A method for identifying disorders of sugar metabolism based on breath volatile organic compound profiles

Abstract

This invention relates to the field of volatile organic compound (VOC) testing technology, and in particular provides a method for identifying glucose metabolism disorders based on the exhaled VOC spectrum. The method includes: after drying and filtering, the exhaled sample is passed through a separation channel with a built-in linear cooling element at a constant flow rate. Multiple resonant mass-sensitive elements are equidistantly placed along the airflow direction in the channel. The resonant frequency shift of each resonant mass-sensitive element during the passage of the exhaled sample is recorded, forming a frequency shift sequence. A quadratic difference value is calculated for every three consecutive shifts in the frequency shift sequence. The position where the quadratic difference value is zero is located, and the index number of that position in the frequency shift sequence is extracted to form an index sequence. The difference between adjacent index numbers in the index sequence is calculated; if it exceeds the upper limit of the standard deviation, an identification signal for glucose metabolism disorders is output. This invention achieves efficient analysis and disease state classification of exhaled biomarkers through data acquisition, feature extraction, and threshold judgment.

Description

Technical Field

[0001] This invention relates to the field of volatile organic compound testing technology, and in particular to a method for identifying glucose metabolism disorders based on the exhaled volatile organic compound spectrum. Background Technology

[0002] Glucose metabolism disorders such as diabetes and insulin resistance are significant metabolic diseases affecting global health, and their early identification is crucial for disease prevention and control. Traditional methods for detecting glucose metabolism disorders mainly rely on blood biochemical indicators, such as fasting blood glucose and glycated hemoglobin, which require blood sample collection and involve invasive procedures, long testing cycles, and difficulties in real-time monitoring. In recent years, disease diagnostic technologies based on breath analysis have received widespread attention due to their non-invasiveness, ease of operation, and repeatability. Human exhaled breath contains various volatile organic compounds, and changes in their composition and concentration are closely related to metabolic state, providing a potential non-invasive approach for the detection of glucose metabolism disorders.

[0003] Existing technologies include various disease detection methods based on exhaled volatile organic compounds, mainly falling into two categories: gas chromatography-mass spectrometry (GC-MS), which offers high detection accuracy but is expensive, complex to operate, and time-consuming to analyze, making it difficult to apply to rapid screening or routine monitoring; and sensor array technology, which relies heavily on the absolute intensity or simple statistical characteristics of sensor responses, failing to adequately utilize the dynamic distribution characteristics of volatile organic compounds in the separation channel, and is easily affected by factors such as environmental temperature and humidity, and individual differences, resulting in limited identification stability and specificity.

[0004] Current sensor array technologies primarily rely on the amplitude of sensor responses or simple statistical characteristics for analysis, failing to fully exploit the temporal or spatial sequence variations of exhaled VOCs. When exhaled samples pass through a separation channel, different VOC components exhibit dynamic distributions within the channel due to differences in their physicochemical properties. Existing methods typically ignore the sequence features implicit in this distribution, leading to insufficient feature extraction. Furthermore, current technologies often employ fixed thresholds or simple classifiers for signal processing, lacking quantitative assessment of sequence dispersion. This makes it difficult to adapt to the natural fluctuations in exhaled breath components between individuals, easily resulting in misjudgments or missed detections. Summary of the Invention

[0005] To achieve the above objectives, the present invention adopts the following technical solution: One aspect of the present invention provides a method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile, comprising the following steps: After being dried and filtered, the exhaled sample passes through a separation channel with a built-in linear cooling element at a constant flow rate. Multiple resonant mass sensing elements are equidistantly placed in the channel along the airflow direction. The resonant frequency shift of each resonant mass sensing element during the passage of the exhaled sample is recorded. These shifts are arranged in order from the inlet to the outlet to form a frequency shift sequence. Calculate the quadratic difference value for every three consecutive offsets in the frequency offset sequence, locate the position where the quadratic difference value is zero, extract the index number of the position in the frequency offset sequence, and form an index sequence; Calculate the difference between adjacent index numbers in the index sequence, take the standard deviation of the difference, and compare the standard deviation with the upper limit of the standard deviation determined in advance through breath samples of healthy individuals. If it exceeds the upper limit of the standard deviation, an identification signal of glucose metabolism disorder is output.

