Device and system for evaluating the cause of dyspnea based on real-time monitoring of chest and abdominal respiratory movements

Abstract

The present invention provides a device and system for evaluating the cause of dyspnea based on real-time monitoring of chest and abdominal respiratory movements, and belongs to the field of computer technology. The device includes: a respiratory index calculation module, which is used to calculate the respiratory index, the thoracic volume in a quiet state, and the tidal volume based on the chest respiratory digital signal and the abdominal respiratory digital signal; wherein the respiratory index includes: chest respiratory amplitude sequence, abdominal respiratory amplitude sequence, average inhalation time, average exhalation time, the inhalation-exhalation ratio of each breath, the respiratory cycle, and the chest-abdominal breathing ratio; a cause evaluation module, which is used to obtain the evaluation result of the cause of dyspnea according to the respiratory index, the thoracic volume in a quiet state, and the tidal volume. The present invention can evaluate the cause of dyspnea.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a device and system for evaluating the cause of dyspnea based on real-time monitoring of chest and abdominal respiratory movements. Background Art

[0002] The causes of dyspnea involve chronic airway diseases, heart diseases, neuromuscular diseases, skeletal muscle deadaptation, and psychological and mental factors. Some patients have multiple organic causes or coexistence of organic and functional causes, which poses a challenge to the accurate assessment of the cause of dyspnea. Traditional methods for assessing the cause of dyspnea are divided into non-invasive assessment methods, including lung function and cardiopulmonary exercise testing, and invasive assessment methods including invasive cardiopulmonary exercise testing. The specific description is as follows:

[0003] Lung function: The cause of lung disease is mainly determined by measuring the actual data of lung function, including lung volume measurement such as vital capacity, forced vital capacity, total lung volume and residual volume, as well as flow rate volume curve and diffusion function measurement, to evaluate the pulmonary ventilation and gas exchange function. The evaluation scope is mainly concentrated in the airway, lung tissue and diaphragm, and there is a lack of effective evaluation methods for cardiogenic dyspnea, psychogenic dyspnea and skeletal muscle deadaptation.

[0004] Cardiopulmonary exercise testing: When the cause of dyspnea is unclear or the dyspnea is out of proportion to the severity of the patient's confirmed cardiopulmonary disease, cardiopulmonary exercise testing (CPET) may be helpful. CPET can assess the load that the patient can withstand, the degree of dyspnea (such as by Borg or other scores), peak oxygen uptake, cardiac output (calculated by CO2 production and oxygen uptake), and the relationship between minute ventilation and CO2 production. Cardiopulmonary exercise testing can provide a more extensive evaluation of the cause of dyspnea, including the differentiation of cardiac, pulmonary, and psychogenic causes of dyspnea. Its disadvantages are that it must rely on large instruments and equipment, be performed in the pulmonary function room of a general hospital, and have certain requirements for the intensity of physical activity. Therefore, it is costly and not universal, and it is difficult to perform in other hospitals and community health centers.

[0005] Invasive cardiopulmonary exercise testing: CPET using pulmonary artery catheterization is also called invasive CPET or iCPET and can only be performed in specialized medical centers. The role of iCPET in the evaluation of dyspnea is not well defined. In general, it is used to evaluate exercise-induced pulmonary hypertension, exercise-induced heart failure, and preload-dependent cardiac output limitation. iCPET can help identify mitochondrial disease (eg, McArdle muscle phosphorylase deficiency, isolated mitochondrial myopathy) based on decreased maximal oxygen uptake (VO2 max), decreased peripheral oxygen extraction (increased mixed venous oxygen content), and increased blood lactate after exercise.

[0006] Due to the limitations of the above traditional evaluation methods, respiratory monitoring using wearable devices has become a major research direction in recent years.

[0007] Chinese patent application CN113057622A discloses a wearable device for intelligently monitoring breathing, such as Figure 1 and Figure 2 As shown, it includes a main body made of elastic material suitable for being worn on the body, a plurality of yarn-shaped stretch sensors, a plurality of stretchable wires, a circuit board and a wireless communication module. Both ends of each stretch sensor are connected to the circuit board through a stretchable wire; the wireless communication module is connected to the circuit board. At least two ends of each stretch sensor are fixed on the main body, and a plurality of stretch sensors are arranged at different positions of the main body to correspond to different respiratory monitoring parts of the body. Among them, when the main body is not deformed, the stretch sensor is in a normal stretching state without deformation. The stretch sensor installed on the wearable device can monitor the human body's respiratory state in real time and intelligently, and can accurately measure the human body's respiratory frequency, amplitude, respiratory difference and respiratory pause time. The device is simple, practical and easy to carry, overcoming the limitation that the respiratory state can only be monitored in the hospital, and is suitable for home and outdoor scenes. The user's current respiratory condition or respiratory stage is judged by the real-time generated resistance change curve. For example: in the normal breathing stage, the curve is flat and the waveform is stable; in the deep breathing stage, the peak is higher and the breathing cycle is longer; in the coughing stage, due to the rapid breathing during coughing, the peaks appear sharp and dense; in the sneezing stage, it appears as a single sharp trough, and there is a weak breathing stage after the single sharp trough, which appears as a wide and continuously decreasing trough.

