A lung cancer atomization nursing device and a nursing method thereof

Abstract

The present application belongs to the technical field of lung cancer atomization nursing, and particularly relates to a lung cancer atomization nursing device and a nursing method thereof. The device comprises a suction and exhalation double passage and a one-way isolation component. Respiratory signals are collected through MEMS flow and pressure sensors, and turbulent acoustic characteristic vectors are extracted through noise reduction and Fourier transform. Interference is filtered out in combination with an unloaded reference calibration, and airway resistance levels are determined according to airflow main frequencies. Atomization flow rate and particle size are adaptively regulated based on a lesion impedance compensation model, and two-phase parameter synchronous switching is realized in combination with time sequence pre-compensation and respiratory prediction. A two-phase deposition strategy combining airway dredging and deep targeted drug delivery is adopted, and a three-stage residual drug purification structure is matched. The present application is suitable for the pathological characteristics of airway stenosis and shortness of breath of lung cancer patients, has strong drug targeting, significantly improves drug deposition efficiency and utilization rate, reduces drug loss and tail gas pollution, and is safe, stable, efficient and accurate in the atomization nursing process.

Description

Technical Field

[0001] This invention belongs to the field of lung cancer nebulization nursing technology, specifically relating to a lung cancer nebulization nursing device and its nursing method. Background Technology

[0002] In clinical nursing care of lung cancer patients, nebulizers are often used to convert liquid medication into inhalable droplets. These droplets are then delivered to a breathing mask via nebulization tubing and inhaled by the patient, directly targeting the lung lesions to achieve the therapeutic goals of airway care, local drug delivery, and symptom relief.

[0003] Most of the conventional nebulizer devices currently used in clinical practice adopt a constant droplet output mode, mainly designed for common respiratory diseases or postoperative rehabilitation scenarios. They are not specifically developed to take into account the pathological characteristics and physiological state of lung cancer patients. They cannot dynamically adjust the aerosol parameters according to the spatial distribution of lung cancer lesions and the degree of airway narrowing. Large-diameter aerosols have difficulty penetrating narrow airways to reach deep lung lesions, while small-diameter aerosols are easily lost in large quantities during exhalation, making it difficult to achieve precise deposition in the lesion area. Ultimately, this results in low drug utilization and unsatisfactory clinical nursing effects. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a lung cancer nebulization nursing device and its nursing method, so as to solve the problems in the background art. The specific solution is as follows: In a first aspect, the present invention provides a lung cancer nebulization nursing device, including a nebulizer, a breathing mask, an inhalation passage and an exhalation passage; the breathing mask is connected to the ends of the inhalation passage and the exhalation passage, and a one-way isolation component is provided at its airway interface; the inhalation passage and the exhalation passage are respectively provided with an inhalation one-way valve and an exhalation one-way valve at the ends of the breathing mask. The lung cancer nebulization nursing device also includes: The sensing module includes a MEMS flow sensor and a pressure fluctuation sensor installed in the inspiratory pathway near the inspiratory one-way valve. These sensors are used to collect the patient's inspiratory flow rate and respiratory pressure signals, and to extract turbulent acoustic feature vectors that characterize the airway pressure state through signal processing. An adaptive atomization module, integrated within the atomizer, includes an atomizing plate and a frequency conversion drive circuit. The frequency conversion drive circuit regulates the vibration amplitude of the atomizing plate by adjusting the duty cycle of the drive waveform, so as to synchronously switch the median particle size of the drug mist and adjust the atomization outlet flow rate. The residual drug purification module is located in the exhalation pathway and includes a drug mist concentration sensor and a residual drug trap. It is used to monitor the concentration of undeposited drug mist in the exhalation in real time and to trap and purify the residual drug mist in the exhalation. The control module, integrated within the nebulizer and electrically connected to the sensing module, adaptive nebulization module, and residual drug purification module, is used to calculate the equivalent airway impedance in real time based on the turbulent acoustic characteristic vector and the built-in lesion impedance compensation model. It also adjusts the particle size switching threshold and nebulization outlet flow rate of the adaptive nebulization module in real time according to the equivalent airway impedance and the concentration of undeposited drug mist, and achieves end-to-end timing pre-compensation.

[0005] Furthermore, the one-way isolation component includes a rotating shaft, blades, and a rotation detection sensor; the blades are driven by airflow to rotate around the rotating shaft; the control module predicts the switching trend of breathing airflow based on the blade rotation angular acceleration fed back by the rotation detection sensor, thereby constructing a full-link timing pre-compensation algorithm, and synchronously switching the opening and closing states of the inhalation one-way valve and the exhalation one-way valve within a preset prediction time before the airflow direction reverses.

[0006] Furthermore, the control module has an unloaded reference calibration mechanism, namely: Before nebulization is started, the sensing module collects the baseline pressure-flow rate signal of the patient's steady breathing without load, and generates a baseline acoustic spectrum template through Fourier transform. During nebulization, the control module performs frequency domain differential processing on the real-time signal and the baseline acoustic spectrum template to filter out non-pathological disturbances.

[0007] Furthermore, the frequency converter drive circuit regulates the vibration amplitude of the atomizing plate, specifically as follows: The variable frequency drive circuit is based on the dynamic compensation command output by the control module according to the equivalent impedance of the airway and the concentration of undeposited drug mist. It adjusts the duty cycle and frequency of the drive waveform through pulse width modulation to drive the atomizing plate to work in multi-frequency resonance mode. The atomization outlet velocity increases nonlinearly with the increase of the equivalent impedance of the airway, achieving nonlinear dynamic tracking compensation in the range of 0.2m / s to 2.0m / s.

[0008] Furthermore, the drug mist concentration sensor adopts a gated time window acquisition mechanism to collect concentration signals during the stable exhalation period; when the concentration of undeposited drug mist in the exhalation is detected to be higher than a preset threshold, the control module automatically increases the dynamic negative pressure in the exhalation pathway and simultaneously adjusts the nebulization output rate; the residual drug collector is sequentially arranged with a hydrophobic microporous polytetrafluoroethylene filter, an electrostatic activated carbon adsorption layer, and a HEPA high-efficiency filter element along the airflow direction.

[0009] Furthermore, the sensing module performs Fourier transform processing on the collected inspiratory flow rate and respiratory pressure signals to decompose the airflow frequency domain distribution characteristics, and thereby constructs a turbulent acoustic feature vector. The turbulent acoustic feature vector includes the energy density distribution, frequency domain energy ratio, and turbulent spectral entropy in the 100Hz-300Hz frequency band. The frequency domain parameters are normalized and integrated through multi-feature statistical weighted fusion, and the degree of airflow turbulence disorder in the airway is quantified by combining the turbulent spectral entropy. When the fused feature quantity in this frequency band is higher than the preset benchmark threshold, it is determined to be a high airway resistance state caused by tumor occupancy.

[0010] Furthermore, the lesion impedance compensation model incorporates a three-dimensional mapping matrix of characteristic frequency, resistance level, and flow rate compensation coefficient. Combined with the airway equivalent impedance normalization solution method, a respiratory baseline statistical drift compensation is introduced to correct the deviation of the airway equivalent impedance calculation results. The control module uses the real-time calculated turbulent acoustic characteristic vector as an input variable, mapping it to the three-dimensional mapping matrix to calculate the current airway equivalent impedance value. The control module further generates dynamic compensation commands based on the airway pressure resistance value to correct the adaptive nebulization module particle size switching threshold and nebulization outlet flow rate.

[0011] Furthermore, the control module executes a two-phase deposition strategy based on the turbulent acoustic characteristic vector and the lesion impedance compensation model, specifically as follows: The control module performs velocity-pressure fusion analysis on the turbulent acoustic feature vector, and divides the intake phase into the airway opening period and the deep penetration period based on the fusion peak inflection point; the control module determines the current airway pressure resistance state based on the turbulent acoustic feature vector and matches the adaptation parameters accordingly. It delivers a high-flow-rate drug mist with a median particle size of 3.0 μm to 5.0 μm during the airway opening period; During the deep penetration phase, switch to a low-flow-rate aerosol with a median particle size of 0.5μm to 2.5μm.