[0006] This invention involves drying and filtering exhaled breath samples, then passing them at a constant flow rate through a separation channel with a built-in linear cooling element. Multiple resonant mass-sensitive elements are equidistantly positioned along the airflow direction within the separation channel. This causes volatile organic compounds (VOCs) in the exhaled breath to exhibit differentiated adsorption behavior within the channel based on a temperature gradient. Each sensitive element records the resonant frequency shift based on changes in adsorbed mass, forming a frequency shift sequence arranged along the airflow direction. This frequency shift sequence reflects the spatial distribution characteristics of VOCs within the separation channel, providing fundamental data. A quadratic difference value is calculated for every three consecutive shifts in the frequency shift sequence. The position where the quadratic difference value is zero is located, and its index number is extracted, forming an index sequence. Mathematical transformations are used to capture the inflection point information of the frequency shift curve. These inflection points correspond to characteristic transition regions in the VOC adsorption process, characterizing abrupt changes in substance distribution or critical phase transition positions. The difference between adjacent index numbers in the index sequence is calculated and the standard deviation of the difference is taken. The standard deviation is then compared with the upper limit of the standard deviation determined in advance using breath samples from healthy individuals. If the upper limit of the standard deviation is exceeded, an identification signal for glucose metabolism disorder is output. The distribution pattern of volatile organic compounds in the breath of patients with glucose metabolism disorder usually shows higher irregularity or dispersion. By quantifying the fluctuation of the index sequence, an effective identification of metabolic abnormalities can be achieved. Attached Figure Description

[0007] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of the method for identifying glucose metabolism disorders based on the exhaled volatile organic compound spectrum provided in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the method for identifying glucose metabolism disorders based on the exhaled volatile organic compound spectrum provided in Embodiment 1 of the present invention. Figure 3This is a process diagram of forming a frequency offset sequence provided in Embodiment 2 of the present invention; Figure 4 This is a process diagram of the composition index sequence provided in Embodiment 3 of the present invention; Figure 5 This is a flowchart illustrating the process of outputting a glucose metabolism disorder identification signal when the standard deviation exceeds the upper limit value, as provided in Embodiment 4 of the present invention. Figure 6 This is a block diagram of the glucose metabolism disorder identification system based on the exhaled volatile organic compound spectrum provided in Embodiment 8 of the present invention; Figure 7 A block diagram of the electronic device provided by the present invention; Figure 8 A block diagram of a computer-readable storage medium provided for this invention.

[0008] Reference numerals in the attached diagram: 1. Offset sequence acquisition module; 2. Index extraction module; 3. Numerical comparison module; 4. Central processing unit / microprocessor / main control chip; 5. Storage medium; 6. Data bus; 7. Input / output bus / external bus / device bus; 8. Display; 9. Input / output device; 10. Computer-readable instructions; 11. Non-transitory computer-readable storage medium. Detailed Implementation

[0009] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0010] Hereinafter, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0011] In this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral part; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. Furthermore, unless otherwise explicitly specified and limited, the term "coupling" should be interpreted broadly. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components; it can also be understood as an electrical connection between different components in a circuit structure through physical lines capable of transmitting electrical signals, such as copper foil or wires on a printed circuit board (PCB), to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in a non-contact manner, such as an electrical connection between two components using capacitive coupling to transmit electrical signals.

[0012] In this embodiment of the invention, directional terms such as "up," "down," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0013] Example 1: As Figure 1 As shown, this embodiment of the invention provides a method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile, comprising the following steps: Step S100: After the exhaled sample is dried and filtered, it passes through the separation channel with a built-in linear cooling element at a constant flow rate. Multiple resonant mass sensing elements are equidistantly placed in the channel along the airflow direction. The resonant frequency offset of each resonant mass sensing element during the passage of the exhaled sample is recorded. The resonant frequency offsets are arranged in order from the inlet to the outlet to form a frequency offset sequence. Step S200: Calculate the quadratic difference value for every three consecutive offsets in the frequency offset sequence, locate the position where the quadratic difference value is zero, extract the index number of the position in the frequency offset sequence, and form an index sequence; Step S300: Calculate the difference between adjacent index numbers in the index sequence, take the standard deviation of the difference, and compare the standard deviation with the upper limit of the standard deviation determined in advance through breath samples of healthy individuals. If it exceeds the upper limit of the standard deviation, output the identification signal of glucose metabolism disorder.