[0008] Chinese patent application CN111671426A provides a human respiratory status monitoring system and method based on flexible sensing and deep learning, such as Figure 3As shown, the human respiratory state monitoring system includes: a flexible tension sensor, used to convert human respiratory data into analog signal output; a microcontroller, connected to the flexible tension sensor through an analog-to-digital converter, used to receive the analog signal output by the flexible tension sensor and convert it into a digital signal, and output it through a wireless transmission module; a terminal, connected to the microcontroller through a wireless transmission module, used to receive the digital signal output by the microcontroller and output it; a cloud server, used to receive the digital signal output by the terminal and use a deep learning network model to monitor and analyze the human respiratory state.

[0009] Chinese patent application CN210019351U discloses a respiratory sensor device and a wearable device, such as Figure 4 As shown, the breathing sensor device includes a retractable resistor component and a processing module electrically connected to the resistor component. The resistance value of the resistor component changes with the change of the length of the resistor component. When the breathing sensor device is worn on the human body, the resistor component can be retracted and retracted with the breathing of the human body. The processing module is used to detect and process the signal generated when the resistor component is retracted and retracted. The breathing sensor device disclosed in the utility model monitors human breathing in a resistive sensing manner. The breathing sensor device is less affected by factors such as humidity, climate, and sweat when collecting signals, and the monitoring result is more accurate. In addition, the breathing sensor device collects relevant information about human breathing by being set at a position corresponding to the human chest. Compared with existing devices that must be worn on the human face to collect human breathing information, it is more convenient to use in daily life or during exercise, and has high wearability.

[0010] Chinese patent application CN109730679A provides a wearable respiratory monitoring device and a respiratory measurement method, which relates to the field of smart wearable devices. Figure 5 As shown, the device includes a close-fitting garment body, a breathing sensor and a signal processor. The breathing sensor is fixed to the part of the garment body corresponding to the chest cavity, and includes a strain sensor and electrode materials fixed at both ends of the strain sensor; wherein the strain sensor includes a conductive inner core and an elastic packaging layer. The signal processor is fixed to the garment body and is used to convert the signal output by the breathing sensor into visual data. The device has a high degree of fit with the human body, a simple structure and high sensitivity. A breathing measurement method is provided, which is simple and effective in monitoring, can monitor and obtain the breathing frequency and amplitude information of the subject in real time, and set the normal breathing amplitude, and judge the human body state according to the number of normal breathing, deep breathing and shallow breathing in a unit time.

[0011] Chinese patent application CN108451532A discloses a method and system for acquiring respiratory information, such as Figure 6As shown, it collects pressure signals corresponding to multiple different body parts of the target human body according to a preset pressure collection method; performs signal processing on the collected pressure signals, and analyzes to obtain the breathing signals corresponding to the target human body; obtains the breathing intensity and breathing frequency corresponding to the target human body according to the obtained breathing signals; has the beneficial effect of obtaining more accurate breathing information by collecting pressure signals from multiple body surfaces of the human body, improves the accuracy and reliability of obtaining breathing information, and further makes the acquisition of breathing information repeatable; adopts a technical solution of simultaneously collecting surface pressure information of the target human body when breathing at multiple points, and performing correlation analysis in conjunction with human anatomy, which can further obtain individualized breathing information such as the breathing pattern of the target human body, organ muscle participation, etc.

[0012] Chinese patent application CN208114591U involves the field of human physiological monitoring and sports health technology, and especially innovates a smart underwear with real-time monitoring function of human electrocardiogram and respiratory signals, which is composed of wearable underwear and smart modules. Figure 7 As shown in the figure, the wearable underwear and the smart module adopt a detachable structure, which is specifically composed of the underwear body, fabric electrodes, metal snaps, and smart modules. The wearable underwear is embedded with three fabric electrodes, which are respectively located on the left chest, right chest, middle of the chest or left chest, right chest, and below the left chest; the wearable underwear is made of a mixture of spandex and nylon and has the characteristics of breathability, sweat absorption, and high elasticity; the smart module is composed of metal snaps, processors, electrocardiorespiratory acquisition modules, wireless transmission modules, storage devices, and power modules. The wearable underwear attaches the embedded fabric electrodes to the chest skin to extract the weak electrical signals of the human epidermis, and transmits the electrical signals to the smart module through three metal snaps; the smart module collects, amplifies, filters, analyzes and processes the signals, and then performs synchronous storage and wireless transmission. The handheld terminal synchronously receives the physiological signals sent by one or more smart modules wirelessly, and performs centralized dynamic display for multiple people, and performs real-time and accurate analysis and alarm prompts, such as heart rate, breathing, etc., so that fitness personnel and coaches can monitor the exercise data in real time, prevent high load and unexpected situations, and provide a scientific training method. The smart underwear of this utility model is designed in full compliance with the principles of ergonomics, achieving accurate monitoring data and comfortable wearing, greatly improving the efficiency of daily training, and providing effective support for big data analysis of physiological signs in the field of sports health.

[0013] Chinese patent application CN105769200A relates to a wearable human respiratory measurement system and measurement method, including: a power module for providing energy for the entire system; a flow signal acquisition module for monitoring human respiratory airflow and collecting flow change signals caused by airflow; a signal conditioning module for processing the flow change signal to obtain a respiratory signal; a Bluetooth transmission module for wirelessly transmitting the respiratory signal; a respiratory signal analysis module for performing data analysis on the respiratory signal to obtain lung capacity parameters such as respiratory frequency and respiratory flow. The system can accurately and reliably monitor the respiratory frequency and flow in real time by measuring human respiration; the module is compact, small, wearable, does not cause discomfort to the human body, is low in cost, and has a wide range of applications.

