Respiratory rehabilitation physiological index monitoring process in training process
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 南昌大学第一附属医院
- Filing Date
- 2026-06-03
- Publication Date
- 2026-07-14
Smart Images
Figure CN122376076A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of biomedical engineering technology, and in particular relates to a process for monitoring respiratory rehabilitation physiological indicators during training. Background Technology
[0002] Respiratory rehabilitation training is a crucial step in rebuilding respiratory function in patients with nerve damage or respiratory diseases. By monitoring the mechanical output and morphological characteristics of subjects during training, quantitative evaluation data can be provided for clinical care. Current technologies are generally based on the engineering assumption that airway pressure output and diaphragmatic contraction are linearly synchronized. The mechanical properties of respiratory muscles are mainly determined by collecting parameters such as peak airway pressure and inspiratory flow rate. However, living biological tissues are nonlinear viscoelastic media and exhibit significant physical hysteresis when overcoming airway resistance. When subjects perform progressively increasing resistance inhalation, the damaged neuromuscular system often generates involuntary compensatory mechanisms, such as engaging accessory muscle groups in the neck or intercostal spaces to exert force. Since airway sensors can only acquire the total respiratory power output, the current technology is insufficient.
[0003] Existing technologies cannot effectively distinguish whether negative airway pressure originates from the active contraction of the diaphragm or the compensatory involvement of accessory muscle groups. For example, Chinese invention patent CN101380233B discloses a method and device for real-time monitoring of respiratory work based on a respiratory mechanics module. It calculates respiratory work by multiplying and summing the airway pressure and volume increments within a sampling period. However, under the nonlinear hysteresis condition of biological tissues, this monitoring logic based on the integration of overall airway parameters has fundamental limitations. Its underlying assumption equates airway output to diaphragmatic contraction efficiency, failing to separate the actual diaphragmatic contraction work from the mixed work component generated by the compensatory force of accessory muscle groups. The technical solution lacks a quantitative representation of the decoupling state between morphological displacement and force, which causes the monitoring results to be biased when there is non-voluntary compensatory behavior, making it difficult to provide an objective basis for evaluating the progress of diaphragmatic rehabilitation. Even if the sampling frequency is increased or the digital filtering algorithm is optimized, it is impossible to eliminate the physical decoupling between muscle displacement and force in the viscoelastic medium to address such interference in physiological measurements. Simply extracting the time difference between morphological mutation points and mechanical extreme points in the time domain ignores the dynamic hysteresis effect of biological tissues under different pressure loads, resulting in physiological distortion of rehabilitation evaluation indicators. The existence of this implicit compensatory behavior makes it difficult for clinicians to accurately obtain the true progress of diaphragmatic rehabilitation.
[0004] Therefore, the technical problem to be solved by this invention is how to construct a physical hierarchy that can overcome the phase lag of physiological signals, realize the actual work of the diaphragm and the compensatory work of the auxiliary muscle groups, and provide a highly objective basis for respiratory rehabilitation evaluation. Summary of the Invention
[0005] This invention aims to solve the problems of distorted physiological efficacy assessment caused by the compensatory exertion of accessory muscle groups in the human respiratory mechanism and the decoupling of mechanical and morphological signals caused by the viscoelasticity of biological tissues.
[0006] In this technical solution, a process for monitoring respiratory rehabilitation physiological indicators during training includes the following steps: Step 101: During the period when the subject cooperates with the respiratory rehabilitation training device to perform incremental resistance inhalation intervention, the pressure sensing unit and the ultrasound detection unit are controlled by a synchronous clock source to obtain the transient airway pressure at the same sampling time and the transient diaphragm thickness characterizing the physical deformation of the subject's diaphragm. Step 102: Using transient airway pressure as the vertical axis variable and transient diaphragm thickness as the horizontal axis variable, establish a coordinate mapping relationship between transient airway pressure and transient diaphragm thickness in a preset two-dimensional logical state space coordinate system, thereby constructing a respiratory mechanics work loop trajectory that characterizes the biomechanical energy evolution trajectory within a single respiratory cycle. Step 103: The area integral of the nonlinear closed region enclosed by the respiratory mechanical work loop trajectory is performed using the discrete Green's formula to extract the respiratory mechanical dissipation work, which characterizes the hysteresis energy loss value caused by the viscoelastic hysteresis effect of the respiratory muscles. Step 104: Extract the maximum displacement difference of the respiratory mechanical work loop trajectory in the horizontal direction to determine the diaphragm variation amplitude, calculate the ratio of respiratory mechanical dissipation work to diaphragm variation amplitude, and obtain the inspiratory phase lag compensation amount used to quantitatively isolate the involuntary compensation work intensity of the accessory muscle groups. Step 105: Based on the inspiratory phase lag compensation, the maximum inspiratory pressure peak value in the transient airway pressure is weighted and attenuated to determine the subject's respiratory rehabilitation physiological indicators and output a monitoring signal indicating the subject's respiratory function status.
[0007] Preferably, step 101 includes: step 1011, using a built-in hardware timer interrupt to trigger the pressure sensing unit to collect the instantaneous airway negative pressure value of the subject under increasing inspiratory load; step 1012, using an ultrasound imaging detection unit to simultaneously acquire the diaphragm image of the subject under inspiratory load and extract the transient diaphragm thickness; step 1013, using the global timestamp generated by the hardware clock source as a reference, performing time-scale registration and alignment on the acquired data to generate a data sequence with a unified time base.