[0014] The exhaled breath sample refers to the gas exhaled by the subject in a single breath. This gas carries volatile organic compounds (VOCs), and the types and concentration distribution of these VOCs constitute a VOC spectrum, which undergoes detectable changes under conditions of disordered glucose metabolism. Volatile gases refer to the vapors of organic compounds present in the exhaled breath sample that can spontaneously transform from liquid or solid to gaseous states at normal temperature and pressure. These vapors originate from the body's metabolic processes, and their types and concentration distribution change when glucose metabolism is disordered. Volatile gases specifically refer to the portion of organic compound vapors that can be adsorbed by the surface of the resonant mass sensing element and cause a shift in the resonant frequency, including but not limited to acetone, ethanol, and short-chain alkanes. Drying filtration refers to the operation of removing water vapor and particulate impurities through physical adsorption or interception before the exhaled breath sample enters the separation channel. This operation prevents water vapor from interfering with the frequency response of the resonant mass sensing element, ensuring that the frequency shift originates solely from VOCs. The separation channel with built-in linear cooling elements refers to a tubular space equipped with elements that linearly reduce temperature along the channel's length. When an exhaled breath sample passes through at a constant flow rate, different volatile organic compounds (VOCs) are retained at different locations within the channel due to their boiling point differences, thus achieving spatial separation of the VOC spectrum. Linear cooling enhances the separation effect. Resonant mass-sensitive elements refer to multiple sensors equidistantly placed along the channel. Each sensor resonates at its natural frequency when there is no mass load. When VOCs are adsorbed onto its surface, the resonant frequency changes, with the offset proportional to the adsorbate mass. Multiple elements are arranged in order from the channel inlet to the outlet, constituting a point-by-point sampling of the VOC distribution after spatial separation. The resonant frequency offset refers to the difference between the current resonant frequency of each resonant mass-sensitive element and the reference frequency under clean conditions during the passage of the exhaled breath sample. The offset reflects the cumulative mass of VOCs at the element's location. All offsets, arranged in element order, form a frequency offset sequence, which is a digital representation of the exhaled VOC spectrum. The quadratic difference value refers to the calculation performed on three consecutive offsets in the frequency shift sequence. It is used to detect zero-crossing points of local curvature changes in the frequency shift sequence, locating the boundary positions where peaks begin or end in the volatile organic compound (VOC) spectrum. Positions where the quadratic difference value is zero correspond to key inflection points in the slope change of the spectrum. The upper limit of the standard deviation is a threshold pre-determined using breath samples from healthy individuals. Specifically, breath samples from multiple healthy individuals are collected, and the standard deviations of the differences between adjacent index numbers in their respective index sequences are obtained using the same steps. The upper limit of these standard deviations, for example, the mean plus three times the standard deviation, is taken as a fixed comparison benchmark. This upper limit represents the normal fluctuation range of peak spacing in the VOC spectrum under healthy conditions. The identification signal for glucose metabolism disorders is a binary indicator output by the method when the calculated standard deviation of the sample exceeds the aforementioned upper limit. This indicates that the dispersion of the spacing between adjacent peaks in the tested breath VOC spectrum exceeds the healthy range, reflecting structural changes in the VOC spectrum caused by abnormal glucose metabolism.

[0015] In the above embodiments, the principle is referenced in the appendix. Figure 2 In this embodiment, the exhaled breath sample, after drying and filtration, passes through a separation channel with a built-in linear cooling element at a constant flow rate. Multiple resonant mass-sensitive elements are equidistantly placed along the airflow direction within the separation channel. This causes volatile organic compounds (VOCs) in the exhaled breath to exhibit differentiated adsorption behavior within the channel according to the temperature gradient. Each sensitive element records the resonant frequency offset based on the change in adsorbed mass, forming a frequency offset sequence arranged along the airflow direction. This frequency offset sequence reflects the spatial distribution characteristics of VOCs in the separation channel, providing basic data. A quadratic difference value is calculated for every three consecutive offsets in the frequency offset sequence. The position where the quadratic difference value is zero is located, and its index number is extracted to form an index sequence. Mathematical transformations are used to capture the inflection point information of the frequency offset curve. The inflection point corresponds to a characteristic transition region in the VOC adsorption process, characterizing abrupt changes in substance distribution or critical phase transition positions. The difference between adjacent index numbers in the index sequence is calculated and the standard deviation of the difference is taken. The standard deviation is then compared with the upper limit of the standard deviation determined in advance using breath samples from healthy individuals. If the upper limit of the standard deviation is exceeded, an identification signal for glucose metabolism disorder is output. The distribution pattern of volatile organic compounds in the breath of patients with glucose metabolism disorder usually shows higher irregularity or dispersion. By quantifying the fluctuation of the index sequence, an effective identification of metabolic abnormalities can be achieved.