[0014] However, the existing techniques for assessing the etiology of dyspnea, as shown in Table 1 , have the following disadvantages.

[0015]

[0016] Table 1 Summary of the invention

[0017] In view of the shortcomings of the above-mentioned dyspnea cause assessment technology, the present invention discloses a dyspnea cause assessment device and system based on real-time monitoring of chest and abdominal respiratory movements, which can assess the cause of dyspnea.

[0018] In order to achieve the above-mentioned object of the invention, the technical solution of the present invention includes the following contents.

[0019] A device for evaluating the cause of dyspnea based on real-time monitoring of chest and abdominal respiratory movements, the device comprising:

[0020] A breathing index calculation module, used to calculate breathing indexes, thoracic volume in a quiet state and tidal volume based on the chest breathing digital signal and the abdominal breathing digital signal; wherein the breathing indexes include: chest breathing amplitude sequence, abdominal breathing amplitude sequence, average inspiration time, average exhalation time, inspiration-exhalation ratio of each breath, breathing cycle and chest-abdominal breathing ratio;

[0021] The cause assessment module is used to obtain the assessment result of the cause of dyspnea based on respiratory indicators, chest volume in a quiet state and tidal volume.

[0022] Furthermore, the breathing index calculation module is also used for:

[0023] For all moments T i Chest breathing digital signal Abdominal breathing digital signal Perform traversal sampling to obtain the peak moment of the chest breathing signal Abdominal breathing signal peak time Chest breathing signal trough moment and the trough moment of the abdominal breathing signal

[0024] Peak moment of chest breathing signal by time and chest breathing signal trough moment Sorting is performed to obtain a peak-trough time sequence of the chest respiratory signal, and according to the chest respiratory amplitude corresponding to the peak-trough time sequence of the chest respiratory signal, a chest respiratory amplitude sequence is obtained;

[0025] Peak moment of abdominal breathing signal by time and the trough moment of the abdominal breathing signal Sorting is performed to obtain a peak-trough time sequence of the abdominal respiratory signal, and according to the abdominal respiratory amplitude corresponding to the peak-trough time sequence of the abdominal respiratory signal, an abdominal respiratory amplitude sequence is obtained;

[0026] Based on the peak and trough time sequence of the chest respiratory signal and the peak and trough time sequence of the abdominal respiratory signal, calculate the inhalation time of the jth breath Exhalation time and I / O ratio

[0027] Based on the inhalation time of each breath and exhalation time Calculate the mean inspiratory time T in and the average exhalation time T ex ;

[0028] Based on the average inspiratory time T in and the average exhalation time T ex , and obtain the respiratory period T c ;

[0029] According to the chest breathing amplitude sequence, the average chest breathing amplitude A is obtained. th ;

[0030] According to the abdominal breathing amplitude sequence, the average abdominal breathing amplitude A is obtained. ab ;

[0031] Based on the average chest breathing amplitude A th and the average breathing amplitude of the abdomen A ab , get the proportion of chest and abdomen breathing R ta ;

[0032] Based on the average chest breathing amplitude A th , and the thoracic volume V at rest is obtained th ;

[0033] Based on the average abdominal breathing amplitude A ab , and the abdominal volume V at rest is obtained ab ;

[0034] Based on the thoracic volume V th and abdominal volume V ab , and obtain the tidal volume VT.

[0035] Further, the evaluation results of the causes of dyspnea include: chronic airway disease;

[0036] The etiology assessment module is also used to:

[0037] Based on the chest breathing amplitude sequence and the abdominal breathing amplitude sequence, the patient's breathing amplitude state is obtained; wherein the breathing amplitude state includes: the breathing amplitude is stable, the breathing amplitude is gradually decreasing, or the breathing amplitude is gradually increasing;

[0038] According to the proportion of chest and abdominal breathing, the patient's breathing pattern is obtained; wherein the breathing pattern includes: abdominal breathing, mixed breathing or chest breathing;

[0039] Obtaining a determination index for chronic airway disease; wherein the determination index for chronic airway disease includes:

[0040] The inhalation-exhalation ratio is less than the set value;

[0041] and,

[0042] When the patient's ventilation demand increases, if there is dynamic hyperinflation of the lungs, the respiratory amplitude gradually decreases;

[0043] and,

[0044] The breathing pattern is chest breathing;

[0045] If the patient's inspiratory-expiratory ratio, respiratory amplitude status and respiratory pattern meet the judgment indicators of chronic airway disease, the patient is judged to be a possible chronic airway disease patient.

[0046] Furthermore, the determination index of dynamic pulmonary hyperinflation includes: during exercise, the inspiration-expiration ratio of each breath is less than 1, and the chest volume increases by 30% or more compared with the chest volume in a resting state.

[0047] Further, the evaluation results of the causes of dyspnea include: interstitial lung disease;

[0048] The etiology assessment module is also used to:

[0049] Based on the chest breathing amplitude sequence and the abdominal breathing amplitude sequence, the patient's breathing amplitude state is obtained; wherein the breathing amplitude state includes: the breathing amplitude is stable, the breathing amplitude is gradually decreasing, or the breathing amplitude is gradually increasing;

[0050] Obtained determination indicators; wherein the determination indicators of interstitial lung disease include:

[0051] When the patient's ventilation demand increases, the respiratory rate is greater than the set value;

[0052] and,

[0053] When the patient's ventilation demand increases, the inspiration-expiration ratio is within a reasonable range;

[0054] and,

[0055] As the patient's ventilatory needs increase, the respiratory amplitude remains stable;

[0056] If the patient's respiratory rate, inspiratory-expiratory ratio and respiratory amplitude status meet the determination indicators of interstitial lung disease, the patient is determined to be a possible interstitial lung disease patient.