[0008] Preferably, the method further includes the following steps: Step 106, extracting the diaphragm thickening fraction of the subject in a single respiratory cycle, and using the diaphragm thickening fraction to weight and correct the inspiratory phase lag compensation amount to generate a fatigue monitoring index that reflects the latent fatigue state of the respiratory muscles; the fatigue monitoring index is used to quantify the dynamic attenuation of the subject's diaphragm contraction efficiency under resistance load.
[0009] Preferably, the method further includes the following steps: Step 1061, when the fatigue monitoring index continues to exceed the preset safety threshold for more than 2 seconds, a load adjustment signal is sent to the respiratory rehabilitation device to reduce the current inspiratory damping load; wherein, the load adjustment signal includes a control quantity for controlling the opening of the proportional valve, so that the inspiratory resistance is reduced to the basic tolerance range of the subject's diaphragm.
[0010] Preferably, generating the respiratory mechanics work loop trajectory in step 102 includes: capturing the dynamic slope characteristics of transient airway pressure in the coordinate system, identifying the characteristic inflection point of the transition from spontaneous breathing to compensatory breathing, and performing segmented fitting of the respiratory mechanics work loop trajectory based on the characteristic inflection point to construct a mechanical hysteresis trajectory curve with asymmetric geometric characteristics.
[0011] Preferably, the method further includes the following steps: Step 107, based on the time-domain evolution trend of respiratory mechanical dissipation work, analyze the degree of decoupling between the mechanical response and morphological displacement of the subject under load training state, and construct a respiratory rehabilitation efficacy evaluation model; the efficacy evaluation model is used to reflect the consistency of the subject's respiratory control center in neuromuscular control of the diaphragm and accessory muscle groups.
[0012] Preferably, the acquisition of transient airway pressure in step 101 includes: step 1014, using a preset normalization algorithm to exclude the linear pressure loss caused by the 1.2mm larynx diameter difference in the respiratory rehabilitation device tubing, and calibrating the sampling reference value of transient airway pressure; the calibration process is based on the tubing fluid dynamics correction model to compensate for the pressure difference between the airway end sensor and the oral cavity end.
[0013] Preferably, the monitoring signal output in step 105 includes: real-time monitoring of the respiratory mechanics work loop trajectory. to The trajectory width variation rate within the pressure range is calculated, and adjustment suggestions for the breathing training program are output. The adjustment suggestions include quantitative settings for the peak inspiratory resistance and inspiratory duration in the next training cycle for the subject.
[0014] Preferably, the method further includes the following steps: Step 108, statistically analyzing the mean fluctuation of respiratory mechanical dissipation work over five consecutive respiratory cycles, and dynamically adjusting the sampling frequency in step 101 based on the mean fluctuation, so that the sampling frequency is non-linearly switched within the range of 50Hz to 200Hz according to the real-time rate of change of the subject's respiratory frequency.
[0015] Compared with existing technologies, the respiratory rehabilitation physiological indicator monitoring process of this invention has the following advantages: 1. In the monitoring of respiratory rehabilitation physiological indicators, by constructing a two-dimensional state-space closed trajectory of transient airway pressure and transient diaphragm thickness, the physical hierarchy of the compensatory work mechanism of respiratory muscles is stripped away. This invention utilizes discrete data pairs obtained by synchronous sampling from the same source clock to transform the phase shift that is difficult to capture in the time domain into geometric features in the state space. By calculating the hysteresis work area enclosed by the closed loop, a direct mapping relationship between pressure output intensity and muscle morphological variation is established. This mechanism can identify the degree of involuntary participation of accessory muscle groups under different pressure loads from the thermodynamic work source level, eliminate artificially high pressure indicators, and thus provide a physiological benchmark reflecting the true diaphragm function for rehabilitation evaluation.
[0016] 2. Based on the area integration operation of the closed trajectory in state space, the monitoring process is improved in terms of anti-interference ability and diagnostic robustness in complex clinical monitoring environments. This invention uses a discrete integral algorithm to process the two-dimensional trajectory closed loop, transforming the dependence on a single fuzzy sampling point into the global feature extraction of the work path throughout the entire respiratory cycle. This measurement method, which transforms from local feature matching to spatial topological geometric feature transformation, gives the system a natural tolerance to random data jitter, effectively reducing the impact of signal-to-noise ratio fluctuations on the calculation of the compensation index and ensuring the consistency of the quantitative diagnostic results of respiratory dysfunction.
[0017] 3. By dynamically linking the phase difference compensation factor and the intervention resistance parameter in reverse, a closed-loop protection mechanism for latent respiratory muscle fatigue is constructed. This invention uses the decoupled phase difference compensation factor as a real-time feedback variable, combined with the instantaneous change rate of the diaphragm thickening fraction, to determine in real time whether the subject's exertion pattern has shifted from active contraction to fatigue compensation. When the compensation intensity exceeds a preset threshold and the morphological variation efficacy drops sharply, the system issues a command through control logic to immediately reduce the mechanical resistance of the current inspiratory intervention. This process achieves active adaptation from externally applied load to internal physiological state, solves the medical safety risks caused by excessive training load, and demonstrates the deep coupling between monitoring technology and clinical intervention strategy. Attached Figure Description
[0018] Figure 1 This is a flowchart of the physiological indicator monitoring process based on respiratory mechanics work loop trajectory during the training process of this invention; Figure 2 This is a schematic diagram of the hardware architecture and multi-dimensional signal interaction principle of the respiratory rehabilitation monitoring system of the present invention. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.