[0016] In summary, this embodiment captures the distribution characteristics of volatile organic compounds through the physical design of the separation channel, extracts key change points of the distribution curve using quadratic difference, and finally identifies glucose metabolism disorders through statistical fluctuation indicators. From data acquisition and feature extraction to threshold judgment, it achieves efficient analysis of exhaled biomarkers and classification of disease states.

[0017] Example 2: As Figure 3 As shown, based on Example 1, the process of forming the frequency offset sequence in step S100 of this embodiment of the invention specifically includes the following steps: Step S101: Fix a flexible circuit strip along the airflow direction on the outer wall of the separation channel. Set a set of parallel contacts on the circuit strip according to the placement position of each resonant mass sensitive element. Each contact is connected to the frequency output terminal of the corresponding element. The arrangement order of the contacts starts from the channel inlet side and ends at the outlet side. Step S102: Press the probe array of a multi-channel frequency acquisition device onto all the contacts of the flexible circuit strip in one go according to the contact arrangement order. The output channel number of the probe array corresponds one-to-one with the inlet-to-outlet sequence of the contacts. The acquisition device reads the resonant frequency offset of each component at the same time. Step S103: A multi-channel frequency acquisition unit writes each offset into a consecutive address segment of its internal memory in ascending order of the output channel number. After writing, the data sequence stored in the consecutive address segment is the frequency offset sequence.

[0018] The flexible circuit strip refers to a strip-shaped assembly composed of a flexible insulating substrate and conductive lines attached to its surface. It is fixed along the airflow direction of the outer wall of the separation channel, and its length matches the placement range of the resonant mass-sensitive elements on the channel. It is used to lead the frequency output signals of each element from the channel wall and arrange them in a concentrated manner. The contacts refer to a set of metal contact pieces on the flexible circuit strip, corresponding to the placement positions of each resonant mass-sensitive element. Each contact piece is electrically connected to the frequency output terminal of the corresponding element through conductive lines inside the flexible circuit strip. All contact pieces are arranged side-by-side on the circuit strip, from the channel entrance side to the exit side, and are used to form temporary or repeatable electrical connections with the probes of external acquisition equipment. The multi-channel frequency acquisition unit refers to a frequency measurement device with multiple parallel input channels. Each input channel corresponds to an independent probe, and all probes are arranged in the same order as the contacts on the flexible circuit strip to form a probe array. This acquisition unit can simultaneously read the frequency signals on all the contacts touched by all probes through a single crimping action, and sequentially write the resonant frequency offset measured by each channel into a continuous address segment of the internal memory according to the output channel number.

[0019] In the above embodiments, this embodiment fixes the flexible circuit strip along the outer wall of the separation channel and connects it to the frequency output terminal of each resonant mass-sensitive element, realizing efficient integration and physical alignment of signals from multiple detection points in the airflow direction; by pressing all contacts at once through the probe array of the multi-channel frequency acquisition device, the synchronization of data acquisition from each channel and the consistency of the contact sequence are ensured, avoiding time errors introduced by time-division acquisition; the offset is written into a continuous address segment according to the output channel number sequence to form a structured frequency offset sequence, providing a complete dataset with spatial correspondence for airflow distribution analysis, which is convenient for direct use in flow field feature calculation and pattern recognition.