[0012] Secondly, this invention discloses a method for nebulized nursing care for lung cancer, implemented based on the aforementioned nebulized nursing device for lung cancer, comprising the following steps: S1, before nebulization is started, the reference pressure-flow rate signal of the patient's steady breathing without load is collected by the sensing module, and the reference acoustic spectrum template is generated by Fourier transform and stored in the control module. S2, During the atomization process, the sensing module collects the inhalation phase pressure and flow rate signals in real time. The control module performs frequency domain differential processing on the real-time signals and the reference acoustic spectrum template to filter out non-pathological disturbances and extract the turbulent acoustic feature vectors from them. S3 extracts the energy density, frequency domain energy ratio, and turbulent spectral entropy within the turbulent acoustic feature vector. The parameters are normalized and integrated through multi-feature statistical weighted fusion. After correcting the signal deviation by combining respiratory baseline statistical drift compensation, the parameters are mapped to the three-dimensional mapping matrix of the lesion impedance compensation model to obtain the current airway equivalent impedance. S4, the control module generates dynamic compensation commands based on the equivalent impedance of the airway, drives the frequency conversion drive circuit to adjust the vibration amplitude of the nebulizer through pulse width modulation, so that the nebulizer works in multi-frequency resonance mode; at the same time, the control module predicts the switching trend of breathing airflow based on the blade rotation angular acceleration, and constructs a full-link timing pre-compensation algorithm to synchronously open and close the inhalation one-way valve and the exhalation one-way valve before the airflow direction reverses. S5, the control module performs velocity-pressure fusion analysis on the turbulent acoustic feature vector, divides the inhalation sequence according to the fusion peak inflection point, and executes a dual-phase deposition strategy: during the airway opening period, it outputs a high-velocity drug mist with a median particle size of 3.0μm-5.0μm, and during the deep penetration period, it switches to a low-velocity drug mist with a median particle size of 0.5μm-2.5μm to complete targeted nebulized drug delivery; S6, the drug mist concentration sensor adopts a gated time window acquisition mechanism to collect the concentration signal during the stable exhalation period; the residual drug purification module monitors the concentration of undeposited drug mist in the exhalation in real time; when the detected concentration is higher than the preset threshold, the control module increases the dynamic negative pressure of the exhalation pathway and corrects the nebulization output parameters based on the feedback of the residual drug mist concentration until the exhalation drug mist concentration falls back to the safe threshold range.

[0013] Compared with existing technologies, this invention has the following advantages: By acquiring inspiratory flow rate and respiratory pressure signals and extracting turbulent acoustic feature vectors in the 100Hz-300Hz frequency band through Fourier transform, combined with idle frequency domain benchmark calibration and differential processing to purify airway pathological signals, and relying on a lesion impedance compensation three-dimensional mapping model to quantitatively calculate the equivalent airway impedance, coupled with leaf angular acceleration respiratory switching prediction and a full-link timing pre-compensation mechanism to offset inherent delays, this invention can achieve synchronous switching of dual-phase nebulization parameters during short-cycle shallow and rapid inhalation in lung cancer patients, while simultaneously executing... This approach employs a dual-phase deposition strategy: high flow rate and large particle size during the airway opening phase for unblocking, and low flow rate and small particle size for targeted deep penetration. It also utilizes a dual closed-loop system—airway impedance and drug concentration during the stable expiratory phase—to real-time adjust the particle size switching threshold and nebulization flow rate. Combined with a gated time window acquisition mechanism and a three-level gradient residual drug capture and purification structure, this approach effectively adapts to the pathological characteristics of airway mechanical stenosis and shortness of breath in lung cancer patients. It significantly improves lesion drug deposition efficiency and drug delivery targeting, reduces ineffective drug loss and residual drug leakage pollution, and achieves a synergistic effect of precise adaptation, efficient drug delivery, and safe purification in lung cancer nebulization care. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the structure of a lung cancer nebulization nursing device according to the present invention; Figure 2 This is a schematic diagram of the frame structure of a lung cancer nebulization nursing device according to the present invention; Figure 3 for Figure 1 A magnified view of a section at point A in the middle; Figure 4 for Figure 1 A magnified view of a section at point B in the middle; Figure 5 This is a flowchart illustrating a lung cancer nebulization nursing method according to the present invention; The reference numerals in the accompanying drawings include: 1. Nebulizer; 2. Breathing mask; 3. Inhalation pathway; 31. Inhalation check valve; 32. MEMS flow sensor; 33. Pressure fluctuation sensor; 4. Exhalation pathway; 41. Exhalation check valve; 42. Drug mist concentration sensor; 43. Residual drug trap; 5. One-way isolation component; 51. Shaft; 52. Blade; 53. Rotation detection sensor; 6. Sensing module; 7. Adaptive nebulization module; 71. Nebulizing plate; 72. Variable frequency drive circuit; 8. Residual drug purification module; 9. Control module. Detailed Implementation

[0016] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0017] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present application. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0018] In the description of this invention, unless otherwise explicitly specified and limited, the term "connection" or similar designation indicating a connection between components should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0019] Conventional nebulizers only use a constant droplet output mode for general drug delivery. They are not adapted to the pathological characteristics of airway stenosis caused by tumors in lung cancer patients in terms of structure and control logic. They cannot identify the level of airway pressure resistance in real time and dynamically adjust the particle size and nebulized airflow intensity. This can easily cause large-diameter droplets to remain in the narrow airway and small-diameter droplets to be lost with exhalation. The drugs are difficult to deposit accurately in the lung lesion area, resulting in low overall drug utilization and limited nebulizer care effects.

[0020] Therefore, this invention discloses a lung cancer nebulization nursing device and its nursing method. Based on airway turbulence acoustic feature recognition, multi-parameter statistical quantitative analysis, adaptive flow rate dynamic compensation, time-division dual-phase targeted drug delivery, and closed-loop purification of exhaled residual drug mist, it realizes individualized and differentiated nebulization nursing for lung cancer patients, taking into account both airway clearing and flushing and deep drug delivery to lung lesions, effectively improving the targeted deposition effect of drugs.

[0021] like Figure 1 , Figure 2As shown, this invention discloses a lung cancer nebulization nursing device, comprising a nebulizer 1, a breathing mask 2, an inspiratory pathway 3, and an expiratory pathway 4. The breathing mask 2 is connected to the ends of the inspiratory pathway 3 and the expiratory pathway 4, respectively, providing a respiratory interface for the patient and guiding the separation of inspiratory and expiratory airflows. A one-way isolation component 5 is provided at the connection point between the breathing mask 2 and the two pathways to achieve one-way isolation of inspiratory and expiratory airflows, preventing interference between the two airflow paths. The lung cancer nebulization nursing device also includes a sensing module 6, an adaptive nebulization module 7, a residual drug purification module 8, and a control module 9. The modules are electrically connected to complete signal transmission and command interaction, forming a complete closed-loop adaptive nebulization control system. The units cooperate to ensure stable operation of the device.

[0022] Among them, the sensing module 6, as the core of patient respiratory signal acquisition, is used to acquire the raw signals of airflow pressure and velocity throughout the breathing process, providing a data foundation for subsequent airway turbulence feature extraction and airway equivalent impedance calculation; the adaptive nebulization module 7, as the core of drug mist generation and dynamic control, realizes the switching of median particle size of drug mist and adaptive adjustment of nebulized airflow intensity, adapting to individualized drug administration needs under different airway pressure resistances; the residual drug purification module 8 is used to perform multi-stage interception and purification of exhaled residual drug mist aerosol, avoiding drug leakage and environmental hazards, while reducing ineffective drug loss; the control module 9 is the core of the entire device operation control, coordinating the operation sequence of each module, dynamic parameter compensation, and overall safety closed-loop control, and is the key unit to realize the adaptive precision nebulization nursing of this invention.