[0020] It should be noted that all directional and positional terms used in this invention, such as: up, down, left, right, front, back, vertical, horizontal, inner, outer, top, low, lateral, longitudinal, center, etc., are only used to explain the relative positional relationship and connection between components in a specific state (as shown in the accompanying drawings). They are only for the convenience of describing this invention and do not require that this invention be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention. In addition, the descriptions of "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated.
[0021] In the description of this invention, unless otherwise explicitly specified and limited, the terms installation, connection, and linking should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to the internal connection of two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.
[0022] In the description of this specification, references to the terms "an embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0023] A process for monitoring respiratory rehabilitation physiological indicators during training includes the following steps: Step 101: During the period when the subject cooperates with the respiratory rehabilitation training device to perform incremental resistance inhalation intervention, the pressure sensing unit and the ultrasound detection unit are controlled by a synchronous clock source to obtain the transient airway pressure at the same sampling time and the transient diaphragm thickness characterizing the physical deformation of the subject's diaphragm. Step 102: Using transient airway pressure as the vertical axis variable and transient diaphragm thickness as the horizontal axis variable, establish a coordinate mapping relationship between transient airway pressure and transient diaphragm thickness in a preset two-dimensional logical state space coordinate system, thereby constructing a respiratory mechanics work loop trajectory that characterizes the biomechanical energy evolution trajectory within a single respiratory cycle. Step 103: The area integral of the nonlinear closed region enclosed by the respiratory mechanical work loop trajectory is performed using the discrete Green's formula to extract the respiratory mechanical dissipation work, which characterizes the hysteresis energy loss value caused by the viscoelastic hysteresis effect of the respiratory muscles. Step 104: Extract the maximum displacement difference of the respiratory mechanical work loop trajectory in the horizontal direction to determine the diaphragm variation amplitude, calculate the ratio of respiratory mechanical dissipation work to diaphragm variation amplitude, and obtain the inspiratory phase lag compensation amount used to quantitatively isolate the involuntary compensation work intensity of the accessory muscle groups. Step 105: Based on the inspiratory phase lag compensation, the maximum inspiratory pressure peak value in the transient airway pressure is weighted and attenuated to determine the subject's respiratory rehabilitation physiological indicators and output a monitoring signal indicating the subject's respiratory function status.
[0024] Preferably, step 101 includes: step 1011, using a built-in hardware timer interrupt to trigger the pressure sensing unit to collect the instantaneous airway negative pressure value of the subject under increasing inspiratory load; step 1012, using an ultrasound imaging detection unit to simultaneously acquire the diaphragm image of the subject under inspiratory load and extract the transient diaphragm thickness; step 1013, using the global timestamp generated by the hardware clock source as a reference, performing time-scale registration and alignment on the acquired data to generate a data sequence with a unified time base.
[0025] Preferably, the method further includes the following steps: Step 106, extracting the diaphragm thickening fraction of the subject in a single respiratory cycle, and using the diaphragm thickening fraction to weight and correct the inspiratory phase lag compensation amount to generate a fatigue monitoring index that reflects the latent fatigue state of the respiratory muscles; the fatigue monitoring index is used to quantify the dynamic attenuation of the subject's diaphragm contraction efficiency under resistance load.
[0026] Preferably, the method further includes the following steps: Step 1061, when the fatigue monitoring index continues to exceed the preset safety threshold for more than 2 seconds, a load adjustment signal is sent to the respiratory rehabilitation device to reduce the current inspiratory damping load; wherein, the load adjustment signal includes a control quantity for controlling the opening of the proportional valve, so that the inspiratory resistance is reduced to the basic tolerance range of the subject's diaphragm.
[0027] Preferably, generating the respiratory mechanics work loop trajectory in step 102 includes: capturing the dynamic slope characteristics of transient airway pressure in the coordinate system, identifying the characteristic inflection point of the transition from spontaneous breathing to compensatory breathing, and performing segmented fitting of the respiratory mechanics work loop trajectory based on the characteristic inflection point to construct a mechanical hysteresis trajectory curve with asymmetric geometric characteristics.
[0028] Preferably, the method further includes the following steps: Step 107, based on the time-domain evolution trend of respiratory mechanical dissipation work, analyze the degree of decoupling between the mechanical response and morphological displacement of the subject under load training state, and construct a respiratory rehabilitation efficacy evaluation model; the efficacy evaluation model is used to reflect the consistency of the subject's respiratory control center in neuromuscular control of the diaphragm and accessory muscle groups.
[0029] Preferably, the acquisition of transient airway pressure in step 101 includes: step 1014, using a preset normalization algorithm to exclude the linear pressure loss caused by the 1.2mm larynx diameter difference in the respiratory rehabilitation device tubing, and calibrating the sampling reference value of transient airway pressure; the calibration process is based on the tubing fluid dynamics correction model to compensate for the pressure difference between the airway end sensor and the oral cavity end.