[0057] Further, the evaluation results of the causes of dyspnea include: heart disease;

[0058] The etiology assessment module is also used to:

[0059] Based on the chest breathing amplitude sequence and the abdominal breathing amplitude sequence, the patient's breathing amplitude state is obtained; wherein the breathing amplitude state includes: the breathing amplitude is stable, the breathing amplitude is gradually decreasing, or the breathing amplitude is gradually increasing;

[0060] Obtaining a determination index for heart disease; wherein the determination index for heart disease includes:

[0061] As the patient's ventilatory needs increase, the respiratory amplitude remains stable;

[0062] and,

[0063] Lung ventilation is less than the set value;

[0064] If the patient's respiratory amplitude state and lung ventilation volume meet the determination indicators of the heart disease, then the patient is determined to be a possible heart disease patient.

[0065] Furthermore, the evaluation results of the causes of dyspnea include: mental and psychological diseases;

[0066] The etiology assessment module is also used to:

[0067] According to the proportion of chest and abdominal breathing, the patient's breathing pattern is obtained; wherein the breathing pattern includes: abdominal breathing, mixed breathing or chest breathing;

[0068] Obtaining the determination index of mental illness; wherein the determination index of mental and psychological illness includes:

[0069] The breathing pattern is chest breathing;

[0070] and,

[0071] Sighing breathing occurs at a set frequency;

[0072] If the patient's breathing pattern is chest breathing, and sigh breathing is determined to occur based on the tidal volume, the patient is determined to be a patient with a mental and psychological disease.

[0073] Further, the evaluation results of the cause of dyspnea include: skeletal muscle deadaptation;

[0074] The etiology assessment module is also used to:

[0075] Obtaining the patient's respiratory rate according to the respiratory cycle;

[0076] According to the proportion of chest and abdominal breathing, the patient's breathing pattern is obtained; wherein the breathing pattern includes: abdominal breathing, mixed breathing or chest breathing;

[0077] Obtaining a skeletal muscle deadaptation determination index; wherein the skeletal muscle deadaptation determination index includes: when the lung function parameter in the exercise state is within a set range, and the changes in the breathing pattern and the breathing amplitude are within a reasonable range;

[0078] If the patient's breathing pattern and breathing indexes during exercise meet the judgment index of skeletal muscle deadaptation and the patient has reduced activity tolerance, the patient is determined to be a skeletal muscle deadaptation patient.

[0079] A dyspnea etiology assessment system based on real-time monitoring of chest and abdominal respiratory movements, the system comprising:

[0080] A first flexible stretchable electronic sensor for collecting chest breathing simulation signals;

[0081] a second flexible stretchable electronic sensor for collecting abdominal breathing simulation signals;

[0082] An analog-to-digital converter, used for converting a chest breathing analog signal and an abdominal breathing analog signal into a chest breathing digital signal and an abdominal breathing digital signal respectively;

[0083] A device for evaluating the cause of dyspnea is used to calculate respiratory indices, thoracic volume in a quiet state, and tidal volume based on chest respiratory digital signals and abdominal respiratory digital signals; and obtain an evaluation result of the cause of dyspnea based on the respiratory indices, thoracic volume in a quiet state, and tidal volume; wherein the respiratory indices include: chest respiratory amplitude sequence, abdominal respiratory amplitude sequence, average inhalation time, average exhalation time, inhalation-exhalation ratio of each breath, respiratory cycle, and thoracic-abdominal breathing ratio.

[0084] Furthermore, the system also includes a wearable device; wherein the first flexible stretchable electronic sensor and the second flexible stretchable electronic sensor are respectively fixed to the wearable device, and correspond to the chest breathing detection site and the abdominal breathing detection site respectively; the first flexible stretchable electronic sensor, the second flexible stretchable electronic sensor, the analog-to-digital converter and the dyspnea cause assessment device are electrically connected.

[0085] Compared with the prior art, the present invention has at least the following technical advantages.

[0086] 1. The present invention does not require deliberate cooperation from the patient and is less affected by subjective factors.

[0087] 2. Not restricted by testing sites and personnel.

[0088] 3. It can be repeated, easy to operate and popularize.

[0089] 4. Pathophysiological analysis can be performed on the monitored parameters.

[0090] 5. Can guide personalized treatment and rehabilitation. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 A schematic diagram of the front structure of a smart tights for intelligently monitoring breathing disclosed in the prior art.

[0092] Figure 2 A graph showing the change in resistance over time of five stretch sensors arranged at different test positions disclosed in the prior art.

[0093] Figure 3 A human respiratory status monitoring system and method based on flexible sensing and deep learning disclosed in the prior art.

[0094] Figure 4 A prior art discloses a respiratory sensing device based on a resistor component.

[0095] Figure 5 A wearable garment and a breathing measurement method disclosed in the prior art.

[0096] Figure 6 A flow chart of pressure signal processing disclosed in the prior art.