[0023] Specifically, in this embodiment, the sensing module 6 is internally equipped with a MEMS flow sensor 32 and a pressure fluctuation sensor 33, such as... Figure 2 , Figure 3As shown, both types of sensors are positioned on the side of the inspiratory passage 3 near the inspiratory one-way valve 31 to ensure that the collected respiratory signals accurately reflect the actual state of the patient's airway. The MEMS flow sensor 32 employs a differential pressure MEMS sensing principle, calculating the airflow velocity in real time by detecting the pressure difference before and after the airflow and outputting a continuously changing voltage time-domain signal. This allows for real-time acquisition of the inspiratory flow velocity time-domain signal during respiration, capturing the dynamic changes in flow velocity throughout the entire inspiratory process. The pressure fluctuation sensor 33 employs a piezoresistive MEMS sensing principle, converting the diaphragm deformation caused by the airway airflow pressure into an electrical signal, simultaneously acquiring the respiratory pressure time-domain signal, and obtaining the real-time characteristics of airway pressure fluctuations. The sensing module 6 incorporates a simple signal preprocessing unit, which processes the dual-channel raw signals using a moving average filter and amplitude gain correction algorithm. In this embodiment, the moving average filter window length is set to 15 to smooth out glitches and noise in the raw signal. In this embodiment, the signal preprocessing unit also includes a low-pass hardware filter with a cutoff frequency of 500Hz, which is used to block the electromagnetic coupling interference of the high-frequency drive signal of the atomizing plate to the low-frequency turbulent acoustic signal; at the same time, the signal amplitude normalization correction is completed by fixing the amplitude gain coefficient, effectively eliminating basic interference signals such as pipeline mechanical vibration, environmental electromagnetic interference, and airflow stray disturbances, and reducing the deviation caused by signal distortion to subsequent frequency domain analysis.

[0024] Furthermore, the sensing module 6 performs frequency domain transformation operation after windowing the preprocessed clean time-domain signal. In this embodiment, the signal sampling frequency is set to 1024Hz. To suppress the spectral leakage caused by finite-duration signal truncation, a Hanning window function is introduced to weight and normalize the time-domain signal before the operation. The expression of the Hanning window function is as follows: in, The total length of the window function. This refers to the sequence number of the discrete sampling sequence. Using the Hanning window for weighting can smooth abrupt changes in the signal's time-domain boundaries, constrain spectral energy diffusion tails, and improve the accuracy of frequency point energy calculations.

[0025] Considering the rapid respiratory reversal and short control window of lung cancer patients, and to meet the real-time control requirements of airway inflection point identification and pre-judgment of air valves, this embodiment adopts an overlapping sliding block real-time sampling architecture, compressing the single-frame signal processing window to 125ms to adapt to the respiratory airflow switching time limit requirements. This embodiment uses a 128-point Fast Fourier Transform to convert the time-domain signal to the frequency-domain signal. The mathematical relationships of the Discrete Fourier Transform are as follows: in, This is the weighted discrete-time domain breathing signal. For the transformed spectral data at the corresponding frequency points, in this embodiment, the window length and the number of transformation points are taken to be the same, satisfying... Relying on the overlapping sliding frame continuous update mechanism, the airflow frequency component information is fully preserved while shortening the calculation window. The continuously fluctuating breathing time-domain waveform is decomposed into frequency components, and the airflow signal information corresponding to different oscillation frequencies is extracted, thus completing the complete conversion of time-domain signal to frequency-domain spectrum data.

[0026] The integrated set of all airflow frequency domain distribution features obtained after conversion constitutes the turbulent acoustic feature vector. Its core features directly correspond to the actual state of the patient's airway: when the airway is unobstructed, the airflow is in a stable laminar state, and the spectrum is concentrated in the low-frequency range; when a tumor causes airway narrowing, the airflow generates turbulent eddies at the narrowing point, and the dominant frequency of the spectrum rises accordingly, thus achieving non-invasive identification of airway compression. This invention limits the airway pathology sensitive frequency band to 100Hz~300Hz. This frequency band is the core energy frequency band of airflow turbulence disturbance after lung cancer tumors cause airway narrowing. The turbulent acoustic feature vector includes three core feature parameters: energy density distribution, frequency domain energy ratio, and turbulent spectral entropy within this frequency band. To achieve accurate quantification of the degree of airway disturbance, this invention introduces Shannon information entropy to characterize the degree of airflow turbulence disturbance within the airway, i.e., turbulent spectral entropy, calculated as follows: in, For turbulent spectral entropy, This represents the normalized percentage of energy at the corresponding frequency point relative to the total energy of the frequency band. This refers to the number of discrete frequency points within the sensitive frequency band of 100Hz to 300Hz. In this embodiment, the sampling frequency is 1024Hz, the number of FFT points is 128, and the frequency resolution is 8Hz, corresponding to the number of discrete frequency points. The physical correspondence is as follows: the higher the degree of airway compression and narrowing caused by lung cancer tumors, the more intense the turbulent disturbance and the higher the airflow disorder when the airflow passes through the narrow cavity, and the lower the corresponding turbulent spectrum entropy value; the higher the airway patency, the more stable and orderly the breathing airflow, and the higher the turbulent spectrum entropy value, thereby realizing the quantitative characterization of the airway pathological state.

[0027] To avoid the limitations of single-frequency domain feature discrimination and improve the stability of airway state identification, this invention performs multi-feature statistical weighted fusion and normalization integration processing on three features: energy density, frequency domain energy ratio, and turbulent spectral entropy. The formula for calculating the fused feature quantity is as follows: in, For multi-feature fusion parameters; Frequency band energy density; The turbulent spectrum entropy; The variance of the energy spectrum in the frequency band; , , Based on the statistical weighting coefficients derived offline from a large number of clinical respiratory samples, the specific values ​​used in this embodiment are: , , The weighting coefficients satisfy the normalization constraint. In this embodiment, the preset threshold for judging the fused feature quantity is 0.75. When the final fused feature quantity... When the threshold is reached, the airway is considered to be in a state of high airway resistance caused by tumor lesions; when the fusion feature value is below the threshold, the airway is considered to be in a state of open airway and low resistance.

[0028] In this embodiment, the adaptive atomization module 7 integrates an atomizing plate 71 and a frequency conversion drive circuit 72. The atomizing plate 71 employs the ultrasonic atomization principle, relying on the cavitation and fragmentation effect generated by its high-frequency vibration to disperse the liquid medicine into tiny droplets. A piezoelectric ceramic atomizing plate with a diameter of 16mm and an inherent resonant frequency of 1.7MHz can be selected. The atomizing plate 71 is located within a relatively sealed cavity, and during vibration, it simultaneously compresses and pressurizes the air within the cavity. This pressure is then channeled through 200 micropores (2μm in diameter) evenly distributed on the surface of the atomizing plate to form a directional, focused jet, ensuring stable and uniform distribution of the medicine mist output. The frequency conversion drive circuit 72, as the driving core of the atomizing plate 71, uses pulse width modulation (PWM) to output a driving waveform. By adjusting the duty cycle of its output waveform, it synchronously controls the vibration amplitude and ultrasonic resonant working mode of the atomizing plate 71. In this embodiment, the PWM duty cycle adjustment range is set to 10%~80%, and the duty cycle and the vibration amplitude of the atomizing plate are linearly positively correlated, satisfying the following relationship: in, The amplitude of the atomizing plate vibration is expressed in μm. This refers to the PWM duty cycle. This is a scaling factor, used in this embodiment. .

