic gas is introduced into N recording channels respectively, the channel signal value and channel concentration value of N recording channels are obtained respectively.

[0055] The unknown anesthetic gas is any one of the N preset anesthetic gases. That is to say, the present invention defines the range of the N preset gases identified. For example, the current preset anesthetic gases are limited to isoflurane (ISO), sevoflurane (SEV), desflurane (DES), halothane (HAL), and enflurane (EN), while the unknown anesthetic gas is one of the above preset anesthetic gases, but it is unknown which one it is.

[0056] Specifically, an unknown anesthetic gas is introduced into N recording channels, and the channel signal value and channel concentration value of each of the N recording channels are acquired. For example, when N=5, the channel signal values ​​of recording channels 1-5 can be recorded as AD. 1 AD 2 AD 3 AD 4 AD 5 Record the channel concentration values ​​of channels 1-5 as C. 1 C 2 C 3 C 4 C 5 .

[0057] Furthermore, in one specific embodiment, the following operations are also performed: mean filtering and semi-logarithmic compression are applied to the reference signal value and the channel signal value, and semi-logarithmic compression is applied to the channel concentration value. The calculation formula for semi-logarithmic compression is as follows:

[0058]

[0059] In the above formula, x is the signal value before semi-logarithmic compression, y is the signal value after semi-logarithmic compression, and K is a pre-set fixed value, serving as the threshold for semi-logarithmic processing. Based on this semi-logarithmic compression, AD value data of different anesthetic gases measured under different channels and concentrations can be compressed to the same order of magnitude. Since this invention ultimately uses a threshold method for judgment, data compression avoids the problem of threshold inapplicability caused by subsequent fluctuations in detection data. Furthermore, in this embodiment, the compressed data can be named the PAD value.

[0060] S103, calculate the attenuation characteristic parameters based on the channel signal value, channel concentration value and reference signal value in each recording channel to obtain the attenuation characteristic parameters of N recording channels.

[0061] Specifically, based on the Lambert-Beer law, we know that:

[0062] I = I0e -kcl

[0063] In the above formula, I represents the infrared light intensity detected by the recording channel, I0 is the source intensity, k represents the extinction coefficient of the gas, c is the gas concentration, and l is the path length of the infrared light.

[0064] Next, the above formula can be simplified to:

[0065]

[0066] The kl value of each recording channel can then be calculated and recorded as the attenuation characteristic parameter L of each channel. This attenuation characteristic parameter is used to indicate the degree of attenuation of infrared light under different recording channels.

[0067] Furthermore, combining the channel signal value, channel concentration value, and reference signal value in this embodiment, the above calculation formula can be rewritten as:

[0068]

[0069] In the above formula, L n PAD is the attenuation characteristic parameter of the nth recording channel. n This represents the channel signal value of the nth recording channel. PC is the reference signal value for the nth recording channel. n This represents the channel concentration value of the nth recorded channel.

[0070] S104. Calculate the classification feature parameters pairwise based on the attenuation feature parameters of the reference channel and the attenuation feature parameters of each non-reference channel to obtain N-1 classification feature parameters.

[0071] Here, the reference channel is a preset channel among the N recording channels, and the non-reference channels are the recording channels other than the reference channel among the N recording channels. For example, if N=5, recording channel 1 is taken as the reference channel, then recording channels 2, 3, 4, and 5 are taken as the non-reference channels.

[0072] In one specific embodiment, the formula for calculating the classification feature parameters is:

[0073]

[0074] In the above formula, L A L b L indicates the classification feature parameters between the reference channel A and the non-reference channel b. A The attenuation characteristic parameter L of reference channel A. b L indicates the attenuation characteristic parameter of the non-reference channel b. B A set of attenuation characteristic parameters indicating non-reference channels.

[0075] Therefore, if channel 1 is the baseline channel and channels 2, 3, 4, and 5 are non-baseline channels, then four classification feature parameters L can be calculated. 1 L 2 L 1 L 3 L 1 L 4 L 1 L 5 .

[0076] S105, calculate the classification threshold pairwise with the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds.

[0077] In one specific embodiment, such as Figure 2 As shown, the classification threshold is calculated through the following steps:

[0078] S1051, obtain the preset threshold coefficient between the reference anesthetic gas and each non-reference anesthetic gas.

[0079] Among them, the reference anesthetic gas is one of the N preset anesthetic gases, and the non-reference anesthetic gas is the preset anesthetic gas other than the reference anesthetic gas among the N preset anesthetic gases.

[0080] For example, the preset anesthetic gases include isoflurane (ISO), sevoflurane (SEV), desflurane (DES), halothane (HAL), and enflurane (EN). If ISO is set as the reference anesthetic gas, then SEV, DES, HAL, and EN are non-reference anesthetic gases.