[0030] Preferably, the monitoring signal output in step 105 includes: real-time monitoring of the respiratory mechanics work loop trajectory. to The trajectory width variation rate within the pressure range is calculated, and adjustment suggestions for the breathing training program are output. The adjustment suggestions include quantitative settings for the peak inspiratory resistance and inspiratory duration in the next training cycle for the subject.
[0031] Preferably, the method further includes the following steps: Step 108, statistically analyzing the mean fluctuation of respiratory mechanical dissipation work over five consecutive respiratory cycles, and dynamically adjusting the sampling frequency in step 101 based on the mean fluctuation, so that the sampling frequency is non-linearly switched within the range of 50Hz to 200Hz according to the real-time rate of change of the subject's respiratory frequency.
[0032] Example 1: In a specific application example of the respiratory rehabilitation physiological index monitoring process provided by the present invention, the inspiratory resistance is set to [value missing] for subjects with diaphragmatic dysfunction due to long-term mechanical ventilation. In incremental resistance rehabilitation training, when the subject exerts involuntary compensatory force due to damage to the neuromuscular transmission pathway, the negative airway pressure generated by the work of the neck and intercostal accessory muscle groups and the negative pressure generated by the actual contraction of the diaphragm are superimposed at the airway pressure sensor. This causes the transient airway pressure peak recorded at the airway end to fail to directly reflect the true contractile efficacy of the diaphragm, thus resulting in the distortion of physiological indicator monitoring.
[0033] When handling situations involving muscle compensation interference, the aforementioned monitoring process synchronously triggers the pressure sensing unit and the ultrasound detection unit through a built-in hardware timer interrupt to acquire transient airway pressure consistent with the sampling time and transient diaphragm thickness characterizing the physical deformation characteristics of the subject's diaphragm. The acquired data is then time-calibrated and aligned using a global timestamp generated by a hardware clock source as a reference, generating a data sequence with a unified time base. Transient airway pressure is used as the vertical axis variable, and transient diaphragm thickness is used as the horizontal axis variable. A coordinate mapping relationship between transient airway pressure and transient diaphragm thickness is established in a preset two-dimensional logical state space coordinate system, thereby constructing a respiratory mechanics work loop trajectory characterizing the biomechanical energy evolution trajectory within a single respiratory cycle.
[0034] The system control unit extracts the maximum displacement difference of the respiratory mechanical work loop trajectory in the horizontal direction to determine the diaphragm variation amplitude, and uses the Discrete Green's formula to perform area integration on the nonlinear closed region enclosed by the respiratory mechanical work loop trajectory to extract the respiratory mechanical dissipation work, which characterizes the hysteresis energy loss caused by the viscoelastic hysteresis effect of the respiratory muscles. The specific calculation formula is as follows: ,in, For respiratory mechanical dissipation work, The closed loop formed by the respiratory mechanics work circuit trajectory in a two-dimensional state space coordinate system; Transient airway pressure, Based on the transient diaphragm thickness, the system calculates the ratio of respiratory mechanical dissipation work to diaphragm variation amplitude to obtain the inspiratory lag compensation amount used to quantitatively strip the involuntary compensatory work intensity of accessory muscle groups. The system then applies a weighted attenuation correction to the peak inspiratory pressure in the transient airway pressure based on the inspiratory lag compensation amount, determining the subject's respiratory rehabilitation physiological indicators. In this example, the system identified an increase in lag area at the end of inspiration due to diaphragmatic fatigue, and thus accurately identified the true decline in diaphragmatic efficacy through the corrected respiratory rehabilitation physiological indicators. It then outputs a monitoring signal indicating the subject's respiratory function status, triggering the respiratory rehabilitation training device to reduce inspiratory resistance. The baseline tolerance range allows for a dynamic adaptation between the externally applied physical load and the subject's actual physiological functional state.
[0035] Example 2: Regarding the respiratory rehabilitation physiological index monitoring process provided by this invention, this experiment collected data in a respiratory biomechanical simulation platform for the subjects. The data was used to determine the measurement accuracy and anti-interference capability of the inspiratory phase lag compensation amount extracted based on the respiratory biomechanical work loop trajectory. This simulation platform includes a set range of... to Furthermore, the platform features a pressure sensing unit with a measurement accuracy of 0.05% and an ultrasonic detection unit with a frame rate of 200Hz. By adjusting the stroke and load feedback function of the electrically driven push rod in the platform, the diaphragm deformation and compensatory movements of accessory muscle groups under different airway resistances are simulated. The sampling frequency was set during the experiment. The sampling frequency is set to 200Hz. The logic behind this setting is to balance the discretization accuracy of the area integration operation with the real-time processing load of the computing system. When the monitored signal contains high-frequency disturbance components generated by the contraction of the neck accessory muscles, the sampling frequency is selected accordingly. The frequency should be greater than 10 times the characteristic frequency of the monitored physiological signal to avoid signal aliasing during the construction of the respiratory mechanics work loop trajectory.