[0029] The specific control logic is as follows: A larger duty cycle results in a higher vibration amplitude of the atomizing plate, a stronger pressurization effect in the sealed cavity, and a higher outlet airflow velocity of the directional jet. Simultaneously, it switches to a high-energy, high-frequency resonance state, allowing the atomizing plate to operate in multi-frequency resonance mode, resulting in stronger vibration cavitation and fragmentation, and larger droplet sizes formed from the broken-up drug solution. Conversely, a smaller duty cycle results in a lower vibration amplitude of the atomizing plate, a weaker pressurization effect in the sealed cavity, and a lower outlet airflow velocity of the directional jet. Simultaneously, it switches to a low-energy, low-frequency resonance state, maintaining multi-frequency resonance mode operation, resulting in weaker vibration cavitation and fragmentation, and smaller droplet sizes formed from the broken-up drug solution. In this embodiment, the adjustable range of the atomizing outlet airflow velocity is 0.2 m / s to 2.0 m / s. The driving adjustment amplitude is linearly related to the airflow velocity. The control module 9 can receive the equivalent impedance signal of the airway output by the sensing module 6 in real time and automatically switch to the appropriate median particle size of the drug mist. Among them, the high-flow-rate, high-energy mode outputs large-particle-size drug mist of 3.0μm to 5.0μm, which is used to impact and clear narrow airways caused by tumor lesions and reduce airway resistance; the low-flow-rate, low-energy mode automatically switches to small-particle-size drug mist of 0.5μm to 2.5μm, which is used for diffusion drug delivery in the peripheral lung lesion area, respectively meeting the dual needs of clearing narrow airways and deep lung targeted drug delivery.

[0030] In this embodiment, the residual drug purification module 8 is fixedly arranged inside the exhalation passage 4, and its layout is consistent with the direction of exhaled airflow to ensure that the exhaled residual drug mist aerosol can flow completely through the purification structure to complete multi-stage treatment. The residual drug purification module 8 includes a drug mist concentration sensor 42 and a residual drug collector 43.

[0031] The drug mist concentration sensor 42 adopts a gated time window acquisition mechanism, which collects the drug mist concentration in the exhaled airflow in real time at a sampling frequency of 100Hz throughout the process and generates a concentration-time change curve. The control module 9 performs sliding average smoothing and stable segment identification on the curve: the initial 0.3s of exhalation corresponds to the interval of residual drug mist in the respiratory mask cavity, and the data in this segment is invalid interference data and is directly discarded; after discarding the initial segment, when the concentration fluctuation of 10 consecutive sampling points is ≤±5% (relative to the average concentration of consecutive sampling points), it is determined to be the exhalation stable period. At this time, the airflow is the undeposited drug mist actually exhaled by the patient's lungs. The control module 9 only extracts the average concentration of this stable plateau period as valid detection data, discards the interference of residual drug mist in the mask, and ensures that the concentration detection results truly reflect the drug deposition effect in the lungs.

[0032] In this embodiment, the preset safety threshold for the concentration of undeposited pesticide spray is 15 μg / m³. 3When the effective detection concentration in the stable phase is higher than the preset threshold, it indicates that the current nebulization output parameters are not well adapted to the patient's airway and that the drug is ineffectively lost. The control module 9 responds to the concentration feedback signal, increases the dynamic negative pressure inside the expiratory pathway to optimize the airway flow field, and simultaneously adjusts the overall nebulization output rate and drug delivery intensity in conjunction with the dynamic compensation command, thus constructing a safe control closed loop that matches residual drug mist emission, airway adaptation regulation, and nebulized drug delivery dosage.

[0033] To avoid interference with detection and waste caused by residual undeposited medication mist inside the breathing mask 2, the control module 9 relies on a pre-judgment mechanism before breathing switches. It preemptively cuts off the nebulization output and closes the inspiratory one-way valve 31 as the inspiratory phase is about to end, stopping the delivery of new medication mist to the mask cavity. Simultaneously, the expiratory one-way valve 41 opens at the moment of exhalation, allowing residual medication mist inside the mask to naturally enter the residual medication collector 43 for multi-stage purification via the patient's own exhalation airflow, minimizing ineffective drug loss. The residual medication collector 43 is used to perform multi-stage interception and purification of residual medication mist aerosol in the exhaled airflow, preventing drug aerosol leakage and environmental pollution, while also reducing the risk of passive inhalation for medical personnel. Along the airflow direction, the residual drug collector is sequentially equipped with a hydrophobic microporous PTFE filter, an electrostatic activated carbon adsorption layer, and a HEPA high-efficiency filter. The multi-layered purification structure works in a coordinated manner to filter step by step: the hydrophobic microporous PTFE filter intercepts large-diameter droplets and liquid condensation, preventing moisture blockage on the inner wall of the pipe; the electrostatic activated carbon adsorption layer, relying on electrostatic adsorption and porous adsorption characteristics, retains the effective components of organic drugs in the drug mist, reducing drug residues in the environment; the HEPA high-efficiency filter filters micron-sized suspended aerosols in the airflow, achieving clean exhaust airflow and ultimately ensuring that the exhaled airflow is harmlessly discharged.

[0034] In this embodiment, the control module 9 is stably electrically connected to the sensing module 6, the adaptive atomization module 7, and the residual drug purification module 8, respectively, to ensure timely signal transmission and accurate command execution between the modules, thus providing a guarantee for the closed-loop control of the entire device.

[0035] The control module 9 incorporates an idle baseline calibration mechanism, which serves as the foundational unit for the device's anti-interference preprocessing. Its core function is to filter out various non-pathological interference components, improving the accuracy of subsequent airway equivalent impedance calculation and resistance level determination. The idle calibration mechanism is automatically triggered before the formal start of the nebulization process, guiding the patient to complete 3 to 5 steady, deep, idle breaths. Simultaneously, the sensing module 6 collects pressure and flow signals across multiple complete respiratory cycles, preprocesses and performs frequency domain transformation on multiple sets of raw signals, generating a unique individual baseline acoustic spectrum template, which is then stored in the internal storage unit of the control module 9. Throughout the subsequent nebulization process, the control module 9 performs frequency domain differential processing on the respiratory signal spectrum collected in real-time by the sensing module 6 and the pre-stored baseline acoustic spectrum template. This process eliminates irrelevant interference components such as tubing mechanical vibration, respiratory baseline shift, and routine physiological respiratory fluctuations, purifying the effective respiratory signal and ensuring the data purity for subsequent turbulence feature extraction, statistical fusion calculation, and airway impedance calculation. It also provides an original baseline reference for subsequent respiratory baseline statistical drift compensation.

[0036] Meanwhile, the control module 9 has a built-in signal analysis unit that can receive the turbulent acoustic feature vector transmitted by the sensing module 6 and extract the airflow dominant frequency parameters and corresponding frequency band energy amplitude information within the turbulent acoustic feature vector. The control module 9 also has a built-in lesion impedance compensation model, which has preset... A three-dimensional mapping matrix of characteristic frequency, drag level, and velocity compensation coefficient; wherein the physical definitions of the three dimensions are as follows: First dimension The primary airflow frequency, with a parameter domain covering the entire frequency band sensitive to lung cancer airway pathology (100Hz~300Hz); the second dimension... This represents the equivalent airway impedance value, with a parameter definition domain covering the entire airway resistance range from 0.3 kPa·s / L to 2.0 kPa·s / L in healthy individuals to those with severe tumor stenosis; Third dimension It is a set of parameters for full atomization compensation, including the flow rate compensation coefficient, the upper limit of atomization flow rate, the particle size of the drug mist during the airway opening period, and the particle size of the drug mist during the deep penetration period.

[0037] All calibration data for this matrix originates from a 3D-printed biomimetic physical model of lung cancer airway stenosis combined with CFD airflow turbulence offline simulation bench tests. Strictly adhering to the clinical anatomical grading standards for lung cancer airway stenosis, parameter sampling and fitting were performed across all operating conditions before offline calibration and storage within the module. This matrix is ​​a static parameter lookup table database with built-in bilinear interpolation lookup rules and interval boundary catch-up logic: for input operating conditions between calibration nodes, bilinear interpolation is used to calculate atomization compensation parameters; when the airflow dominant frequency > 300Hz or the airway equivalent impedance ≥ 2.0kPa·s / L, catch-up control is performed according to the upper limit parameters of the severe airway pressure condition. The matrix can adjust the parameters based on the real-time input airflow dominant frequency. Equivalent impedance of airway The mapping output corresponds to the fogging compensation parameters. .