[0097] Figure 7 A smart underwear with real-time monitoring function of electrocardiogram and respiratory signals disclosed in the prior art.

[0098] Figure 8 The present invention discloses a flow chart of a method for evaluating the cause of dyspnea based on real-time monitoring of thoracic and abdominal respiratory movements.

[0099] Fig. 9Schematic diagram of the chest breathing signal and its peaks and troughs. DETAILED DESCRIPTION

[0100] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below through specific implementations and in conjunction with the accompanying drawings.

[0101] The method for evaluating the cause of dyspnea based on real-time monitoring of thoracic and abdominal respiratory movements of the present invention does not require deliberate cooperation from patients, is less affected by subjective factors, is not limited by test sites and personnel, can be repeated, is easy to operate, and is easy to popularize. It can perform pathophysiological analysis on monitoring parameters and can guide personalized treatment and rehabilitation.

[0102] Specifically, if Figure 8 As shown, the present invention mainly includes the following steps.

[0103] Step A: Flexible stretchable electronic sensors are set on the chest and abdomen to synchronously collect chest and abdominal respiratory signals.

[0104] In one embodiment, the flexible stretchable electronic sensor can be a resistive, capacitive, piezomagnetic, inductive sensor, etc., and its flexible substrate has good flexibility and ductility, and good skin adhesion. The sensor can be fixed to the chest and abdomen in a wearable form such as an elastic bandage or a tights, and a stretch sensor is set on the chest and abdomen to monitor the breathing of the chest and abdomen. The stretchable length of the stretch sensor needs to exceed the maximum amplitude of the chest and abdomen fluctuation during breathing (such as greater than 10 cm).

[0105] Step B: The original signal of the sensor is synchronously converted into a digital signal through a dual-channel analog-to-digital converter.

[0106] In one embodiment, the chest and abdomen flexible electronic sensor is connected to a dual-channel analog-to-digital converter via a USB data cable. The analog-to-digital converter can be fixed on an elastic strap in the form of Velcro. The analog-to-digital converter includes two input channels, which can simultaneously receive chest and abdomen sensor data, and synchronously convert chest and abdomen sensor signals into digital signals. The digital signals are transmitted to the computer via a USB data cable or wireless transmission such as Bluetooth. The data is sampled at a frequency f to obtain a time-synchronized chest and abdomen respiratory signal Where n is the total number of sampling points, and when the total sampling time is t, n=t×f. is time T i Corresponding chest breathing amplitude and abdominal breathing amplitude

[0107] Step C: Band-pass filter the digital signal to remove low-frequency and high-frequency noise to obtain a smooth breathing signal.

[0108] In one embodiment, the respiratory signal is in the form of a curve of the amplitude of the chest and abdomen changing over time, which can be visualized online in real time through data visualization tools such as MATLAB, and the data can be stored and viewed in the form of numerical values ​​or images.

[0109] Step D: Calculate relevant respiratory indicators such as inspiration and expiration time, inspiration-expiration ratio, respiratory cycle, chest-abdominal breathing ratio, etc. through the respiratory signal data, and estimate the thoracic volume and tidal volume.

[0110] In one embodiment, a specific method for calculating the breathing index includes the following contents.

[0111] a) Find the peaks and troughs of the chest / abdomen respiratory signal: traverse the sampled chest / abdomen respiratory signal data Calculate the peak time of chest breathing signal Abdominal breathing signal peak time Chest breathing signal trough moment Abdominal breathing signal trough moment

[0112] i. Peak moment of chest breathing signal The moment when the following conditions are met:

[0113]

[0114]

[0115] in is the sampling point i th / time The chest breathing amplitude, is the sampling point p th / time chest breathing amplitude.

[0116] ii. Abdominal breathing signal peak time The moment when the following conditions are met:

[0117]

[0118]

[0119] in is the sampling point i ab / time Abdominal breathing amplitude, is the sampling point p ab / time Abdominal breathing amplitude.

[0120] iii. Chest breathing signal trough moment The moment when the following conditions are met:

[0121]

[0122]

[0123] in is the sampling point i th / time The chest breathing amplitude, is the sampling point v th / time chest breathing amplitude.

[0124] iv. Abdominal breathing signal trough moment The moment when the following conditions are met:

[0125]

[0126]

[0127] in is the sampling point i ab / time Abdominal breathing amplitude, is the sampling point v ab / time Abdominal breathing amplitude.

[0128] b) The peaks and troughs of the respiratory signal appear alternately. Number the pairs of troughs and peaks (the trough and the next peak), such as Fig. 9 As shown, assuming that there are s pairs of troughs and peaks in the collected respiratory signal, the peak and trough moment sequence of the chest respiratory signal is obtained by sorting them in time:

[0129]

[0130] According to the chest breathing amplitude corresponding to the peak and trough time sequence of the chest breathing signal, a chest breathing amplitude sequence can be obtained.

[0131] Similarly, the peak and trough moment sequence of the abdominal breathing signal is obtained by time sorting:

[0132]

[0133] Afterwards, according to the abdominal breathing amplitudes corresponding to the peak and trough time sequence of the abdominal breathing signal, an abdominal breathing amplitude sequence can be obtained.