[0036] The experiment was divided into an experimental group and a control group. The experimental group used the method provided in this invention to extract the inspiratory phase lag compensation by calculating the area of the closed region of the respiratory work loop trajectory. The control group used the phase alignment method of extracting the time difference between the pressure extreme point and the thickness extreme point. To simulate the dynamic clinical monitoring environment, Gaussian white noise with a signal-to-noise ratio of 20dB and power frequency harmonic interference with a frequency of 50Hz were actively superimposed on the original signal sequence. Under baseline conditions, the experimental group measured an inspiratory phase lag compensation of 0.11, and the deviation of the corrected maximum inspiratory pressure from the preset value of the simulation platform was 1.2%. The control group experienced a measurement deviation of 5.6% due to noise interference in extreme point identification. This deviation increased with increasing airway resistance. At that time, the simulation platform increased the output of the auxiliary muscle group force weight. The experimental group observed that the closed loop area of the respiratory mechanical work loop trajectory in the pressure-morphology coordinate system showed nonlinear expansion. The compensation amount after inspiratory hysteresis increased to 0.41. The system calculated the area of the nonlinear closed region enclosed by the respiratory mechanical work loop trajectory through the discrete Green's formula and attenuated the maximum inspiratory pressure to maintain the measurement error of physiological indicators at 2.2%.
[0037] When airway resistance further increases to Furthermore, when the high load duration exceeded 10 seconds, the ratio of respiratory mechanical dissipation work to diaphragmatic variation amplitude obtained in the experimental group climbed to 0.78. At this point, the control group, unable to physically separate the mixed work component generated by the accessory muscle groups, exhibited a 72% artificially high deviation in its maximum inspiratory pressure output. In contrast, the experimental group, utilizing global feature extraction of the work path within the respiratory cycle, calculated the inspiratory lag compensation amount under noise background, accurately characterizing the involuntary compensation strength of the accessory muscle groups. This allowed them to identify the true decline trend of diaphragmatic contraction efficiency and further increase resistance to... After the above, the inspiratory phase lag compensation amount measured in the experimental group entered the saturation range of 0.86 to 0.88, indicating that the diaphragm displacement amplitude no longer increased with the increase of airway pressure, verifying the reliability of this process in achieving objective assessment of respiratory rehabilitation physiological indicators under complex compensation conditions.
[0038] Example 3: This example combines Figures 1 to 2 The process of monitoring respiratory rehabilitation physiological indicators during training is explained, such as... Figure 1 As shown, the respiratory rehabilitation physiological index monitoring process during training includes step 101, which simultaneously acquires transient airway pressure and transient diaphragm thickness, and then proceeds to step 102, which establishes a two-dimensional mapping relationship to construct a respiratory mechanics work loop trajectory. Subsequently, step 103 is executed to extract respiratory mechanics dissipation work by integrating the area of the work loop trajectory. Then, in step 104, the ratio of dissipation work to diaphragm variation amplitude is calculated to obtain the hysteresis compensation amount. Finally, step 105 is reached to correct the inspiratory pressure peak value based on the hysteresis compensation amount and output the monitoring signal.
[0039] like Figure 2 As shown, the synchronous clock source outputs a global timestamp to the pressure sensing unit and sends a signal to the ultrasound imaging detection unit. The respiratory rehabilitation training device transmits the instantaneous airway negative pressure value to the pressure sensing unit, which includes an airway end sensor and a first data acquisition link, through the dotted line. Based on this, the pressure sensing unit outputs the transient airway pressure to the control unit. The ultrasound imaging detection unit, which includes a speckle tracking module and a second data acquisition link, outputs the transient diaphragm thickness to the control unit. The control unit, which is internally configured with a respiratory rehabilitation efficacy evaluation model and a fatigue monitoring index, sends a load adjustment signal to the respiratory rehabilitation training device, which includes a proportional valve and tubing.