[0038] The complete dataset corresponding to the full-condition hierarchical calibration within the matrix is ​​as follows: Airway patency condition: dominant airflow frequency Airway equivalent impedance • s / L, corresponding to the flow rate compensation coefficient. Atomization flow rate limit Particle size during airway opening period Particle size during deep penetration period ; Mild airway compression conditions: dominant airflow frequency Airway equivalent impedance The corresponding compensation parameter is the flow velocity compensation coefficient. Atomization flow rate limit Particle size during airway opening period Particle size during deep penetration period ; Moderate airway compression conditions: dominant airflow frequency Airway equivalent impedance The corresponding compensation parameter is the flow velocity compensation coefficient. Atomization flow rate limit Particle size during airway opening period Particle size during deep penetration period ; Severe airway compression conditions: dominant airflow frequency Airway equivalent impedance The corresponding compensation parameter is the flow velocity compensation coefficient. Atomization flow rate limit Particle size during airway opening period Particle size during deep penetration period ; The above-mentioned parameters fully calibrate the one-to-one mapping relationship between the main airflow frequency, the equivalent impedance of the airway, and the nebulization operation parameters. The calibration parameters cover the upper limit of nebulization flow rate, the threshold of drug mist particle size, and the weighting of the output ratio of dual-phase drug delivery droplets corresponding to each resistance level.

[0039] To compensate for impedance calculation deviations caused by individual differences in respiratory baselines and fluctuations in environmental conditions, this embodiment introduces a statistical drift compensation for respiratory baselines. This is combined with the normalized solution formula for airway equivalent impedance to correct for deviations in the calculation results. The formula for calculating airway equivalent impedance is as follows: in, Real-time airway equivalent impedance (unit: kPa・s / L). The respiratory pressure difference (unit: kPa); The real-time average inspiratory flow rate (unit: L / s); The statistical drift compensation for the respiratory baseline (unit: kPa・s / L) is generated from the no-load reference calibration results and is used to compensate for system deviations caused by individual respiratory baseline shifts, changes in ambient temperature and humidity, and airflow losses in the tubing. Control module 9 maps the turbulent acoustic feature vector, after multi-feature statistical weighted fusion, to a three-dimensional mapping matrix as input parameters. It then uses the normalized solution formula mentioned above to calculate the accurate equivalent airway impedance value and generates corresponding dynamic compensation commands based on the impedance results, enabling adaptive correction of subsequent nebulization module operating parameters.

[0040] In this embodiment, the airway pressure resistance level is divided according to the airflow dominant frequency distribution range corresponding to the turbulent acoustic characteristic vector. The division rules are compatible with the sensitive frequency range: when the airway airflow dominant frequency is below 100Hz, it is determined that the airway is unobstructed and there is no obvious lesion pressure; the dominant frequency range corresponding to mild resistance is 100Hz~150Hz, the dominant frequency range corresponding to moderate resistance is 150Hz~220Hz, and the dominant frequency range corresponding to severe resistance is 220Hz~300Hz.

[0041] Control module 9 combines the lookup results of the three-dimensional mapping matrix to match differentiated adaptive control strategies for different airway resistance levels, and performs dynamic flow rate compensation based on the equivalent airway impedance. Under mild resistance conditions, control module 9 calls the conventional nebulization flow rate setting, with a flow rate range of 0.2 m / s to 0.8 m / s, prioritizing the output of small-diameter drug mist of 0.5 μm to 2.5 μm, focusing on diffusion-based drug delivery to lung lesions; under moderate resistance conditions, the nebulization outlet flow rate is moderately increased, with a flow rate range of 0.8 m / s to 1.4 m / s, balancing the output ratio of large-diameter and small-diameter drug mists, while also considering airway patency and deep lung drug delivery; under severe resistance conditions, control module 9 automatically triggers the maximum flow rate compensation mode, increasing the nebulization flow rate to the upper limit of the adjustable range of 2.0 m / s, prioritizing the output of high-flow-rate large-diameter drug mist of 3.0 μm to 5.0 μm, enhancing the impact and patency-clearing effect on tumor-stenotic airways.

[0042] To coordinate the regulation of drug mist deposition and exhaust emissions, control module 9 responds to the feedback signal from drug mist concentration sensor 42. When the drug mist concentration in the exhaled airflow is detected to be higher than 15 μg / m³, control module 9 will respond accordingly. 3 When the preset safety threshold is reached, it indicates that the drug deposition rate in the lungs is low and the ineffective loss is large. The system automatically increases the dynamic negative pressure inside the expiratory pathway 4 to accelerate the expulsion of residual airflow, and simultaneously regulates the overall nebulization output rate and appropriately reduces the nebulized drug dosage. This creates a safe control closed loop that matches the drug dosage, airway adaptation control and harmless exhaust gas emission, thereby improving drug utilization and reducing ineffective drug loss while ensuring the nebulization nursing effect.

[0043] In this embodiment, the unidirectional isolation component 5 includes a rotating shaft 51, blades 52, and a rotation detection sensor 53. These three components work together to not only identify the airflow direction but also predict the switching trend of breathing airflow through dynamic changes in blade deflection, thus achieving pre-control of unidirectional airflow opening and closing. The blades 52 are made of low-inertia, lightweight materials with extremely low rotational inertia. Figure 2 As shown, the one-way isolation component 5 is installed at the airway interface of the breathing mask 2 corresponding to the inspiratory passage 3 and the expiratory passage 4. Its installation position is adapted to the design: the airflow in the inspiratory passage 3 is located to the right of the vertical central axis of the rotating shaft 51, which facilitates the airflow to drive the blade 52 to rotate counterclockwise during inhalation; the inlet and outlet airways of the breathing mask 2 are located above the horizontal central axis of the rotating shaft 51, ensuring that the airflow can pass smoothly from the top of the rotating shaft 51 during the patient's breathing, and can drive the blade 52 to rotate clockwise during exhalation.

[0044] Specifically, when the respiratory airflow passes through the airway, it directly drives the blades 52 to rotate around the axis 51, and the direction of blade rotation strictly corresponds to the direction of airflow: during inhalation, the airflow flows from the inhalation passage 3 to the breathing mask 2, causing the blades 52 to rotate counterclockwise; during exhalation, the airflow flows from the breathing mask 2 to the exhalation passage 4, causing the blades 52 to rotate clockwise. The rotation detection sensor 53 collects the deflection angle, instantaneous angular velocity, and angular acceleration changes of the blades 52 in real time. The physical relationship of the blade motion is as follows: in, This refers to the real-time deflection angle of the blades. Sampling time, The instantaneous angular velocity of the blade. This refers to the blade rotation angular acceleration. Control module 9 identifies the transition trend of the breathing airflow based on changes in the blade rotation angular acceleration and presets a critical angular velocity threshold for airflow reversal. When the airflow trend corresponding to the angular acceleration meets the prediction conditions, the control module 9 can predict the inhalation and exhalation transition node and receive the real-time airflow direction signal and airflow switching prediction signal uploaded by the rotation detection sensor 53. Before the airflow direction reverses, the inhalation one-way valve and the exhalation one-way valve are opened and closed simultaneously.

[0045] The control module 9, combining real-time airflow direction and switching prediction signals, performs pre-emptive opening and closing control of the inspiratory one-way valve 31 and the expiratory one-way valve 41: During stable ventilation in the inspiratory phase, the inspiratory one-way valve 31 remains open and the expiratory one-way valve 41 remains closed, ensuring that the nebulized mist smoothly enters the patient's airway; when an airflow switch is detected, the nebulization output is preemptively cut off and the valve status is switched; during the expiratory phase, the inspiratory one-way valve 31 remains closed and the expiratory one-way valve 41 remains open, ensuring that all residual nebulized mist exhaled enters the residual medication purification module 8. This achieves time-separated independent opening and closing of the inspiratory and expiratory pathways, eliminating crossflow and backflow problems caused by airway switching lag, effectively avoiding mutual interference between the two airflows, and ensuring a stable and continuous nebulization nursing process.