[0134] c) Calculate the inspiratory time of the jth breath Exhalation time and I / O ratio

[0135]

[0136]

[0137]

[0138] d) Calculate the time difference between all peaks and adjacent troughs, and take the average value as the inspiratory time T in and exhalation time T ex Estimates:

[0139]

[0140]

[0141] e) Estimation of respiratory cycle:

[0142] T c =T in +T ex

[0143] f) Estimate the average breathing amplitude of the chest:

[0144]

[0145] in, Indicates peak time The corresponding chest breathing amplitude, Indicates the trough moment The corresponding chest breathing amplitude.

[0146] g) Estimate the average abdominal breathing amplitude:

[0147]

[0148] in, Indicates peak time The corresponding abdominal breathing amplitude, Indicates peak time The corresponding abdominal breathing amplitude.

[0149] h) Estimate the proportion of thoracic and abdominal breathing:

[0150]

[0151] When R ta >1, chest breathing is dominant, R ta <1, abdominal breathing is dominant, based on which the user's breathing pattern can be judged: R ta When ≥1.1, it is chest breathing, R ta≤0.9 is abdominal breathing, 0.9 <R ta When <1.1, it is mixed breathing.

[0152] i) Estimate the thoracic volume. For a single individual, at time T i Thoracic volume Proportional to the current chest breathing amplitude

[0153]

[0154] Where k greater than 0 is a constant. The thoracic volume V at rest th According to the average breathing amplitude of the chest during quiet breathing A th To conduct an assessment:

[0155] V th = k × A th

[0156] j) Estimation of tidal volume VT:

[0157] VT=V th +V ab

[0158] V ab = k × A ab

[0159] Step E. Evaluate the cause of dyspnea.

[0160] In one embodiment, the cause of dyspnea is assessed by monitoring the form, amplitude, deformation of chest and abdominal respiratory movements, as well as dynamic changes during the inhalation and exhalation phases, combined with the patient's perception of changes in dyspnea, to evaluate the cause of dyspnea.

[0161] a) Dyspnea caused by chronic airway diseases: Because of airway obstruction, the expiratory flow rate is limited, which prolongs the expiratory time, so the I / E ratio is less than 1. When the ventilation demand increases, the expiratory force increases to overcome the increased airway resistance, which increases the intrathoracic pressure, aggravates the airflow obstruction, and prolongs the breathing time. As a result, some patients still have some gas in the lungs at the end of exhalation that cannot be completely exhaled as in the resting state, resulting in gas retention. As the exercise time increases, more and more gas is retained in the lungs, that is, "dynamic hyperinflation of the lungs" occurs. At this time, the main feature of the respiratory movement is that the increase in respiratory rate is relatively limited, and as the gas continues to be retained, the lung volume at the end of exhalation gradually increases, resulting in a gradual increase in the chest volume after exercise and a gradual decrease in tidal volume, so the respiratory amplitude gradually decreases. If this situation does not occur, the respiratory amplitude will remain basically unchanged for a certain period of time, and the respiratory movement is characterized by a decrease in the I / E ratio.

[0162] In addition, chronic airway diseases increase intrathoracic pressure during exhalation, affecting the normal movement of the diaphragm. At this time, respiratory movement can be enhanced by contraction of the intercostal muscles, and changes in breathing patterns may occur (gradually changing from abdominal breathing to chest breathing). This device can observe and record the deformation of the increased thoracic basal volume and the gradual decrease in tidal volume that occur with exercise by performing real-time quantitative monitoring of the amplitude of respiratory movement and the deformation of the thorax during exercise. These conditions can be gradually improved after stopping exercise and performing pursed lip breathing.

[0163] Based on the above characteristics, the mechanism of dyspnea in patients with chronic airway diseases can be judged more accurately, thereby laying the foundation for formulating reasonable exercise plans for pulmonary rehabilitation.

[0164] b) Dyspnea caused by restrictive lung disease: Represented by interstitial lung disease, the most common type of restrictive lung disease, the main mechanisms of dyspnea caused by interstitial lung disease are restrictive ventilation dysfunction and diffusion dysfunction. The former is the main influencing factor of respiratory movement changes, that is, when restrictive ventilation dysfunction occurs, the lung volume (including total lung volume, vital capacity, etc.) is reduced, and lung compliance is reduced, but because there is no airway obstruction, the patient's respiratory airflow rate is not significantly affected. When the ventilation demand increases, subject to the limitation of increased respiratory amplitude, the patient will have shallow and rapid breathing, that is, the increase in respiratory amplitude is relatively small, but the respiratory frequency is significantly increased, thereby increasing lung ventilation. At this time, the inspiration-expiration ratio is not significantly changed compared to the resting state. Since the air volume in the lungs remains relatively stable at the end of exhalation, the patient's respiratory amplitude remains stable for a certain period of time.

[0165] c) Dyspnea caused by heart disease: The situation is complicated, and the main mechanism is pulmonary congestion or pulmonary edema (caused by increased pulmonary venous pressure) caused by left heart failure and reduced cardiac output. Pulmonary congestion can cause a decrease in lung volume and impaired alveolar diffusion function, which is similar to the characteristics of interstitial lung disease. When the patient's ventilation needs increase, the body also increases ventilation through shallow and rapid breathing, and the respiratory amplitude is relatively stable during exercise. Unlike interstitial lung disease, in which the respiratory mechanics of the lungs remain relatively stable, when patients with heart disease experience dyspnea, it is often because the heart function cannot be further improved due to the increase in oxygen consumption. On the contrary, the decline in heart function will lead to further deterioration of lung function (worsening pulmonary congestion or pulmonary edema), which makes it more likely that the patient will experience a decrease in lung ventilation over time.