[0040] Example 4: During respiratory function remodeling in subjects with neuromuscular conduction disorders, the nonlinear hysteresis between tension output and morphological displacement caused by viscoelastic tissue leads to phase deviation in the physiological signals acquired by the system. To clarify the discrete calculation path and establish a reproducible monitoring method, the measurement range of the pressure sensing unit is selected as follows: to The static resolution is The ultrasonic detection unit is equipped with a speckle tracking module, and the image acquisition frame rate is set to 200Hz. After acquiring a data sequence with consistent sampling times, the system will set the sampling period... Transient airway pressure With transient diaphragm thickness Before constructing this coordinate system, the system performs a morphological dimension alignment procedure, mapping the coordinates to a set of planar coordinate points. Based on the assumption of incompressibility of local muscle tissue, the transient diaphragm thickness change is equivalent to a single-dimensional work stroke along the sound beam direction in the physical model, ensuring that the output dimension of the subsequent closed region area matches the absolute thermodynamic work unit, the joule. The acquisition unit extracts the geometric amplification factor characterizing the effective cross-sectional area of the diaphragm dome based on pre-recorded baseline lung volume data of the subjects, and directly couples it to the bottom-layer analog front-end gain unit of the ultrasound detection unit. To ensure that the source of this spatial deformation amplification factor has a definite geometric engineering basis, the control unit internally pre-sets a biological standard hemispherical septum topological model characterizing the lower boundary of the human thoracic diaphragm. During the extraction process, the system calls speckle tracking... The tracking module calculates the dynamic thickening arc length of the diaphragm fibers on the two-dimensional cross-section in real time as the instantaneous extreme diameter of the septal surface. This is combined with the subject's specific thoracic expansion transverse diameter parameter calculated based on the recorded baseline lung volume image. Through a spatial surface dual integral algorithm, the real-time total area of the three-dimensional dome expansion is continuously calculated. This dynamic integral area result is then divided and normalized with the static base surface area extracted and solidified at the end of expiration. Finally, a cross-sectional geometric amplification factor with dimensionality reduction characteristics and elimination of individual differences is obtained. The system reads the transient diaphragm thickness value and integrates the cross-sectional area weight during the analog-to-digital conversion stage, transforming it into a physical quantity with equivalent volume dimensions. The underlying physical implementation of the above fusion operation is not simply post-processing software multiplication, but rather... The calculated dynamic geometric amplification factor is converted into a controlled bias voltage signal with a defined potential by the built-in digital-to-analog converter (DAC) in the control unit. This signal is physically fed into the control base of an independent programmable voltage-controlled amplifier (VGA) located after the conventional time gain compensation (TGC) module in the ultrasound probe echo receiving link. This drives the voltage amplitude of the original analog envelope signal of the ultrasound radio frequency echo to undergo real-time proportional scaling before entering the ADC sampling conversion. Thus, at the lowest level of hardware circuit processing, a seamless physical dimension conversion from one-dimensional thickness features to a three-dimensional equivalent work volume signal is achieved in the form of an electrophysical multiplier, ensuring the security of biometric information. The original tissue structure features acquired by ultrasound imaging are stored in the acquisition core. The layers are desensitized by a one-way hash algorithm and converted into an anonymous time-series array without physiological signs to ensure that the subsequent operation and processing boundary converges within the range of neutral device data. The control unit performs feature inflection point identification and quantification: calculates the discrete first derivative of airway pressure with respect to the equivalent thickness variable, tracks the evolution trajectory of the derivative in real time, and if it is identified that the first derivative flips from a positive value and remains stable below zero for more than 40ms in a single inspiratory cycle, the first coordinate node of the flip is extracted and established as the feature inflection point of the transition from spontaneous breathing to compensatory breathing. The basis for setting the 40ms maintenance time is that the system needs to use this time-domain filtering hard window to eliminate false positive interference caused by the inertia of a single fluid pipeline or the normal contraction of the diaphragm touching the physiological limit of the transient thickness stagnation.Under this logical constraint, only when the damaged respiratory nerve center involuntarily and excessively calls upon the neck and intercostal accessory muscle groups to produce a sudden burst of contraction, this forceful lifting of the thoracic cavity will not only draw out an additional surge of negative pressure in the entire airway network, but will also inevitably generate a strong reverse mechanical traction on the lower end of the diaphragm through the deformation linkage of the rigid thoracic cavity and abdominal fascia. This forced regression of the surface muscle morphology caused by the unique stress of pure non-local compensation, coupled with the resulting increase in total airway negative pressure, constitutes the only deterministic physiological cause to support the long-term and deep negative reversal of the discrete first derivative. This ensures the logical accuracy and reliability of the judgment of compensatory behavior based on mathematical indicators of reversal. The area of the closed region enclosed by the respiratory mechanical work loop trajectory is calculated to determine the respiratory mechanical dissipation work in a single cycle. The specific calculation formula is as follows: ,in, For the first The work dissipated by respiratory mechanics within one respiratory cycle The total number of sampling points within a single complete respiratory cycle; For sampling point index; This represents the transient airway pressure at the corresponding sampling point. To determine the transient diaphragm thickness at the corresponding sampling point, the compensation amount after determining the inspiratory hysteresis is... Then, the system calculates the corrected maximum inspiratory pressure based on the subject's resting baseline value. The calculation formula is as follows: ,in, This is the corrected maximum inhalation pressure. This is the peak value of the original maximum inspiratory pressure collected by the system. The compensatory amount after inspiratory lag is determined by the ratio of respiratory mechanical dissipation work to the amplitude of diaphragmatic variation. These are the weighting coefficients; The natural constant, the weighting coefficient The value of is determined by the baseline lung volume measured during the preliminary experimental phase. Under the condition that the baseline lung volume is 3000mL to 5000mL, the weighting coefficient is . The linear mapping is in the range of 0.5 to 1.5.
[0041] When the system detects the corrected maximum inhalation pressure When the temperature falls below the subject's preset tolerance threshold and lasts for 2 seconds, it indicates that the diaphragm is fatigued and its compensatory strength exceeds the safety limit. The system then generates a control signal to adjust the proportional valve opening, reducing the inspiratory resistance of the respiratory rehabilitation training device from... Downgraded to This method transforms physiological indicators into mechanical execution quantities, enabling the intensity of rehabilitation interventions to be adjusted based on muscle work status. This avoids the risk of training load exceeding limits caused by airway pressure assessment. Through this numerical deduction process, the monitoring technology achieves end-to-end support from the sensing end to the execution end.