[0046] Meanwhile, the control module 9 incorporates a dual-phase deposition strategy, which is the core of targeted drug delivery for lung cancer patients, adapting to the dynamic changes in airway morphology throughout the entire inhalation process. The control module 9 fuses and analyzes the real-time inspiratory flow rate and respiratory pressure signals transmitted by the sensing module 6, reconstructing a complete and continuous respiratory cycle waveform, and constructing flow-pressure fusion characteristic parameters. The fusion relationship is as follows: in, The fusion feature value of the respiratory signal (dimensionless); Real-time intake airflow velocity (unit: m / s). The maximum inspiratory flow rate of the patient was collected during the no-load calibration phase (unit: m / s). The respiratory pressure difference (unit: kPa) The maximum respiratory pressure difference of the patient collected during the no-load calibration phase (unit: kPa). , These are the flow velocity weighting coefficient and the pressure weighting coefficient, respectively, in this embodiment. , The weighting coefficients satisfy the normalization constraint. .

[0047] Control module 9 presets a two-stage boundary critical threshold. Using the relationship between fusion feature values ​​and threshold values ​​as the criterion for inflection point determination, a single complete inhalation process is seamlessly divided into two continuous action phases: the airway opening phase and the deep penetration phase. During the airway opening period, when Switch to the deep penetration phase at that time.

[0048] To adapt to the physiological characteristics of short-cycle, shallow, and rapid inhalation in lung cancer patients and eliminate the inherent delays in sensor acquisition, signal processing, drive response, and airway transmission, this embodiment constructs a full-link timing pre-compensation algorithm through the blade angular acceleration prediction mechanism of the unidirectional isolation component 5. The control module 9 pre-stores the inherent delay parameters of the fixed links in the entire link and completes the total delay calculation according to the following formula: in, The signal acquisition delay for the MEMS flow and pressure sensor is in the range of microseconds to milliseconds, and in this embodiment it is no more than 2ms. The computational delay for frequency domain analysis, feature fusion, and impedance calculation shall not exceed 200 μs; The command response delay for the frequency converter drive circuit is fixed and not greater than 50μs; The delay in the airflow delivery of the drug mist through the inhalation pathway is calculated according to... Real-time calculation, in which The effective length of the inhalation pathway (fixed value ≤ 15cm). This is the real-time atomization outlet flow rate. Control module 9 will calculate the total delay. Set as the pre-trigger duration for switching atomization parameters, i.e. .

[0049] Based on this, control module 9 determines the blade rotation angular velocity. angular acceleration Real-time assessment of respiratory trends, when and The timing is determined to be the initiation of inhalation, and the flow rate-pressure fusion characteristic value is monitored in real time. ,when Approaching the two-stage boundary critical threshold And satisfy At this time, it is predicted that the inspiratory phase is about to enter the inflection point. The control module 9 issues a switching command for the atomized particle size and outlet flow rate in advance within the T pre-transition time before the inspiratory start or the arrival of the phase inflection point. In this embodiment, the effective length of the inspiratory pathway is limited to no more than 15cm, and the drug atomization delivery delay T is compressed to the range of 75ms~750ms. With the full-link timing pre-compensation algorithm, the delay lag problem in each link can be eliminated, ensuring that the parameter switching of the dual-phase deposition strategy is synchronized with the patient's inspiratory phase.

[0050] During the airway opening phase, the patient's airway rapidly expands to its maximum ventilation opening. Control module 9 calls the corresponding adjustment parameters and outputs a high-flow-rate drug mist with a median particle size of 3.0μm~5.0μm. Relying on the strong airflow impact effect, it clears the airway narrowing caused by the tumor, opening a smooth airway for subsequent deep drug penetration. During the deep penetration phase, the patient's airway morphology tends to be stable. Control module 9 automatically switches the nebulization output parameters and releases a low-flow-rate, gentle drug mist with a median particle size of 0.5μm~2.5μm. The airflow is gentle and uniform, and can smoothly penetrate into the terminal area of ​​the lung lesion through the cleared airway, achieving efficient targeted deposition of the drug at the lesion site, significantly improving the effective utilization rate of the drug and the overall nebulization treatment effect.

[0051] In one embodiment, when the dominant frequency of the airflow corresponding to the turbulent acoustic characteristic vector is in the range of 100Hz to 300Hz, it indicates that the airway of a lung cancer patient is under high resistance and pressure due to tumor occupancy. Control module 9, relying on the pre-stored three-dimensional parameter mapping relationship within the lesion impedance compensation model, adaptively matches the corresponding nebulization operation parameters according to the airway resistance level. The overall adaptation rule is: the higher the airway pressure resistance, the higher the nebulization airflow intensity, and the higher the output priority of large-particle impact-type drug mist. This allows for personalized adaptive nebulization drug delivery based on the degree of lesion compression, improving the targeting and adaptability of nebulization care.

[0052] The complete workflow of the entire device consists of the following steps: pre-emptive empty calibration, unidirectional airway isolation and airflow trend prediction, respiratory signal acquisition and preprocessing, frequency domain feature extraction, airway resistance determination, parameter adaptive compensation, dual-phase time-segmented targeted nebulization drug delivery, and multi-stage purification of residual exhaust gas. Each process is seamlessly integrated and operates in a closed loop, forming a nebulization care system tailored to the specific pathological characteristics of lung cancer patients. This effectively addresses issues such as low drug utilization, poor lesion deposition, and lack of pathologically specific design in existing equipment. It balances airway patency with deep targeted drug delivery, achieving safe, efficient, and precise nebulization care.

[0053] like Figure 5 As shown, the present invention also discloses a nursing method for lung cancer nebulization care, implemented based on the above-mentioned lung cancer nebulization care device, comprising the following steps: S1. Before nebulization is started, the control module 9 initiates the no-load reference calibration mechanism. The sensing module 6 collects the reference pressure-flow rate signal under the patient's stable no-load breathing state. After the signal is initially denoised by the preprocessing unit built into the sensing module 6, it is windowed by the Hanning window and subjected to 128-point fast Fourier transform to generate a reference acoustic spectrum template. This template is stored in the internal storage unit of the control module 9 to provide a pure reference for subsequent airway signal analysis.

[0054] S2, during nebulization, the sensing module 6 collects the raw signals of the patient's inspiratory phase pressure and flow rate in real time. The control module 9 performs frequency domain differential operation on the real-time collected signals and the reference acoustic spectrum template stored in S1 to effectively filter out non-pathological disturbances such as tubing mechanical disturbances, environmental electromagnetic interference, and normal physiological respiratory fluctuations. The turbulent acoustic feature vector containing energy density, frequency domain energy ratio, and turbulent spectrum entropy is extracted from the noise-reduced pure signal and uploaded to the control module 9 for subsequent analysis.

[0055] S3, control module 9 extracts three core parameters within the turbulent acoustic feature vector: energy density, frequency domain energy ratio, and turbulent spectral entropy. It performs multi-feature statistical weighted fusion calculation according to preset statistical weight coefficients to complete parameter normalization and integration. At the same time, it combines the respiratory baseline statistical drift compensation amount to correct the signal deviation caused by individual respiratory baseline offset and environmental condition fluctuations. The corrected fused feature parameters are mapped to the three-dimensional mapping matrix of the lesion impedance compensation model. The airway equivalent impedance is calculated by solving the normalization solution formula of the airway equivalent impedance.

[0056] S4, the control module 9 generates a dynamic compensation command based on the calculated equivalent impedance of the airway, drives the frequency conversion drive circuit 72 in the adaptive nebulization module 7, and adjusts the vibration amplitude of the nebulizer 71 through pulse width modulation, so that the nebulizer 71 works in multi-frequency resonance mode, realizing adaptive adjustment of the nebulized airflow intensity and the particle size of the drug mist; at the same time, the control module 9 predicts the trend of breathing airflow switching based on the change of the rotation angle acceleration of the blade 52 collected by the rotation detection sensor 53, and synchronously opens and closes the inhalation one-way valve 31 and the expiration one-way valve 41 before the airflow direction reverses, thereby constructing a full-link timing pre-compensation algorithm to realize the time-division independent opening and closing of the inhalation and expiration pathways, avoiding airflow cross-flow and backflow phenomena.