[0166] d) Dyspnea caused by mental illness: mainly occurs in patients with anxiety or depression. These patients have abnormal breathing control and mainly chest breathing at rest. Although the patient's lung function is normal, compared with normal people, the ventilation efficiency of chest breathing is significantly lower than that of abdominal breathing, and the tidal volume is reduced. This is the main reason why many patients with this disease feel that they "cannot breathe to the bottom". Because of the decrease in tidal volume, the retention of gas in the lungs gradually increases. After a certain degree, the patient will have a large tidal volume breathing (i.e. "sighing breathing", chest deformation due to the significant increase in tidal volume) with a tidal volume of 2-3 times the normal value due to the significant increase in tidal volume. This process will be repeated in the future, and its frequency may increase with the severity of the disease. The above manifestations cannot be measured through routine pulmonary function tests, and the patient's subjective feelings may not be noticed by the doctor during the actual diagnosis and treatment process due to the lack of support from objective examination results, resulting in misdiagnosis of the disease. This device can be used to monitor the patient's respiratory dynamics for a long time (up to 24 hours), record the changes in respiratory movement forms at rest and after activity, and compare them with the patient's symptoms of dyspnea. It can provide objective indicators with important reference value for the diagnosis of such patients, including the breathing form of mainly chest breathing associated with dyspnea and sighing breathing of a certain frequency.

[0167] e) Skeletal muscle deadaptation: It is an independent cause of exertional dyspnea, which is independent of cardiopulmonary disease and has a core mechanism of reduced skeletal muscle oxygen uptake capacity. It is also an important combined cause of dyspnea in chronic cardiopulmonary disease. It is mainly manifested in lower limb muscle dysfunction, and there are rarely abnormal respiratory rate or breathing patterns. This device dynamically tracks the changes in basic lung function parameters of patients with dyspnea, combined with observations of changes in respiratory movement patterns and amplitudes during exercise, to provide objective indicators for reference in assessing whether there is skeletal muscle deadaptation (basic lung function is relatively stable, and the breathing pattern does not change much during activity, but there is a significant decrease in activity tolerance), thereby providing an important basis for the rational formulation of respiratory rehabilitation plans.

[0168] For the evaluation of dynamic hyperinflation of the lungs, the commonly used pulmonary function determination index is: at any time point during exercise, the deep inspiration volume is reduced by 150mL or 4.5% compared with the resting state. When the ratio of tidal volume to deep inspiration volume reaches 70%, the patient may experience obvious dyspnea. Therefore, the determination index of dynamic hyperinflation of the lungs by this device is: during exercise, the inspiration-expiration ratio is less than 1, and the chest volume increases by 30% or more compared with the resting state.

[0169] In summary, firstly, the present invention can measure the lung volume in real time, judge the breathing pattern, and analyze the cause of dyspnea through real-time monitoring of the respiratory signal; secondly, the etiology analysis of dyspnea of ​​the present invention is based on respiratory mechanics, which is closer to the pathological and physiological state of the disease; finally, by monitoring the respiratory parameters and breathing patterns, the present invention can also guide personalized treatment and rehabilitation.

[0170] The above embodiments are provided only for the purpose of describing the present invention, and are not intended to limit the scope of the present invention. The scope of the present invention is defined by the appended claims. Various equivalent substitutions and modifications made without departing from the spirit and principles of the present invention should all be included within the scope of the present invention.

Claims

1. A device for evaluating the cause of dyspnea based on real-time monitoring of chest and abdominal respiratory movements, characterized in that: The device comprises: A breathing index calculation module, used to calculate the breathing index and the thoracic volume in a quiet state based on the chest breathing digital signal and the abdominal breathing digital signal; wherein the breathing index includes: a chest breathing amplitude sequence, an abdominal breathing amplitude sequence, an inhalation-exhalation ratio of each breath, and a chest-abdominal breathing ratio; For all moments T i Chest breathing digital signal Abdominal breathing digital signal Perform traversal sampling to obtain the peak moment of the chest breathing signal Abdominal breathing signal peak time Chest breathing signal trough moment and the trough moment of the abdominal breathing signal Peak moment of chest breathing signal by time and chest breathing signal trough moment Sorting is performed to obtain a peak-trough time sequence of the chest respiratory signal, and according to the chest respiratory amplitude corresponding to the peak-trough time sequence of the chest respiratory signal, a chest respiratory amplitude sequence is obtained; Peak moment of abdominal breathing signal by time and the trough moment of the abdominal breathing signal Sorting is performed to obtain a peak-trough time sequence of the abdominal respiratory signal, and according to the abdominal respiratory amplitude corresponding to the peak-trough time sequence of the abdominal respiratory signal, an abdominal respiratory amplitude sequence is obtained; Based on the peak and trough time sequence of the chest respiratory signal and the peak and trough time sequence of the abdominal respiratory signal, calculate the inhalation time of the jth breath Exhalation time and I / O ratio According to the chest breathing amplitude sequence, the average chest breathing amplitude A is obtained. th ; According to the abdominal breathing amplitude sequence, the average abdominal breathing amplitude A is obtained. ab ; Based on the average chest breathing amplitude A th and the average respiratory rate of the abdomen A ab , we get the proportion of chest and abdomen breathing R ta ; Based on the average chest breathing amplitude A th , and the thoracic volume V at rest is obtained th ; The cause assessment module is used to obtain the assessment result of the cause of dyspnea according to the respiratory index and the chest volume in a quiet state; wherein the assessment result of the cause of dyspnea includes: chronic airway disease; The etiology assessment module is also used to: Based on the chest breathing amplitude sequence and the abdominal breathing amplitude sequence, the patient's breathing amplitude state is obtained; wherein the breathing amplitude state includes: the breathing amplitude is stable, the breathing amplitude is gradually decreasing, or the breathing amplitude is gradually increasing; According to the proportion of chest and abdominal breathing, the patient's breathing pattern is obtained; wherein the breathing pattern includes: abdominal breathing, mixed breathing or chest breathing; Obtaining a determination index for chronic airway disease; wherein the determination index for chronic airway disease includes: The inhalation-exhalation ratio is less than the set value; and, When the patient's ventilation demand increases, if there is dynamic hyperinflation of the lungs, the respiratory amplitude gradually decreases; and, The breathing pattern is chest breathing; If the patient's inspiratory-expiratory ratio, respiratory amplitude status and respiratory pattern meet the judgment indicators of chronic airway disease, the patient is judged to be a possible chronic airway disease patient.