[0042] Example 5: In the initial setup of deploying the monitoring process to a new subject, the system initiates a calibration procedure to determine the decoupling weight coefficients. The baseline values were determined by recording the static diaphragm thickness variation rate and maximum inspiratory pressure of the subjects under zero resistance conditions. The control unit used the least squares method to fit the distribution slope of the data in a two-dimensional state space coordinate system and determined the slope as the biomechanical baseline value. The decoupling weight coefficient was calculated based on the measured lung volume values of the subjects through a linear mapping relationship. In the signal acquisition process, a mean filtering algorithm is used to process the raw physiological signal to eliminate data fluctuations caused by sensor zero-point offset.
[0043] When the monitoring process faces sensor replacement or changes in the monitoring environment, the system initiates a calibration procedure to ensure that the time synchronization deviation between the pressure acquisition link and the ultrasonic detection link is less than 5ms. This is achieved by applying a 1Hz frequency and an amplitude of [missing value] at the airway end. The step pressure signal is captured and the time deviation between the rising edge of the pressure waveform and the starting point of diaphragm movement in the ultrasound image is captured. The control unit adjusts the sampling trigger delay of the pressure sensing unit and the ultrasound detection unit according to the time deviation, thereby constructing the respiratory mechanics work loop trajectory under a unified time base and providing a consistent data benchmark for calculating the inspiratory phase lag compensation.
[0044] Example 6: Under dynamic respiratory function monitoring conditions where the subject is in a fluctuating environment with air pressure and sensor thermal drift, the system uses a baseline offset method to establish the physical zero point of airway pressure. Specifically, at the end of expiration before inhalation, the pressure sensing unit collects 20 pressure sample points within a 100ms steady-state window and updates the initial pressure compensation value under the current environment based on the mean of these sample points. To adapt the scheme to the specific biomechanical characteristics of the subject, the control unit records the static diaphragm thickness variation rate and maximum inspiratory pressure under zero-resistance conditions. The least squares method is used to fit the slope of the data distribution in a two-dimensional state-space coordinate system, and the slope is determined as the biomechanical baseline value. The decoupling weight coefficient is calculated based on the subject's measured lung volume using a linear mapping relationship. In the signal acquisition process, mean filtering is used to process the raw physiological signals in order to eliminate data fluctuations caused by sensor zero-point offset.
[0045] When the system faces sensor replacement or changes in the monitoring environment, the control unit uses a pre-calibration procedure to control the time synchronization deviation between the first and second data acquisition links to within 5ms. This is achieved by applying a 1Hz frequency and amplitude signal to the airway. The step pressure signal is captured, and the time deviation between the rising edge of the pressure waveform and the starting point of diaphragmatic movement in the ultrasound image is obtained. The control unit adjusts the sampling trigger delay of the pressure sensing unit and the ultrasound detection unit according to the time deviation, thereby constructing the respiratory mechanics work loop trajectory under a unified time base. To address the loop non-closure phenomenon caused by asynchronous physical sampling, the control unit establishes a convergence check based on the geometric distance between the last coordinate point and the starting coordinate point in a single respiratory cycle. When the geometric distance exceeds 5% of the diaphragm thickness sampling resolution, cubic spline interpolation is used to generate a compensation node at the end of the time axis to achieve physical closure of the respiratory mechanics work loop trajectory. The convergence compensation constraint is as follows: ,in, This is the closure deviation. The transient diaphragmatic thickness at the beginning of a single respiratory cycle. The transient diaphragm thickness at the end of a single respiratory cycle. This refers to the transient airway pressure at the beginning of a single respiratory cycle. The transient airway pressure at the end of a single respiratory cycle, when the closure deviation... Less than the preset threshold At that time, the determined compensatory amount after inspiratory lag Entering the weight decay correction path.
[0046] Under monitoring conditions where subjects are at risk of diaphragmatic atrophy, the system uses the diaphragmatic thickening score to provide anatomical constraints on the evaluation dimensions of respiratory rehabilitation physiological indicators. The diaphragmatic thickening score is calculated as the ratio of the difference between the transient diaphragmatic thickness at the end of inspiration and the transient diaphragmatic thickness at the end of expiration to the transient diaphragmatic thickness at the end of expiration. The control unit acquires the diaphragmatic thickening score within a single respiratory cycle and uses it as the compensatory amount for inspiratory lag. The validation factor is the diaphragmatic thickening fraction below 20% and the corresponding inspiratory lag compensatory amount. If the decoupling threshold is exceeded, the system will reduce the decoupling weight coefficient. The value of the parameter is used to correct the sensitivity of the final output monitoring signal. This method establishes a correlation between the morphological functional decline of the subject and the mechanical compensation characteristics, avoiding the measurement drift of a single biomechanical parameter under extremely low muscle activity. This makes the determined respiratory rehabilitation physiological indicators have biophysical logical consistency. In the specific algorithm implementation, the system defines the above fatigue monitoring index as the product of the inspiratory phase lag compensation amount and the diaphragm function decline factor. The decline factor is calculated by subtracting the obtained diaphragm thickening fraction in a single respiratory cycle from a constant. This calculation formula establishes a nonlinear amplification mapping path. When the system detects an increase in the proportion of involuntary work by the accessory muscle groups and a significant decline in the intrinsic physical thickening capacity of the diaphragm, the calculated fatigue monitoring index will undergo a leap-like nonlinear increase in the numerical domain. This transforms the hidden complex physiological fatigue into a single quantitative and accurate value with clear derivative triggering characteristics that can be directly compared with the safety threshold.