[0057] S5, control module 9 performs velocity-pressure fusion analysis on the turbulent acoustic feature vector. Based on the fusion peak inflection point corresponding to the velocity-pressure fusion weight, it divides the time sequence of a single complete inhalation process and executes a dual-phase deposition strategy: during the airway opening phase, it outputs a high-velocity drug mist with a median particle size of 3.0μm~5.0μm, relying on the airflow impact effect to clear the narrow airway caused by tumor occupancy; during the deep penetration phase, it automatically switches to a low-velocity drug mist with a median particle size of 0.5μm~2.5μm, so that the drug mist can smoothly penetrate into the terminal lesion area of ​​the lung and complete targeted nebulized drug delivery.

[0058] S6, the aerosol concentration sensor 42 adopts a gated time window acquisition mechanism to collect the concentration signal during the stable exhalation period; the residual drug purification module 8 monitors the volume concentration of undeposited aerosol in the exhalation pathway 4 in real time; when the detected concentration is higher than the preset safety threshold, the control module 9 immediately increases the dynamic negative pressure inside the exhalation pathway 4, accelerates the flow rate of residual drug, and corrects the nebulization output rate and drug delivery intensity based on the residual aerosol concentration feedback signal until the exhaled aerosol concentration falls back to the safe threshold range; at the same time, the exhaled residual aerosol flows through the residual drug collector 43 to complete the interception and purification, ensuring clean exhaust gas emission, thus forming a complete closed-loop adaptive nebulization nursing process.

[0059] Example 1: This embodiment focuses on the clinical application of the lung cancer nebulization nursing device and method of the present invention in patients with lung cancer complicated by severe airway compression and stenosis. The specific actual application conditions and quantitative data are as follows: The patient was a 62-year-old male with lung cancer. He was clinically diagnosed with severe airway stenosis caused by a tumor, with an organic stenosis of 68%. His baseline respiratory rate was 22 breaths / minute, peak inspiratory flow was 0.8 m / s, peak expiratory flow was 0.6 m / s, and his respiratory rhythm was short and easily disturbed by momentary coughing. The amplitude of momentary airway pressure fluctuation during coughing was ≥1.2 kPa.

[0060] After the device is activated, the no-load baseline calibration mechanism is triggered first, guiding the patient to complete four steady, deep no-load breaths. The sensing module 6 simultaneously acquires pressure and flow rate signals over four complete respiratory cycles, with the signal acquisition ranges being 0.1–2.5 kPa for pressure and 0.1–1.0 m / s for flow rate. The control module 9 performs mean fitting on multiple sets of raw signals to generate a patient-specific pressure-flow rate baseline map, with a baseline flow rate mean of 0.75 m / s and a baseline pressure mean of 0.5 kPa.

[0061] After calibration, the nebulization function is activated, and the airflow drives the blades 52 of the one-way isolation component 5 to rotate counterclockwise, with a real-time rotational angular velocity of 16.5 rad / s. The rotation detection sensor 53 collects the blade rotation status in real time and uploads the signal. The control module 9 correspondingly opens the inspiratory one-way valve 31 and closes the expiratory one-way valve 41, realizing the independent opening and closing of the inspiratory and expiratory pathways at different times, with no obvious airflow cross-flow throughout. Subsequently, the MEMS flow sensor 32 and pressure fluctuation sensor 33 of the sensing module 6 collect the patient's respiratory physiological signals in real time. After the signals are preprocessed by moving average filtering, a fast Fourier transform is performed to generate turbulent acoustic feature vectors. The frequency resolution of this batch of testing equipment is 8 Hz, the patient's real-time airflow main frequency is 256 Hz, and the fluctuation range is ±3 Hz, which is in the 220 Hz~300 Hz severe airway pressure sensitive frequency band. The airway pressure resistance value calculated by the model is 1.8 kPa・s / L, which matches the severe airway pressure condition caused by lung cancer tumor lesions.

[0062] Control module 9 calls the built-in three-dimensional mapping matrix of the lesion impedance compensation model to match the individualized drug delivery parameters corresponding to severe pressure. The flow rate compensation coefficient is 1.0, increasing the nebulizer outlet flow rate to the upper limit of the adjustable range of 2.0 m / s, with an operational fluctuation error ≤ ±0.1 m / s. The nebulizer jet timing is coordinated with the patient's inhalation through a full-link timing pre-compensation algorithm to avoid choking caused by a mismatch between the drug mist flow rate and the spontaneous inhalation flow rate. The frequency conversion drive circuit controls the nebulizer plate 71 to switch to a high-energy multi-frequency resonant mode with an inherent resonant frequency of 1.7 MHz, and pressurizes the nebulizer cavity by 0.3 kPa to form a stable, high-speed directional drug mist jet.

[0063] The device employs a full-link timing pre-compensation algorithm to perform dual-phase deposition targeted nebulization drug delivery. Control module 9 divides the inspiratory timing using flow-pressure fusion characteristic inflection points, with airway opening and deep penetration phases lasting 0.4 s and 0.8 s, respectively. During the airway opening phase, a high-flow-rate, large-particle-size drug mist with a median particle size of 4.2 μm and a deviation of ±0.3 μm is output. This high-speed airflow impacts and clears the narrowed airways of the tumor, relieving airway spasm and opening up subsequent drug penetration channels. During the deep penetration phase, the device automatically switches to a low-flow-rate drug mist with a median particle size of 1.8 μm and a deviation of ±0.2 μm, reducing the airflow velocity to 0.8 m / s. The drug mist then gently enters the peripheral lung lesion area for deposition. Clinical testing showed a drug deposition rate of 41% in the patient's lesion area, compared to 21% for traditional constant droplet output nebulizers, representing a 20 percentage point increase in effective drug deposition, demonstrating significant advantages in targeted drug delivery.

[0064] During the exhalation phase, the drug mist concentration sensor 42 employs a gated time window acquisition mechanism to generate a real-time concentration-time change curve and identify the plateau phase. After eliminating interference from residual drug mist from the mask during the initial exhalation phase, the effective undeposited drug mist concentration was obtained as 18.5 μg / m³. 3 Based on the effective concentration feedback signal during the stable phase, control module 9 increases the negative pressure in the conventional tubing within the exhalation pathway from 0.05 kPa to 0.12 kPa, and simultaneously reduces the nebulization output rate to 1.0 ml / min to minimize ineffective drug loss. Residual exhaled drug mist flows through residual drug collector 43, undergoing three stages of purification: a hydrophobic PTFE filter, an electrostatic activated carbon adsorption layer, and a HEPA high-efficiency filter. The drug mist concentration in the exhaust air is ≤0.08 μg / m³, meeting the medical emission safety standards for antitumor nebulizer exhaust.

[0065] This clinical nebulization treatment lasted 15 minutes. The device operated stably with no airflow leakage or drug aerosol spillage. The patient's airway ventilation significantly improved, with the frequency of coughing decreasing from 9 times / 15 minutes before nebulization to 3 times / 15 minutes. In summary, this invention can accurately adapt to the pathological characteristics of patients with severe airway stenosis in lung cancer. It outperforms traditional nebulization equipment in terms of airway patency, targeted drug deposition rate, respiratory comfort, and safe exhaust emissions. All operating parameters are stable and reproducible.

