A vest for diaphragmatic breathing training and a control method thereof

Abstract

The application discloses a vest for abdominal breathing training and a control method thereof, and relates to the field of medical rehabilitation equipment.The vest comprises a vest body, a flexible pressure sensor array, a microprocessor and a feedback device; the flexible pressure sensor array is arranged at the abdominal region of the vest body; the flexible pressure sensor array is used for collecting abdominal pressure in real time; the microprocessor is used for determining the breathing mode of each breath, the pressure peak of each inhalation and the pressure valley of each exhalation according to the collected abdominal pressure in real time, determining whether each inhalation is up to standard according to the pressure peak of each inhalation, determining whether each exhalation is up to standard according to the pressure valley of each exhalation, and controlling the feedback device to provide feedback and guide the patient to breathe in a correct way according to the up-to-standard result and the breathing mode of each breath.The application can monitor the inhalation mode, provide feedback in real time and guide the patient to master correct abdominal breathing skills.

Description

Technical Field

[0001] This application relates to the field of medical rehabilitation devices, and in particular to a vest for diaphragmatic breathing training and a method for controlling the vest. Background Technology

[0002] Abdominal breathing is one of the core techniques in pulmonary rehabilitation. It increases lung ventilation through diaphragmatic movement, improves blood oxygen saturation, and promotes expectoration. Currently, commonly used breathing training methods in clinical practice include: 1. Manual guidance method: Nurses or rehabilitation therapists verbally instruct patients to "inhale and expand their abdomen, exhale and contract their abdomen." Disadvantages: Relies on manual intervention, cannot be quantified and assessed, and patients are prone to developing incorrect chest breathing habits.

[0003] 2. Breathing trainer: Trains expiratory strength using devices such as air resistance balls. Disadvantages: Only trains exhalation; cannot monitor inhalation patterns and cannot distinguish between thoracic and abdominal breathing.

[0004] 3. Traditional abdominal binder devices: These use a single pressure sensor to monitor changes in the abdomen. Disadvantages: Single-point measurement is easily affected by body position and the tightness of the abdominal binder; the sensor is prone to displacement; data stability is poor; it cannot accurately determine respiratory depth and rhythm; and it can only record respiratory rate, not provide real-time feedback.

[0005] In conclusion, there is an urgent need for a breathing training vest that can monitor inhalation patterns, provide real-time feedback, and guide patients to master correct diaphragmatic breathing techniques. Summary of the Invention

[0006] The purpose of this application is to provide a vest for diaphragmatic breathing training and a control method thereof, which can monitor the inhalation mode, provide real-time feedback, and guide patients to master the correct diaphragmatic breathing techniques.

[0007] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a vest for abdominal breathing training, comprising: The vest body, a flexible pressure sensor array, a microprocessor, and a feedback device; the flexible pressure sensor array is located in the abdominal area of ​​the vest body.

[0008] A flexible pressure sensor array is used to collect abdominal pressure in real time; a microprocessor is used to determine the breathing pattern, the pressure peak value of each inhalation, and the pressure trough value of each exhalation based on the real-time collected abdominal pressure, and to determine whether each inhalation meets the target based on the pressure peak value of each inhalation, obtaining a first target result; and to determine whether each exhalation meets the target based on the pressure trough value of each exhalation, obtaining a second target result. The microprocessor then uses the first target result, the second target result, and the breathing pattern control feedback device to provide feedback and guide the patient to breathe correctly; the breathing pattern can be either thoracic breathing or abdominal breathing.

[0009] Secondly, this application provides a control method for a vest used for diaphragmatic breathing training, including: The breathing pattern, peak pressure of each inhalation, and trough pressure of each exhalation are determined based on real-time abdominal pressure data.

[0010] The first result of achieving the target is obtained by determining whether each inhalation meets the target based on the pressure peak value of each inhalation.

[0011] The second result of achieving the target is obtained by judging whether each exhalation meets the target based on the pressure trough value of each exhalation.

[0012] The device provides feedback and guides the patient to breathe correctly based on the first target achievement result, the second target achievement result, and the breathing mode control feedback for each breath; the breathing mode is either chest breathing mode or abdominal breathing mode.