[0020] Example 3: As Figure 4 As shown, based on Example 2, the process of composing the index sequence in step S200 of this embodiment of the invention specifically includes the following steps: Step S201: Write the frequency offset sequence sequentially into a linear storage area, set a read pointer to point to the starting address of the linear storage area; then set a three-depth cache stack, read an offset from the pointer position each time and push it to the bottom of the stack, while pushing the original data in the stack up. When the stack is full of three offsets, proceed to the next step. Step S202: Take the first offset and the third offset from the top of the stack, add their values ​​together and put them into the accumulator; then take the second offset from the stack, copy its value and add it to the original value to get double the value, and put the sum and the doubled value in the accumulator into the value comparator at the same time; if the comparator outputs an equal signal, then write the current second offset's sequential number in the frequency offset sequence to the tail of an output queue; Step S203: Move the read pointer one offset position backward, clear the earliest offset pushed into the stack, i.e., the first offset at the bottom of the stack; then push the offset at the new pointer position onto the bottom of the stack, and repeat the process of taking out the first offset and the third offset from the top of the stack until the read pointer points to the end address of the storage area and no more three complete offsets can be obtained in the stack. All sequential numbers in the output queue form an index sequence according to the writing order.

[0021] In the above embodiments, this embodiment achieves dynamic detection of specific patterns in the frequency offset sequence through the collaborative operation of a linear storage area and a triple-deep cache stack, combined with real-time computation of an accumulator and a numerical comparator. The configuration of the linear storage area and the read pointer ensures sequential access and continuous traversal of the sequence data, providing a stable data flow for stack operations; the triple-deep cache stack maintains the latest three offsets through a push-and-push mechanism, forming a sliding window that supports real-time truncation of consecutive triples in the sequence. The cooperation between the accumulator and the numerical comparator enables immediate determination of arithmetic conditions: by calculating the equality of the sum of the first and last offsets with twice the value of the middle offset, the offset positions that satisfy the linear relationship are identified; the determination process is executed immediately after the data is pushed onto the stack, without the need for additional storage of intermediate results, reducing access latency. The cyclical mechanism of pointer movement and stack data clearing allows the sliding window to traverse the entire sequence until the data is exhausted; the output queue records the offset numbers that meet the conditions in the detection order, and the final generated index sequence completely reflects the position distribution of all patterns that satisfy the linear relationship in the sequence.

[0022] In summary, this embodiment achieves efficient and real-time detection of specific numerical relationships in a sequence by integrating streaming processing with hardware-level computing units, while avoiding the need for multiple scans of the complete sequence or large-scale caching, thus improving processing efficiency and resource utilization.

[0023] Example 4: Figure 5 As shown, based on Example 1, the process of outputting an identification signal for glucose metabolism disorder in step S300 of this embodiment of the invention, when the standard deviation exceeds the upper limit, specifically includes the following steps: Step S301: After calculating the standard deviation value, compare the value with the upper limit of the standard deviation measured in advance using breath samples from healthy individuals. When the standard deviation value exceeds the upper limit, the exceeding state is transmitted to the signal generation program as a trigger flag. Step S302: After receiving the trigger flag, the signal generation program extracts each bit of the signal value from a pre-frozen signal sequence in the system read-only area in the storage order. After extraction, the complete signal value sequence is transmitted to the signal sending program. Step S303: The signal sending program sends the received signal value sequence bit by bit through the data output interface. During the sending process, the level of each signal value is kept stable. After the sending is completed, the sequence presented on the output interface is the identification signal of glucose metabolism disorder.

[0024] In the above embodiments, this embodiment compares the standard deviation of the exhaled sample obtained in real time with a preset health threshold. When the detected value exceeds the threshold, a standardized signal generation process is triggered. The preset signal sequence is extracted sequentially from the read-only storage area and a complete identification signal is stably output through the data interface. This ensures the reliability, consistency and anti-interference of the glucose metabolism disorder identification signal output, forming an automated closed-loop processing from threshold judgment to signal output.

[0025] Example 5: Based on Example 4, the process in which the sequence presented on the output interface after the transmission is completed in step S303 of this embodiment of the invention is an identification signal of glucose metabolism disorder, specifically includes the following steps: Step S3031: A fixed-length bit sequence is pre-stored in the system read-only area. Each bit of the bit sequence is arranged in a set order, and the overall pattern of the sequence is defined as a unique identifier for sugar metabolism disorder. Step S3032: When the standard deviation value exceeds the upper limit of the standard deviation, the signal generation program starts from the starting address of the system read-only area and reads each bit in ascending order of address. After reading each bit, it is temporarily stored in the corresponding position of the transmission buffer until all bits are read. Step S3033: The signal transmission program starts from the first bit in the transmission buffer and converts each bit into a level state on the data output interface in sequence. The next bit is sent after the previous bit is sent. When the last bit is sent, the complete level sequence presented on the data output interface is the identification signal of glucose metabolism disorder.