[0081] S1052, set the reference channel and each non-reference channel as a group to obtain N-1 groups.

[0082] If recording channel 1 is used as the reference channel and recording channels 2, 3, 4, and 5 are used as non-reference channels, then there are 4 groups here: 1-2, 1-3, 1-4, and 1-5.

[0083] S1053, within each group, calculate the classification threshold based on the reference signal value of the reference channel, the reference signal value of the corresponding non-reference channel, and the corresponding preset threshold coefficient to obtain N-1 classification thresholds.

[0084] In one specific embodiment, the formula for calculating the classification threshold is:

[0085]

[0086] In the above formula, Indicator reference anesthetic gas G A With non-reference anesthetic gas G b The classification threshold between G B Indicates the collection of all non-standard anesthetic gases. Indicator threshold coefficient, The reference signal value indicating reference channel A, Indicates the reference signal value of non-reference channel b.

[0087] For example, if 1-2 groups of recording channels are set up to classify ISO and SEV, the formula for calculating the classification threshold can be rewritten as follows:

[0088]

[0089] Furthermore, if 1-3 groups of recording channels are set up for classifying ISO and DES, the formula for calculating the classification threshold can be rewritten as follows:

[0090]

[0091] Similarly, the classification threshold Threshold can also be obtained. ISO-HAL and Threshold ISO-EN The threshold coefficients for different classification thresholds are different, and these threshold coefficients need to be determined experimentally in advance.

[0092] S106. Compare N-1 classification feature parameters and N-1 classification thresholds, and determine the category of the unknown anesthetic gas based on the comparison results.

[0093] In one specific embodiment, the comparison results of the classification feature parameters and the classification threshold include:

[0094]

[0095] In the above formula, R Ab Indicates the use of reference anesthetic gas G A With non-reference anesthetic gas G b Subclassification results under group, G B Indicates the collection of all non-reference anesthetic gases, and compares the subcategories of all groups, L A L b Indicating the classification feature parameters between the baseline channel A and the non-baseline channel b, Indicator reference anesthetic gas G A With non-reference anesthetic gas G b The classification threshold between them;

[0096] The categories of unknown anesthetic gases were determined based on the comparison results, including:

[0097] When all subclassification results for all groups are the baseline anesthetic gas, the unknown anesthetic gas is confirmed as the baseline anesthetic gas; when any subclassification result for any group is not the baseline anesthetic gas, the unknown anesthetic gas is determined as a subclassification result that is not the baseline anesthetic gas.

[0098] For example, under group 1-2, G A Indicates ISO, G b Indicate SEV; under groups 1-3, G A Indicates ISO, G b Indicate DES; under groups 1-4, G A Indicates ISO, G b Indicate HAL; under groups 1-5, G A Indicates ISO, G b indicates EN.

[0099] Furthermore, if L 1 L 2 <Threshold ISO-SEV The output subclassification results under group 1-2 are ISO. If L 1 L 2 Threshold ISO-SEV If the output is 1-2, the subclassification result will be SEV. The same applies to the other groups, so I will not go into details.

[0100] Furthermore, when the subclassification results for all groups are ISO, ISO, ISO, ISO, then the unknown anesthetic gas is identified as ISO. When the subclassification results for all groups are SEV, ISO, ISO, ISO, then the unknown anesthetic gas is identified as SEV. When the subclassification results for all groups are ISO, DES, ISO, ISO, then the unknown anesthetic gas is identified as DES. The remaining results are similar and will not be elaborated further.

[0101] The aforementioned method for identifying anesthetic gases first acquires baseline signal values ​​from N recording channels during zeroing, without introducing any anesthetic gas. Then, with the same unknown anesthetic gas introduced, it acquires channel signal values ​​and channel concentration values ​​from each of the N recording channels. Next, based on the acquired parameters, it calculates N-1 classification feature parameters and N-1 classification thresholds, compares these N-1 parameters with the thresholds, and finally determines the category of the unknown anesthetic gas based on the comparison results. This invention requires minimal preliminary preparation, primarily utilizing data detected by the recording channels, making it easy to implement and apply. Furthermore, this invention is widely applicable to the identification of different anesthetic gases and exhibits good identification performance for all of them.