[0013] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a vest for diaphragmatic breathing training. By incorporating a flexible pressure sensor array, it overcomes the shortcomings of using a single pressure sensor to monitor abdominal changes. Based on real-time collected abdominal pressure, it determines the breathing pattern, peak pressure of each inhalation, and trough pressure of each exhalation, thus monitoring the inhalation mode. The peak pressure of each inhalation determines whether the target for each inhalation has been met, yielding a first target result. The trough pressure of each exhalation determines whether the target for each exhalation has been met, yielding a second target result. Feedback is provided by a control feedback device based on the first and second target results and the breathing pattern of each breath, guiding the patient to breathe correctly. It can provide real-time feedback and guide the patient to master correct diaphragmatic breathing techniques. This wearable breathing training device is designed for post-lung cancer surgery patients, COPD patients, and individuals with weakened respiratory function. By sensing abdominal rise and fall in real time and providing biofeedback, it guides patients to master correct diaphragmatic breathing techniques, promoting lung rehabilitation. 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 embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the overall structure of the vest used for abdominal breathing training provided in this application.

[0016] Figure 2 This is a structural diagram of the flexible pressure sensor array provided in this application.

[0017] Figure 3 A block diagram of the internal structure of the control box provided in this application.

[0018] Figure 4 This is a schematic diagram of the APP interface provided in this application.

[0019] Reference numerals: 1: Vest body; 2: Flexible pressure sensor array; 3: Control box; 4: Shoulder strap adjustment buckle; 21: Flexible substrate; 22: Pressure sensing unit; 23: Flexible circuit connection line. Detailed Implementation

[0020] 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 this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] In one exemplary embodiment, such as Figure 1 As shown, a vest for abdominal breathing training is provided, including: a vest body 1, a flexible pressure sensor array 2, a microprocessor, and a feedback device; the flexible pressure sensor array 2 is disposed in the abdominal area of ​​the vest body 1.

[0023] The flexible pressure sensor array 2 is used to collect abdominal pressure in real time; the microprocessor is used to determine the breathing pattern, the pressure peak value of each inhalation and the pressure trough value of each exhalation based on the real-time collected abdominal pressure, and to determine whether each inhalation meets the target based on the pressure peak value of each inhalation, thus obtaining a first target result; and to determine whether each exhalation meets the target based on the pressure trough value of each exhalation, thus obtaining a second target result. The microprocessor then uses the first target result, the second target result and the breathing pattern of each inhalation to control the feedback device to provide feedback and guide the patient to breathe in the correct way; the breathing pattern is either thoracic breathing mode or abdominal breathing mode.

[0024] In practical applications, the flexible pressure sensor array 2 structure is as follows: Figure 2The system includes a flexible substrate 5, pressure sensing units 22, and flexible circuit connection lines 23. Multiple pressure sensing units 22 are arranged in an array and uniformly distributed on the flexible substrate 5. The flexible circuit connection lines 23 are disposed on the flexible substrate 5 and are used to electrically connect the multiple pressure sensing units 22 to each other and to transmit the pressure signals collected by the pressure sensing units 22 to the microprocessor.

[0025] In practical applications, the breathing pattern, peak pressure of each inhalation, and trough pressure of each exhalation are determined based on real-time collected abdominal pressure data. Specifically: A time-abdominal pressure curve was plotted based on real-time abdominal pressure data.

[0026] The peak pressure of each inhalation and the trough pressure of each exhalation are determined based on the time-abdominal pressure curve.

[0027] For any given breath, calculate the abdominal pressure change amplitude ΔP (i.e., the difference between the peak inspiratory pressure and the trough expiratory pressure). If ΔP < baseline pressure change amplitude ΔP_base × 30%, the breath is determined to be a thoracic breathing pattern; otherwise, it is an abdominal breathing pattern. In the initial training phase, before a preset number of m effective abdominal breaths have been collected, the baseline pressure change amplitude ΔP_base is set to a preset initial value. This initial value is determined based on the typical pressure change amplitude of resting abdominal breathing, preferably 15 mmHg-25 mmHg, more preferably 20 mmHg. Once the preset number of m effective abdominal breaths has been collected, the baseline pressure change amplitude ΔP_base is determined based on the average pressure change amplitude of the patient's first m effective abdominal breaths, where m is a preset positive integer (e.g., m=5).