[0066] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A lung cancer nebulization nursing device, characterized in that, It includes a nebulizer (1), a breathing mask (2), an inhalation passage (3), and an exhalation passage (4); the breathing mask (2) is connected to the ends of the inhalation passage (3) and the exhalation passage (4), and a one-way isolation component (5) is provided at the airway interface; the inhalation passage (3) and the exhalation passage (4) are respectively provided with an inhalation one-way valve (31) and an exhalation one-way valve (41) at the end of the breathing mask (2); The lung cancer nebulization nursing device also includes: The sensing module (6) includes a MEMS flow sensor (32) and a pressure fluctuation sensor (33) installed in the inspiratory passage (3) near the inspiratory one-way valve (31) to collect the patient's inspiratory flow rate and respiratory pressure signals, and extract the turbulent acoustic feature vector characterizing the airway pressure state through signal processing; An adaptive atomization module (7) is integrated into an atomizer (1) and includes an atomizing plate (71) and a frequency conversion drive circuit (72). The frequency conversion drive circuit (72) adjusts the vibration amplitude of the atomizing plate (71) by adjusting the duty cycle of the drive waveform, so as to synchronously switch the median particle size of the drug mist and adjust the atomization outlet flow rate. The residual drug purification module (8) is located in the exhalation passage (4) and includes a drug mist concentration sensor (42) and a residual drug trap (43) for real-time monitoring of the concentration of undeposited drug mist in exhalation and interception and purification of residual drug mist in exhalation. The control module (9) is integrated into the nebulizer (1) and electrically connected to the sensing module (6), the adaptive nebulization module (7), and the residual drug purification module (8) respectively. It is used to calculate the equivalent impedance of the airway in real time based on the turbulent acoustic feature vector and the built-in lesion impedance compensation model. It also corrects the particle size switching threshold and the nebulization outlet flow rate of the adaptive nebulization module (7) in real time according to the equivalent impedance of the airway and the concentration of undeposited drug mist, and realizes full-link time-series pre-compensation.

2. The lung cancer nebulization nursing device according to claim 1, characterized in that, The one-way isolation component (5) includes a rotating shaft (51), a blade (52), and a rotation detection sensor (53); the blade (52) is driven by airflow to rotate around the rotating shaft (51); the control module (9) predicts the switching trend of breathing airflow based on the blade rotation angular acceleration fed back by the rotation detection sensor (53), thereby constructing a full-link time-series pre-compensation algorithm, and synchronously switching the opening and closing states of the inhalation one-way valve (31) and the exhalation one-way valve (41) within a preset prediction time before the airflow direction reverses.

3. The lung cancer nebulization nursing device according to claim 1, characterized in that, The control module (9) has an unloaded reference calibration mechanism, namely: Before nebulization is started, the reference pressure-flow rate signal of the patient’s steady breathing without load is collected by the sensing module (6) and a reference acoustic spectrum template is generated by Fourier transform. During the nebulization nursing process, the control module (9) performs frequency domain differential processing on the real-time signal and the reference acoustic spectrum template to filter out non-pathological disturbances.

4. The lung cancer nebulization nursing device according to claim 1, characterized in that, The frequency conversion drive circuit (72) regulates the vibration amplitude of the atomizing plate (71), specifically as follows: The variable frequency drive circuit (72) is based on the dynamic compensation command output by the control module (9) according to the equivalent impedance of the airway and the concentration of undeposited drug mist. It adjusts the duty cycle and frequency of the drive waveform through pulse width modulation to drive the atomizing plate (71) to work in multi-frequency resonance mode. The atomization outlet velocity increases nonlinearly with the increase of the equivalent impedance of the airway, achieving nonlinear dynamic tracking compensation in the range of 0.2m / s to 2.0m / s.

5. The lung cancer nebulization nursing device according to claim 1, characterized in that, The drug mist concentration sensor (42) adopts a gated time window acquisition mechanism to acquire the concentration signal during the stable period of exhalation. When the concentration of undeposited drug mist in the exhalation is detected to be higher than the preset threshold, the control module (9) automatically increases the dynamic negative pressure in the exhalation pathway (4) and adjusts the nebulization output rate simultaneously. The residual drug collector (43) is arranged in sequence along the airflow direction with a hydrophobic microporous polytetrafluoroethylene filter, an electrostatic activated carbon adsorption layer and a HEPA high-efficiency filter element.

6. The lung cancer nebulization nursing device according to claim 1, characterized in that, The sensing module (6) performs Fourier transform processing on the collected inspiratory flow rate and respiratory pressure signals to decompose the airflow frequency domain distribution characteristics and thereby construct a turbulent acoustic feature vector. The turbulent acoustic feature vector includes the energy density distribution, frequency domain energy ratio and turbulent spectrum entropy in the 100Hz-300Hz frequency band. The frequency domain parameters are normalized and integrated by multi-feature statistical weighted fusion, and the degree of airflow turbulence in the airway is quantified by combining the turbulent spectrum entropy. When the fused feature quantity in this frequency band is higher than the preset benchmark threshold, it is determined to be a high airway resistance state caused by tumor occupancy.

7. The lung cancer nebulization nursing device according to claim 6, characterized in that, The lesion impedance compensation model has a built-in three-dimensional mapping matrix of characteristic frequency-resistance level-flow velocity compensation coefficient; combined with the airway equivalent impedance normalization solution method, the respiratory baseline statistical drift compensation amount is introduced to correct the deviation of the airway equivalent impedance calculation result; the control module (9) uses the real-time calculated turbulent acoustic characteristic vector as the input variable and maps it to the three-dimensional mapping matrix to calculate the current airway equivalent impedance value; the control module (9) further generates a dynamic compensation command for correcting the particle size switching threshold and atomization outlet flow rate of the adaptive nebulization module (7) according to the airway pressure resistance value.

8. The lung cancer nebulization nursing device according to claim 7, characterized in that, The control module (9) executes a dual-phase deposition strategy based on the turbulent acoustic feature vector and lesion impedance compensation model, specifically as follows: The control module (9) performs velocity-pressure fusion analysis on the turbulent acoustic feature vector, and divides the intake phase into the airway opening period and the deep penetration period based on the fusion peak inflection point; the control module (9) determines the current airway pressure resistance state and matches the adaptation parameters based on the turbulent acoustic feature vector: It delivers a high-flow-rate drug mist with a median particle size of 3.0 μm to 5.0 μm during the airway opening period; During the deep penetration phase, switch to a low-flow-rate aerosol with a median particle size of 0.5μm to 2.5μm.

9. A method for nebulized nursing care for lung cancer, implemented based on the lung cancer nebulized nursing device according to any one of claims 1-8, characterized in that, Includes the following steps: S1, before nebulization is started, the reference pressure-flow rate signal of the patient’s steady breathing without load is collected by the sensing module (6), and the reference acoustic spectrum template is generated by Fourier transform and stored in the control module (9); S2, during the atomization process, the sensing module (6) collects the inhalation phase pressure and flow rate signals in real time, and the control module (9) performs frequency domain differential processing on the real-time signals and the reference acoustic spectrum template to filter out non-pathological disturbances and extract the turbulent acoustic feature vectors from them. S3 extracts the energy density, frequency domain energy ratio, and turbulent spectral entropy within the turbulent acoustic feature vector. The parameters are normalized and integrated through multi-feature statistical weighted fusion. After correcting the signal deviation by combining respiratory baseline statistical drift compensation, the parameters are mapped to the three-dimensional mapping matrix of the lesion impedance compensation model to obtain the current airway equivalent impedance. S4, the control module (9) generates a dynamic compensation command based on the equivalent impedance of the airway, drives the frequency conversion drive circuit to adjust the vibration amplitude of the nebulizer through pulse width modulation, so that the nebulizer works in the multi-frequency resonance mode; at the same time, the control module (9) predicts the switching trend of breathing airflow based on the blade rotation angular acceleration, and constructs a full-link timing pre-compensation algorithm to synchronously open and close the inhalation one-way valve and the exhalation one-way valve before the airflow direction reverses. S5, the control module (9) performs velocity-pressure fusion analysis on the turbulent acoustic feature vector, divides the inhalation sequence according to the fusion peak inflection point, and executes a dual-phase deposition strategy: outputs high-velocity drug mist with a median particle size of 3.0μm-5.0μm during the airway opening period, and switches to low-velocity drug mist with a median particle size of 0.5μm-2.5μm during the deep penetration period to complete targeted atomization drug delivery; S6, the drug mist concentration sensor (42) adopts a gated time window acquisition mechanism to acquire the concentration signal during the stable period of exhalation; the residual drug purification module (8) monitors the concentration of undeposited drug mist in exhalation in real time; when the detected concentration is higher than the preset threshold, the control module (9) increases the dynamic negative pressure of the exhalation pathway and corrects the nebulization output parameters based on the feedback of the residual drug mist concentration until the exhalation drug mist concentration falls back to the safe threshold range.

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