[0102] In one embodiment, such as Figure 3 As shown, an anesthetic gas identification device is proposed, the device comprising:

[0103] The basic parameter acquisition module 301 is used to acquire the reference signal values ​​of N recording channels at zeroing time, provided that no anesthetic gas is introduced into the N recording channels; wherein, different recording channels are irradiated with infrared light of different preset wavelengths; and to acquire the channel signal values ​​and channel concentration values ​​of the N recording channels respectively, provided that the same unknown anesthetic gas is introduced into the N recording channels respectively; wherein, the unknown anesthetic gas is any one of the N preset anesthetic gases;

[0104] The feature parameter calculation module 302 is used to calculate attenuation feature parameters based on the channel signal value, channel concentration value, and reference signal value in each recording channel to obtain attenuation feature parameters for N recording channels. The attenuation feature parameters are used to indicate the degree of attenuation of infrared light under different recording channels. The module calculates classification feature parameters pairwise based on the attenuation feature parameters of the reference channel and the attenuation feature parameters of each non-reference channel to obtain N-1 classification feature parameters. The reference channel is a preset channel among the N recording channels, and the non-reference channels are the recording channels other than the reference channel among the N recording channels.

[0105] The classification threshold calculation module 303 is used to calculate the classification threshold pairwise based on the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds;

[0106] The gas identification module 304 is used to compare N-1 classification feature parameters and N-1 classification thresholds, and determine the category of the unknown anesthetic gas based on the comparison results.

[0107] Figure 4 An internal structural diagram of an anesthetic gas detection device in one embodiment is shown. Figure 4 As shown, the anesthetic gas identification device includes a processor, a memory, and a network interface connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement the anesthetic gas identification method. The internal memory may also store a computer program, which, when executed by the processor, enables the processor to implement the anesthetic gas identification method. Those skilled in the art will understand that… Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the anesthetic gas identification device to which the present application is applied. A specific anesthetic gas identification device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0108] A computer-readable storage medium storing a computer program, which, when executed by a processor, performs the following steps: acquiring reference signal values ​​of N recording channels at zeroing time, provided that no anesthetic gas is introduced into any of the N recording channels; acquiring channel signal values ​​and channel concentration values ​​of the N recording channels respectively, provided that the same unknown anesthetic gas is introduced into each of the N recording channels; calculating attenuation characteristic parameters based on the channel signal value, channel concentration value, and reference signal value of each recording channel to obtain attenuation characteristic parameters for the N recording channels; calculating classification characteristic parameters pairwise between the attenuation characteristic parameters of the reference channels and the attenuation characteristic parameters of each non-reference channel to obtain N-1 classification characteristic parameters; calculating classification thresholds pairwise between the reference signal value of the reference channels and the reference signal value of each non-reference channel to obtain N-1 classification thresholds; comparing the N-1 classification characteristic parameters and the N-1 classification thresholds, and determining the category of the unknown anesthetic gas based on the comparison result.

[0109] An anesthetic gas identification device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps: Under the premise that no anesthetic gas is introduced into N recording channels, acquire the reference signal values ​​of the N recording channels at zero calibration; under the premise that the same unknown anesthetic gas is introduced into each of the N recording channels, acquire the channel signal value and channel concentration value of each of the N recording channels; calculate attenuation characteristic parameters based on the channel signal value, channel concentration value, and reference signal value of each recording channel to obtain attenuation characteristic parameters for the N recording channels; calculate classification characteristic parameters pairwise based on the attenuation characteristic parameters of the reference channels and the attenuation characteristic parameters of each non-reference channel to obtain N-1 classification characteristic parameters; calculate classification thresholds pairwise based on the reference signal value of the reference channels and the reference signal value of each non-reference channel to obtain N-1 classification thresholds; compare the N-1 classification characteristic parameters and the N-1 classification thresholds, and determine the category of the unknown anesthetic gas based on the comparison result.

[0110] It should be noted that the above-mentioned anesthetic gas identification method, device, equipment, and computer-readable storage medium belong to the same general inventive concept, and the contents of the embodiments of the anesthetic gas identification method, device, equipment, and computer-readable storage medium are applicable to each other.

[0111] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0112] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0113] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. An anesthetic gas recognition method characterized by, The method includes: Under the premise that no anesthetic gas is introduced into N recording channels, the reference signal values ​​of N recording channels at zero calibration are obtained; wherein, different recording channels are illuminated with infrared light of different preset wavelengths; Under the premise that the same unknown anesthetic gas is introduced into N recording channels respectively, the channel signal value and channel concentration value of N recording channels are obtained respectively; wherein, the unknown anesthetic gas is any one of N preset anesthetic gases; Attenuation characteristic parameters are calculated based on the channel signal value, channel concentration value, and reference signal value in each recording channel to obtain attenuation characteristic parameters for N recording channels; wherein, the attenuation characteristic parameters are used to indicate the degree of attenuation of infrared light under different recording channels; Classification feature parameters are calculated pairwise based on the attenuation feature parameters of the reference channel and each non-reference channel to obtain N-1 classification feature parameters; wherein, the reference channel is a preset channel among the N recording channels, and the non-reference channels are recording channels other than the reference channel among the N recording channels; The classification threshold is calculated pairwise with the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds; The N-1 classification feature parameters and the N-1 classification thresholds are compared, and the category of the unknown anesthetic gas is determined based on the comparison results. The classification threshold is calculated pairwise based on the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds, including: Obtain a preset threshold coefficient between a reference anesthetic gas and each non-reference anesthetic gas; wherein, the reference anesthetic gas is one of the N preset anesthetic gases, and the non-reference anesthetic gas is a preset anesthetic gas other than the reference anesthetic gas among the N preset anesthetic gases; Set the reference channel and each non-reference channel as a group to obtain N-1 groups; Within each group, a classification threshold is calculated based on the reference signal value of the reference channel, the reference signal value of the corresponding non-reference channel, and the corresponding preset threshold coefficient to obtain N-1 classification thresholds.