[0028] In practical applications, the vest body 1 is made of a spandex and cotton blend (80% cotton, 20% spandex), which is breathable and sweat-absorbent. It features shoulder strap adjustment buckles 4, made of medical-grade silicone anti-slip material, allowing for strap length adjustment and preventing the vest from shifting. The adjustable Velcro side opening accommodates chest circumferences of 70cm-120cm, making it an adjustable-size, elastic wearable vest. A flexible pressure sensor pad, measuring 18cm x 12cm, is embedded in the front of the abdomen. It contains a 16 x 16 flexible pressure sensor array 2 with a spacing of 1.2cm, a sampling frequency of 50Hz, a pressure measurement range of 0mmHg-100mmHg, and a pressure measurement accuracy of ±2 mmHg.

[0029] In practical applications, vests used for diaphragmatic breathing training also include stainless steel dry electrodes for synchronously acquiring electrocardiogram signals and assessing respiratory-heart rate coupling.

[0030] The stainless steel dry electrodes are located on the inner side of the vest body 1, corresponding to the chest area. Specifically, there are two electrodes, located on the left and right chest areas of the inner side of the vest, so that when the patient wears the vest, the electrodes are in direct contact with the chest skin to collect electrocardiogram signals.

[0031] Assessing respiratory-heart rate coupling includes the following steps: The abdominal pressure signal collected by the flexible pressure sensor array 2 and the electrocardiogram signal collected by the stainless steel dry electrode are acquired in real time and synchronously.

[0032] The start and end times of each respiratory cycle are identified based on the abdominal pressure signal to obtain a respiratory signal time series.

[0033] Based on the electrocardiogram signal, the position of the R wave in each heartbeat is identified, and the continuous RR interval is calculated to obtain the heart rate variability time series.

[0034] Calculate the phase synchronization index between the respiratory signal time series and the heart rate variability time series.

[0035] The calculated phase synchronization index is compared with a preset coupling threshold. If the phase synchronization index is greater than or equal to the preset coupling threshold, it is determined that the breathing-heart rate coupling is good, indicating that the user is in an effective abdominal breathing training state and the autonomic nervous system regulation function is improved. If the phase synchronization index is less than the preset coupling threshold, it is determined that the breathing-heart rate coupling is poor, indicating that the user's breathing mode may be incorrect (such as chest breathing), the breathing rhythm is irregular, or the physical and mental state is poor. At this time, the feedback device is triggered (for example, controlling the red LED indicator to flash and cooperating with the vibration motor to vibrate) to issue a prompt signal, guiding the user to adjust the breathing mode or relax the body and mind.

[0036] In a more preferred embodiment, the preset coupling threshold is not a fixed value, but is adjustable within the range of 0.6 to 0.8 based on the user's age, resting heart rate, or disease type to accommodate physiological differences among different populations. The default value during system initialization is 0.7.

[0037] In another exemplary embodiment of this application, the feedback device includes: a vibration motor, a red LED indicator, a green LED indicator, and a blue LED indicator.

[0038] In another exemplary embodiment of this application, the vest for diaphragmatic breathing training further includes a control box 3, which is detachably disposed on the side of the vest body 1; the control box 3 houses the microprocessor, the red LED indicator, the green LED indicator, and the blue LED indicator. In practical applications, the control box 3 is made of ABS plastic, IP22 waterproof, and measures 6cm × 4cm × 1.5cm.