[0047] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.
Claims
1. A process for monitoring respiratory rehabilitation physiological indicators during training, characterized in that, Includes the following steps: Step 101: During the period when the subject cooperates with the respiratory rehabilitation training device to perform incremental resistance inhalation intervention, the pressure sensing unit and the ultrasound detection unit are controlled by a synchronous clock source to obtain the transient airway pressure at the same sampling time and the transient diaphragm thickness characterizing the physical deformation of the subject's diaphragm. Step 102: Using transient airway pressure as the vertical axis variable and transient diaphragm thickness as the horizontal axis variable, establish a coordinate mapping relationship between transient airway pressure and transient diaphragm thickness in a preset two-dimensional logical state space coordinate system, thereby constructing a respiratory mechanics work loop trajectory that characterizes the biomechanical energy evolution trajectory within a single respiratory cycle. Step 103: The area integral of the nonlinear closed region enclosed by the respiratory mechanical work loop trajectory is performed using the discrete Green's formula to extract the respiratory mechanical dissipation work, which characterizes the hysteresis energy loss value caused by the viscoelastic hysteresis effect of the respiratory muscles. Step 104: Extract the maximum displacement difference of the respiratory mechanical work loop trajectory in the horizontal direction to determine the diaphragm variation amplitude, calculate the ratio of respiratory mechanical dissipation work to diaphragm variation amplitude, and obtain the inspiratory phase lag compensation amount used to quantitatively isolate the involuntary compensation work intensity of the accessory muscle groups. Step 105: Based on the inspiratory phase lag compensation, the maximum inspiratory pressure peak value in the transient airway pressure is weighted and attenuated to determine the subject's respiratory rehabilitation physiological indicators and output a monitoring signal indicating the subject's respiratory function status.
2. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, Step 101 includes: Step 1011, using a built-in hardware timer interrupt to trigger the pressure sensing unit to collect the instantaneous airway negative pressure value of the subject under increasing inspiratory load; Step 1012, using an ultrasound imaging detection unit to synchronously acquire the diaphragm image of the subject under inspiratory load and extract the transient diaphragm thickness; Step 1013, using the global timestamp generated by the hardware clock source as a reference, performing time-scale registration and alignment on the acquired data to generate a data sequence with a unified time base.
3. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, It also includes the following steps: Step 106: Extract the diaphragm thickening fraction of the subject in a single respiratory cycle, and use the diaphragm thickening fraction to weight and correct the inspiratory phase lag compensation amount to generate a fatigue monitoring index that reflects the latent fatigue state of the respiratory muscles; the fatigue monitoring index is used to quantify the dynamic attenuation of the subject's diaphragm contraction efficiency under resistance load.
4. The respiratory rehabilitation physiological indicator monitoring process according to claim 3, characterized in that, It also includes the following steps: Step 1061: When the fatigue monitoring index continues to exceed the preset safety threshold for more than 2 seconds, a load adjustment signal is sent to the respiratory rehabilitation device to reduce the current inspiratory damping load; wherein, the load adjustment signal includes a control quantity for controlling the opening of the proportional valve, so that the inspiratory resistance is reduced to the basic tolerance range of the subject's diaphragm.
5. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, The process of generating the respiratory mechanics work loop trajectory in step 102 includes: capturing the dynamic slope characteristics of transient airway pressure in the coordinate system, identifying the characteristic inflection point of the transition from spontaneous breathing to compensatory breathing, and performing segmented fitting of the respiratory mechanics work loop trajectory based on the characteristic inflection point to construct a mechanical hysteresis trajectory curve with asymmetric geometric characteristics.
6. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, It also includes the following steps: Step 107: Based on the time-domain evolution trend of respiratory mechanical dissipation work, analyze the degree of decoupling between the mechanical response and morphological displacement of the subjects under load training, and construct a respiratory rehabilitation efficacy evaluation model; the efficacy evaluation model is used to reflect the consistency of the neuromuscular control of the diaphragm and accessory muscle groups by the respiratory control center of the subjects.
7. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, Step 101, which involves collecting transient airway pressure, includes: Step 1014, using a preset normalization algorithm to eliminate the linear pressure loss caused by the 1.2mm larynx diameter difference in the respiratory rehabilitation device tubing, and calibrating the sampling reference value of transient airway pressure; the calibration process is based on a tubing fluid dynamics correction model to compensate for the pressure difference between the airway end sensor and the oral cavity end.
8. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, The monitoring signals output in step 105 include: real-time monitoring of the respiratory mechanics work loop trajectory. to The trajectory width variation rate within the pressure range is calculated, and adjustment suggestions for the breathing training program are output. The adjustment suggestions include quantitative settings for the peak inspiratory resistance and inspiratory duration in the next training cycle for the subject.
9. The respiratory rehabilitation physiological indicator monitoring process according to claim 1, characterized in that, It also includes the following steps: Step 108: Statistically analyze the mean fluctuation of respiratory mechanical dissipation work over 5 consecutive respiratory cycles, and dynamically adjust the sampling frequency in step 101 based on the mean fluctuation, so that the sampling frequency is non-linearly switched within the range of 50Hz to 200Hz according to the real-time rate of change of the subject's respiratory rate.