2. The method of claim 1, wherein, The formula for calculating the attenuation characteristic parameter is as follows: In the above formula, is an attenuation characteristic parameter of the nth recording channel, is a channel signal value of the nth recording channel, is a reference signal value of the nth recording channel, is a channel concentration value of the nth recording channel.

3. The method of claim 1, wherein, The formula for calculating the classification feature parameters is as follows: In the above formula, Indicator reference channel Classification feature parameters between the non-benchmark channel b and the non-benchmark channel b Indicator reference channel The attenuation characteristic parameters, Indicates the attenuation characteristic parameters of the non-reference channel b. A set of attenuation characteristic parameters indicating non-reference channels.

4. The method according to claim 1, characterized in that, The formula for calculating the classification threshold is: In the above formula, Indicator reference anesthetic gas Non-standard anesthetic gases The classification threshold between them Indicates the collection of all non-standard anesthetic gases. Indicator threshold coefficient, The reference signal value indicating reference channel A, Indicates the reference signal value of non-reference channel b.

5. The method according to claim 1, characterized in that, The comparison results of the classification feature parameters and the classification threshold include: In the above formula, Indicator in reference anesthetic gas Non-standard anesthetic gases Subclassification results under the group The comparison results are composed of the set of all non-reference anesthetic gases and the subcategories of all groups. Indicator reference channel Classification feature parameters between the non-benchmark channel b and the non-benchmark channel b Indicator reference anesthetic gas Non-standard anesthetic gases The classification threshold between them; Determining the category of the unknown anesthetic gas based on the obtained comparison results includes: When the subclassification results of all groups are the reference anesthetic gas, the unknown anesthetic gas is confirmed as the reference anesthetic gas. When any subclassification result is not the reference anesthetic gas, the unknown anesthetic gas is determined to be a subclassification result that is not the reference anesthetic gas.

6. The method according to claim 1, characterized in that, After acquiring the channel signal values ​​and channel concentration values ​​of N recording channels respectively, the process further includes: The reference signal value and the channel signal value are subjected to mean filtering and semi-logarithmic compression. The channel concentration values ​​are subjected to semi-logarithmic compression.

7. A device for identifying anesthetic gases, employing the anesthetic gas identification method as described in claim 1, characterized in that, The device includes: The basic parameter acquisition module is used to acquire the reference signal values ​​of N recording channels at zeroing time, provided that no anesthetic gas is introduced into the N recording channels; wherein, different recording channels are irradiated with infrared light of different preset wavelengths; and to acquire the channel signal values ​​and channel concentration values ​​of the N recording channels respectively, provided that the same unknown anesthetic gas is introduced into each of the N recording channels; wherein, the unknown anesthetic gas is any one of the N preset anesthetic gases; The feature parameter calculation module is used to calculate attenuation feature parameters based on the channel signal value, channel concentration value, and reference signal value in each recording channel to obtain attenuation feature parameters for N recording channels. The attenuation feature parameters indicate the degree of infrared light attenuation in different recording channels. Classification feature parameters are calculated pairwise based on the attenuation feature parameters of the reference channel and each non-reference channel to obtain N-1 classification feature parameters. The reference channel is a preset channel among the N recording channels, and the non-reference channels are recording channels other than the reference channel among the N recording channels. The classification threshold calculation module is used to calculate the classification threshold pairwise based on the reference signal value of the reference channel and the reference signal value of each non-reference channel to obtain N-1 classification thresholds; The gas identification module is used to compare the N-1 classification feature parameters and the N-1 classification thresholds, and determine the category of the unknown anesthetic gas based on the comparison results.

8. A computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 6.

9. An anesthetic gas identification device, comprising a memory and a processor, the memory storing a computer program, which, when executed by the processor, causes the processor to perform the steps of the method as claimed in any one of claims 1 to 6.

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