[0039] In another exemplary embodiment of this application, the vest for diaphragmatic breathing training further includes: a data terminal, a Bluetooth module, and a power supply; the control box 3 has the Bluetooth module and the power supply built in; the microprocessor is further configured to determine the respiratory rate, the time-abdominal pressure curve of each breath, the respiratory depth of each breath, the rhythm uniformity score of each breath, the effective number of breaths in a single training session, the pass rate of a single training session, the number of training sessions per day, the daily respiratory depth trend chart, and the daily rhythm uniformity trend chart based on the real-time collected abdominal pressure; the microprocessor is further configured to transmit the respiratory rate, the time-abdominal pressure curve of each breath, the respiratory depth of each breath, the rhythm uniformity score of each breath, the effective number of breaths in a single training session, and the daily rhythm uniformity trend chart through the Bluetooth module. The data terminal receives the following information: achievement rate, daily training sessions, daily respiratory depth trend graph, daily rhythm evenness trend graph, breathing pattern for each breath, peak pressure for each inhalation, trough pressure for each exhalation, achievement result for each inhalation, and achievement result for each exhalation. The data terminal displays and records the respiratory rate, time-abdominal pressure curve for each breath, respiratory depth for each breath, rhythm evenness score for each breath, effective number of breaths per training session, achievement rate for each training session, daily training sessions, daily respiratory depth trend graph, daily rhythm evenness trend graph, breathing pattern for each breath, peak pressure for each inhalation, trough pressure for each exhalation, achievement result for each inhalation, and achievement result for each exhalation. It also provides a gamified training mode. The power source is a lithium battery.

[0040] In practical applications, such as Figure 3As shown, the control box 3 also includes: a vibration motor drive circuit, an LED drive circuit, and a power management module. The microprocessor is electrically connected to each pressure sensing unit 22 in the flexible pressure sensor array 2 via a flexible circuit connection line 23, for receiving real-time abdominal pressure signals; the microprocessor is electrically connected to the Bluetooth module, for wirelessly transmitting respiratory data to the data terminal via the Bluetooth module; the microprocessor is electrically connected to the vibration motor drive circuit, and the vibration motor drive circuit is electrically connected to the vibration motor, for controlling the vibration of the vibration motor via the vibration motor drive circuit; the microprocessor is electrically connected to the LED drive circuit, and the LED drive circuit is electrically connected to the red LED indicator, the green LED indicator, and the blue LED indicator, for controlling the on / off and flashing of each LED indicator via the LED drive circuit; the input terminal of the power management module is electrically connected to the lithium battery, and the output terminal of the power management module is electrically connected to the microprocessor, the Bluetooth module, the vibration motor drive circuit, and the LED drive circuit, for converting the voltage of the lithium battery into the operating voltage required by each component and supplying power to each component. The control box 3 is electrically connected to the flexible pressure sensor array 2, the vibration motor and each LED indicator through a detachable interface. The detachable interface is used to separate the control box 3 from the vest body 1 when disassembling the control box 3.

[0041] In practical applications, the Bluetooth module is Bluetooth 5.0 with a transmission distance of 10 meters. The 500 mAh lithium battery provides 8 hours of continuous use and 7 days of standby time. Charging is via USB-C magnetic charging. The vest is removable and washable, and the control box can be wiped with alcohol.

[0042] In practical applications, the data terminal is a smartphone or tablet with a corresponding app installed.

[0043] In another exemplary embodiment of this application, determining whether each inhalation meets the standard is based on the pressure peak value of each inhalation, specifically as follows: For any single inhalation, if the peak pressure of the inhalation during that number of inhalations is greater than or equal to the inhalation threshold, then the inhalation during that number of inhalations is considered to have met the inhalation standard.

[0044] In another exemplary embodiment of this application, determining whether each exhalation meets the standard is based on the pressure trough value of each exhalation, specifically as follows: For any given exhalation, if the trough pressure value of the exhalation under the specified number of exhalations is less than or equal to the exhalation target threshold, then the exhalation under the specified number of exhalations is determined to have met the target.

[0045] In another exemplary embodiment of this application, the patient receives feedback and is guided to breathe correctly based on the first target achievement result, the second target achievement result, and the respiratory pattern control feedback device for each breath, specifically as follows: If the first target is met, then control the vibration motor to vibrate.

[0046] If the second target result is yes, then control the green LED indicator to flash.

[0047] If the set number of abdominal breathing cycles is completed, the blue LED light will remain on and the vibration motor will vibrate.

[0048] If the breathing pattern is chest breathing for three consecutive breaths, the red LED indicator will flash and the vibration motor will vibrate, guiding the patient to breathe correctly.

[0049] In another exemplary embodiment of this application, the inspiratory target threshold is determined according to the formula: inspiratory target threshold = P_max × α, where P_max is the baseline pressure peak, α is an adjustable inspiratory parameter determined based on the rate of achieving the target for n consecutive breaths, and n is a preset positive integer.