2. The device for evaluating the cause of dyspnea according to claim 1, characterized in that: The determination index of dynamic lung hyperinflation includes: during exercise, the inspiration-expiration ratio of each breath is less than 1, and the chest volume increases by 30% or more compared with the chest volume in a quiet state.

3. A dyspnea etiology assessment system based on real-time monitoring of chest and abdominal respiratory movements, characterized in that: The system comprises: A first flexible stretchable electronic sensor for collecting chest breathing simulation signals; a second flexible stretchable electronic sensor for collecting abdominal breathing simulation signals; An analog-to-digital converter, used for converting a chest breathing analog signal and an abdominal breathing analog signal into a chest breathing digital signal and an abdominal breathing digital signal respectively; The device for evaluating the cause of dyspnea is used to calculate the respiratory index and the thoracic volume in a quiet state based on the chest respiratory digital signal and the abdominal respiratory digital signal; according to the respiratory index and the thoracic volume in a quiet state, the evaluation result of the cause of dyspnea is obtained; wherein the respiratory index includes: chest respiratory amplitude sequence, abdominal respiratory amplitude sequence, inspiration-expiration ratio of each breath and thoracic-abdominal breathing ratio; wherein, For all moments T i Chest breathing digital signal Abdominal breathing digital signal Perform traversal sampling to obtain the peak moment of the chest breathing signal Abdominal breathing signal peak time Chest breathing signal trough moment and the trough moment of the abdominal breathing signal Peak moment of chest breathing signal by time and chest breathing signal trough moment Sorting is performed to obtain a peak-trough time sequence of the chest respiratory signal, and according to the chest respiratory amplitude corresponding to the peak-trough time sequence of the chest respiratory signal, a chest respiratory amplitude sequence is obtained; Peak moment of abdominal breathing signal by time and the trough moment of the abdominal breathing signal Sorting is performed to obtain a peak-trough time sequence of the abdominal respiratory signal, and according to the abdominal respiratory amplitude corresponding to the peak-trough time sequence of the abdominal respiratory signal, an abdominal respiratory amplitude sequence is obtained; Based on the peak and trough time sequence of the chest respiratory signal and the peak and trough time sequence of the abdominal respiratory signal, calculate the inhalation time of the jth breath Exhalation time and I / O ratio According to the chest breathing amplitude sequence, the average chest breathing amplitude A is obtained. th ; According to the abdominal breathing amplitude sequence, the average abdominal breathing amplitude A is obtained. ab ; Based on the average chest breathing amplitude A th and the average respiratory rate of the abdomen A ab , we get the proportion of chest and abdomen breathing R ta ; Based on the average chest breathing amplitude A th , and the thoracic volume V at rest is obtained th ; The assessment results of the causes of dyspnea include: chronic airway disease; The evaluation result of the cause of dyspnea obtained based on the respiratory index and the chest volume in a quiet state includes: Based on the chest breathing amplitude sequence and the abdominal breathing amplitude sequence, the patient's breathing amplitude state is obtained; wherein the breathing amplitude state includes: the breathing amplitude is stable, the breathing amplitude is gradually decreasing, or the breathing amplitude is gradually increasing; According to the proportion of chest and abdominal breathing, the patient's breathing pattern is obtained; wherein the breathing pattern includes: abdominal breathing, mixed breathing or chest breathing; Obtaining a determination index for chronic airway disease; wherein the determination index for chronic airway disease includes: The inhalation-exhalation ratio is less than the set value; and, When the patient's ventilation demand increases, if there is dynamic hyperinflation of the lungs, the respiratory amplitude gradually decreases; and, The breathing pattern is chest breathing; If the patient's inspiratory-expiratory ratio, respiratory amplitude status and respiratory pattern meet the judgment indicators of chronic airway disease, the patient is judged to be a possible chronic airway disease patient.

4. The dyspnea cause assessment system according to claim 3, characterized in that: The system also includes a wearable device; wherein the first flexible stretchable electronic sensor and the second flexible stretchable electronic sensor are respectively fixed to the wearable device, and correspond to the chest breathing detection site and the abdominal breathing detection site respectively; the first flexible stretchable electronic sensor, the second flexible stretchable electronic sensor, the analog-to-digital converter and the dyspnea cause assessment device are electrically connected.

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