[0026] In the above embodiments, this embodiment uses a preset unique identifier bit sequence to read and temporarily store the bits in address order when the trigger condition is met, and then converts them bit by bit into level signals for output through the data interface; this ensures the uniqueness, order integrity and transmission stability of the identification signal, forming a standardized signal reconstruction process from sequence reading to level conversion.

[0027] Example 6: Based on Example 5, the process of sequentially converting each bit into a level state on the data output interface in step S3033 of this embodiment of the invention specifically includes the following steps: Step S30331: Take a bit from the current read position of the transmit buffer, and send the value of the bit to the selection control terminal of a two-to-one strobe path. The two input terminals of the strobe path are connected to a high-level reference source and a low-level reference source, respectively. Step S30332: The selected path connects the voltage of the corresponding reference source to the signal line of the data output interface according to the received bit value, and keeps the connected state unchanged after connection. Step S30333: After maintaining the on state for a preset stable time interval, disconnect the gating path from the current reference source and move the read position of the transmit buffer to the next bit.

[0028] In the above embodiments, this embodiment maps the bit value to the physical signal output of the corresponding level reference source through the gating path, and switches to the next bit processing after maintaining a stable time; this ensures the accurate generation and stable maintenance of the signal level of each bit, and realizes the reliable conversion from digital bit to physical level.

[0029] Example 7: Based on Example 6, the process of selecting the path to connect the voltage of the corresponding reference source to the signal line of the data output interface according to the received bit value in step S30332 of this embodiment of the invention specifically includes the following steps: Step S303321: Write the received bit value into a temporary status register, and connect the output of the temporary status register to the selection control terminal of the strobe path; Step S303322: The selection path contains two switching elements controlled by the selection control terminal. One switching element is connected to a high-level reference source, and the other switching element is connected to a low-level reference source. According to the value received by the selection control terminal, the corresponding switching element is closed and the other switching element is opened. Step S303323: Close the coupling switch between the output terminal of the gating path and the signal line of the data output interface, so that the reference source voltage connected to the closed switching element is output to the signal line through the gating path.

[0030] In the above embodiments, this embodiment temporarily stores bit values ​​in the status register and controls the selection of switching elements in the gating path to achieve directional coupling between the reference source voltage and the signal line; it ensures accurate switching and electrical isolation of the signal path during level conversion and completes a reliable connection from logic selection to physical level output.

[0031] Example 8: As Figure 6As shown, based on Examples 1-7, the glucose metabolism disorder identification system based on the exhaled volatile organic compound spectrum provided in this embodiment of the invention includes: The offset sequence acquisition module 1 is used to process the exhaled sample through a separation channel with a built-in linear cooling element at a constant flow rate after drying and filtration. Multiple resonant mass sensing elements are equidistantly arranged in the channel along the airflow direction. The module records the resonant frequency offset of each resonant mass sensing element during the passage of the exhaled sample. These offsets are arranged in order from inlet to outlet to form a frequency offset sequence. Index extraction module 2 is used to calculate the quadratic difference value for every three consecutive offsets in the frequency offset sequence, locate the position where the quadratic difference value is zero, extract the index number of the position in the frequency offset sequence, and form an index sequence. The numerical comparison module 3 is used to calculate the difference between adjacent index numbers in the index sequence, take the standard deviation of the difference, and compare the standard deviation with the upper limit of the standard deviation determined in advance through breath samples of healthy individuals. If it exceeds the upper limit of the standard deviation, an identification signal of glucose metabolism disorder is output.