[0050] In another exemplary embodiment of this application, the expiratory target threshold is determined according to the formula: Expiratory target threshold = P_min × β, where P_min is the baseline pressure trough value, β is an adjustable expiratory parameter determined based on the expiratory target achievement rate of n consecutive breaths, and n is a preset positive integer. α and β are adjustable coefficients ranging from 0.6 to 0.9.

[0051] The working principle of the vest for abdominal breathing training provided in this application is as follows: 1. Sensing Layer: When the patient inhales, the abdomen expands, compressing the flexible pressure sensor array 2 and causing a change in pressure distribution; when exhaling, the abdomen contracts, and the pressure decreases. The flexible pressure sensor array 2 collects pressure values ​​in real time and converts them into digital signals.

[0052] 2. Processing Layer: The microprocessor within the control box 3 plots a time-abdominal pressure curve based on the pressure values ​​collected in real-time by the flexible pressure sensor array 2, and analyzes the time-abdominal pressure curve to obtain: The inhalation start time, peak time, and duration of each inhalation.

[0053] The onset time, trough, and duration of each exhalation.

[0054] Respiratory rate, respiratory depth, and rhythm evenness scores.

[0055] The rhythm evenness score is calculated based on the rhythm variation coefficient of the most recent k consecutive complete respiratory cycles, specifically as follows: (1) Acquiring the cycle durations of the last k consecutive complete respiratory cycles , wherein k is a preset positive integer, preferably 10; each complete respiratory cycle includes one inspiration and one expiration; the microprocessor determines the start time and end time of each respiration by detecting the positions of the troughs and peaks of the pressure waveform based on the time-abdominal pressure curve, and the time difference between the start times of two adjacent respirations is the cycle duration of a complete respiratory cycle, or alternatively, the time difference between the inspiration start time and the next inspiration start time is the cycle duration.

[0056] (2) Calculating the average value T_mean of k cycle durations: .

[0057] (3) Calculating the standard deviation σ of k cycle durations: σ= .

[0058] (4) Calculating the rhythm variation coefficient CV: CV=(σ / T_mean)×100%.

[0059] (5) Mapping the rhythm variation coefficient CV to a rhythm uniformity score (Score), wherein the mapping formula is: Score=100×(1-CV), when CV<1.

[0060] Score=0, when CV≥1.

[0061] wherein the value range of Score is 0 to 100, the closer Score is to 100, the more uniform the respiratory rhythm is (that is, the smaller the difference in cycle duration between each respiration is), and the closer Score is to 0, the more irregular the respiratory rhythm is (that is, the larger the difference in cycle duration between each respiration is).

[0062] preferably, the rhythm uniformity score can also adopt a grading system, for example: when CV≤0.05, it is rated as "Excellent" (Score≥95).

[0063] when 0.05<CV≤0.10, it is rated as "Good" (95>Score≥90).

[0064] when 0.10<CV≤0.15, it is rated as "Medium" (90>Score≥85).

[0065] when CV>0.15, it is rated as "To be improved" (Score<85).

[0066] wherein, drawing the time-abdominal pressure curve according to the pressure values collected in real time by the flexible pressure sensor array 2 is specifically: At each sampling moment, the M×N pressure sensing units 22 in the flexible pressure sensor array 2 respectively collect M×N local pressure values.

[0067] The microprocessor performs a weighted average of M×N local pressure values ​​at each sampling time to obtain a comprehensive pressure value representing the overall abdominal pressure at that time. The weight of each pressure sensing unit 22 is determined according to the pressure change amplitude of the unit during baseline abdominal breathing, and the unit with a larger pressure change amplitude is given a higher weight.

[0068] The microprocessor connects the combined pressure values ​​at each sampling time in chronological order to generate a time-abdominal pressure curve.

[0069] 3. Feedback layer: Inhalation meets standard: The built-in micro-vibration motor in the sensor area vibrates lightly once to indicate "You're using the right amount of force".

[0070] Exhalation target met: The green LED indicator in control box 3 flashes once.

[0071] Training complete: After accumulating 20 effective breaths (diaphragmatic breathing mode), the blue light inside control box 3 will stay on and vibrate 3 times to celebrate.

[0072] Error message: If you breathe with your chest for three consecutive times, the red light will flash and vibrate, reminding you to "breathe with your abdomen".