[0032] In the above embodiments, this embodiment achieves continuous and dynamic detection and feature extraction of the exhaled volatile organic compound (VOC) spectrum. By combining a linear cooling element and a resonant mass-sensitive element, a temperature gradient is formed within the separation channel, causing VOCs with different boiling points to adsorb at corresponding positions and induce frequency shifts. This transforms the distribution of organic components into a frequency shift sequence along the airflow direction. Based on index extraction using the second-order difference zero point, the inflection point positions of the frequency shift curve are effectively captured. These inflection points correspond to significant changes in adsorption behavior, reflecting the adsorption temperature nodes of key organic components. By calculating the standard deviation of adjacent differences in the index sequence, the dispersion of the inflection point distribution is quantified. Increased dispersion indicates an abnormal adsorption temperature distribution of organic components in the exhaled sample, corresponding to the disordered VOC spectrum phenomenon associated with glucose metabolism disorders. Finally, by comparing the standard deviation with a healthy baseline, objective and quantitative identification of glucose metabolism disorders is achieved without relying on the absolute concentration of specific biomarkers, improving the detection sensitivity and robustness against changes in the overall pattern of complex exhaled spectra.

[0033] Figure 7 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0034] The electronic device may include a central processing unit / microprocessor / main control chip 4; and a storage medium 5 coupled to the central processing unit / microprocessor / main control chip 4 and storing computer-executable instructions therein for performing the steps of various methods of embodiments of the present invention when executed by the processor.

[0035] The central processing unit / microprocessor / main control chip 4 may include, but is not limited to, one or more processors or microprocessors.

[0036] Storage medium 5 may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0037] In addition, the electronic device may include (but is not limited to) a data bus 6, an input / output bus / external bus / device bus 7, a display 8, and input / output devices 9 (e.g., keyboard, mouse, speaker, etc.).

[0038] The central processing unit / microprocessor / main control chip 4 can communicate with external devices (8, 9, etc.) via wired or wireless networks (not shown) through the input / output bus / external bus / device bus 7.

[0039] The storage medium 5 may also store at least one computer-executable instruction for performing the steps of various functions and / or methods in the embodiments described herein when the central processing unit / microprocessor / main control chip 4 is running.

[0040] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0041] Figure 8 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0042] like Figure 8 As shown, the non-transitory computer-readable storage medium 11 stores instructions, such as computer-readable instructions 10. When the computer-readable instructions 10 are executed by a processor, the various methods described above can be performed. The non-transitory computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium 11 can be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions 10 stored on the non-transitory computer-readable storage medium 11, the various methods described above can be performed.

[0043] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0044] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0045] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0046] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods of the various embodiments of this invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0047] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile, characterized in that, Includes the following steps: Exhaled breath samples are collected and passed through a separation channel equipped with multiple mass-sensitive elements to obtain a response signal sequence formed by the responses of each mass-sensitive element. The response signal sequence is differentially processed to identify signal change feature points and extract their position information to generate a feature sequence. The dispersion index is calculated based on the degree of fluctuation of the position information in the feature sequence, and the dispersion index is compared with a preset threshold. Based on the comparison result, a glucose metabolism disorder identification signal is output.

2. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 1, characterized in that, After being dried and filtered, the exhaled sample passes through a separation channel with a built-in linear cooling element at a constant flow rate. Multiple resonant mass sensing elements are equidistantly placed along the airflow direction in the channel. The resonant frequency shift of each resonant mass sensing element during the passage of the exhaled sample is recorded. The shifts are arranged in order from the inlet to the outlet to form a frequency shift sequence.

3. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 2, characterized in that, The process of forming a frequency offset sequence includes the following steps: A flexible circuit strip is fixed on the outer wall of the separation channel along the airflow direction. A set of parallel contacts are set on the circuit strip according to the placement position of each resonant mass sensitive element. Each contact is connected to the frequency output terminal of the corresponding element. The arrangement of the contacts starts from the channel inlet side and ends at the outlet side. The probe array of a multi-channel frequency acquisition device is pressed onto all the contacts of the flexible circuit strip in one go according to the contact arrangement order. The output channel number of the probe array corresponds one-to-one with the inlet-to-outlet sequence of the contacts. The acquisition device reads the resonant frequency offset of each component at the same time. A multi-channel frequency acquisition unit writes each offset into a consecutive address segment of its internal memory in ascending order of the output channel number. After the writing is completed, the data sequence stored in the consecutive address segment is the frequency offset sequence.

4. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 1, characterized in that, Calculate the quadratic difference value for every three consecutive offsets in the frequency offset sequence, locate the position where the quadratic difference value is zero, extract the index number of the position in the frequency offset sequence, and form an index sequence.

5. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 4, characterized in that, The process of assembling an index sequence includes the following steps: Write the frequency offset sequence sequentially into a linear memory area, set a read pointer to point to the starting address of the linear memory area; then set up a three-depth cache stack, read an offset from the pointer position and push it to the bottom of the stack each time, while pushing the original data in the stack up. When the stack is full of three offsets, execute the next step. Take the first and third offsets from the top of the stack, add their values ​​together and put them into the accumulator; then take the second offset from the stack, copy its value and add it to the original value to get double the value, and put the sum and double the value in the accumulator into the value comparator at the same time; if the comparator outputs an equal signal, write the current second offset's sequential number in the frequency offset sequence to the tail of an output queue; Move the read pointer one offset forward, clear the earliest offset pushed onto the stack (i.e., the first offset at the bottom of the stack), and push the offset at the new pointer position onto the bottom of the stack. Repeat this process of taking the first and third offsets from the top of the stack until the read pointer points to the end address of the storage area and no more three complete offsets can be obtained from the stack. All sequential numbers in the output queue are arranged into an index sequence according to the writing order.

6. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 1, characterized in that, Calculate the difference between adjacent index numbers in the index sequence, take the standard deviation of the difference, and compare the standard deviation with the upper limit of the standard deviation determined in advance through breath samples of healthy individuals. If it exceeds the upper limit of the standard deviation, an identification signal of glucose metabolism disorder is output.

7. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 6, characterized in that, The process of outputting a signal to identify glucose metabolism disorders when the standard deviation exceeds the upper limit includes the following steps: After the standard deviation value is calculated, the value is compared with the upper limit of the standard deviation value determined in advance through breath samples of healthy individuals. When the standard deviation value exceeds the upper limit value, the exceeding state is transmitted to the signal generation program as a trigger flag. After receiving the trigger flag, the signal generation program extracts each bit of the signal value from a pre-frozen signal sequence in the system's read-only area in the storage order. After extraction, it transmits the complete signal value sequence to the signal sending program. The signal sending program sends the received signal value sequence bit by bit through the data output interface. During the transmission process, the level of each signal value remains stable. After the transmission is completed, the sequence presented on the output interface is the identification signal of glucose metabolism disorder.

8. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 7, characterized in that, The process of displaying a sequence as a recognition signal for glucose metabolism disorder on the output interface after transmission is complete includes the following steps: A fixed-length bit sequence is pre-stored in the system's read-only area. Each bit in the bit sequence is arranged in a set order, and the overall pattern of the sequence is defined as a unique identifier for sugar metabolism disorder. When the standard deviation exceeds the upper limit of the standard deviation, the signal generation program starts from the starting address of the system read-only area and reads each bit in ascending order of address. After each bit is read, it is temporarily stored in the corresponding position of the transmit buffer until all bits are read. The signal transmission program starts from the first bit in the transmission buffer and sequentially converts each bit into a level state on the data output interface. The next bit is sent only after the previous bit has been sent. When the last bit has been sent, the complete level sequence presented on the data output interface is the identification signal for glucose metabolism disorder.

9. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 1, characterized in that, The process of sequentially converting each bit into a level state on the data output interface includes the following steps: Take a bit from the current read position of the transmit buffer and send the value of the bit to the selection control terminal of a two-to-one strobe path. The two input terminals of the strobe path are connected to a high-level reference source and a low-level reference source, respectively. The selection path connects the voltage of the corresponding reference source to the signal line of the data output interface according to the received bit value, and keeps the connection state unchanged after connection. After maintaining the connected state for a preset stable time interval, the connection between the gating path and the current reference source is disconnected, and the read position of the transmit buffer is moved to the next bit.

10. The method for identifying glucose metabolism disorders based on the exhaled volatile organic compound profile as described in claim 1, characterized in that, The process of selecting a path to connect the voltage of the corresponding reference source to the signal line of the data output interface based on the received bit value includes the following steps: The received bit value is written into a temporary status register, and the output of the temporary status register is connected to the selection control terminal of the gating path. The selection path contains two switching elements controlled by the selection control terminal. One switching element is connected to a high-level reference source, and the other switching element is connected to a low-level reference source. According to the value received by the selection control terminal, the corresponding switching element is closed, and the other switching element is opened. The coupling switch between the output terminal of the gating path and the signal line of the data output interface is closed, so that the reference source voltage connected to the closed switching element is output to the signal line through the gating path.

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