[0073] 4. Data Layer: Connects to a mobile app via Bluetooth to record respiratory data (respiratory rate, time-abdominal pressure curve for each breath, respiratory depth for each breath, rhythm uniformity score for each breath, effective number of breaths per training session, achievement rate for each training session, number of training sessions per day, daily respiratory depth trend chart and daily rhythm uniformity trend chart, respiratory pattern for each breath, pressure peak for each inhalation, pressure trough for each exhalation, achievement result for each inhalation, and achievement result for each exhalation), and generates weekly reports, which nurses can view and adjust training goals on.

[0074] This application also provides a more specific embodiment, detailing the vest used for abdominal breathing training described above, specifically including: Wearable vest body 1; Flexible pressure sensor array 2: Embedded and installed at the corresponding position on the abdomen of the vest body 1, consisting of an M×N matrix of pressure sensing units 22; Control box 3: Detachably installed on the side of the vest body 1, with built-in microprocessor, vibration motor, three-color LED indicator, Bluetooth module and power supply; Data interaction system including a data terminal with built-in mobile APP.

[0075] The flexible pressure sensor array 2 adopts a 16×16 grid layout, with the spacing between adjacent sensing units ranging from 1.0cm to 1.5cm, and a coverage area of ​​no less than 15cm×10cm. Each sensing unit is a capacitive or piezoresistive flexible pressure sensor with a measurement range of 0mmHg-100mmHg and an accuracy of ±2mmHg. The array layout can capture the spatiotemporal changes in abdominal pressure distribution, identify the bulging area and movement trajectory of the abdomen during respiration, and avoid measurement errors caused by the positional offset of single-point sensors.

[0076] The feedback system consists of a vibration motor and a three-color LED indicator. The vibration motor is located in the abdominal sensor area. The control box 3 only contains a microprocessor, LED indicator, Bluetooth, and power supply. The three-color LED is: green (for indicating that breathing has reached the target), red (for error indication), and blue (for indicating that training is complete).

[0077] The microprocessor is used to execute the feedback logic and dynamically adjust the training difficulty: When the peak pressure of a certain inhalation is detected to be greater than or equal to the inhalation threshold, the vibration motor vibrates once (200ms) to indicate that the inhalation has reached the target.

[0078] When the pressure trough of a given exhalation is detected to be less than or equal to the exhalation threshold, the green LED will flash once (100ms) to indicate that exhalation is complete.

[0079] When the chest breathing pattern is detected after 3 consecutive breaths, the LED red light flashes and the vibration motor vibrates 3 times in a row, indicating "Please breathe with your abdomen".

[0080] The microprocessor is used to execute an adaptive learning algorithm to determine the inspiratory and expiratory target thresholds, specifically including: an initial phase, an adaptive phase, and a difficulty-adaptive phase. Initial stage: Upon initial use by the patient or after system reset, the microprocessor employs preset initial inspiratory and expiratory thresholds. These thresholds are set based on general clinical experience values ​​for diaphragmatic breathing training; for example, the initial inspiratory threshold is preset to 60 mmHg, and the initial expiratory threshold to 20 mmHg. Simultaneously, the microprocessor determines whether each breath meets the target based on these thresholds and temporarily stores the breathing data that meets the target and is identified as diaphragmatic breathing.

[0081] Adaptive phase: Once the microprocessor has collected 5 valid abdominal breaths (i.e., the breathing pattern is determined to be abdominal breathing, and both inhalation and exhalation meet the standards), it automatically calculates the average peak pressure of these 5 valid abdominal breaths as the baseline peak pressure P_max, and calculates the average trough pressure of these 5 valid abdominal breaths as the baseline trough pressure P_min. From this point onward, the microprocessor switches to using the formula: The inspiratory threshold = P_max × 0.8 and the expiratory threshold = P_min × 1.2 are used to calculate the dynamic threshold.

[0082] Threshold switching decision logic: If, before accumulating 5 effective abdominal breaths, the patient's m consecutive breaths (e.g., m=8) are all judged as chest breathing mode, the microprocessor will prompt "Please adjust the vest wearing position or restart training" through the feedback device, and will maintain the use of the initial threshold until 5 effective abdominal breaths are successfully collected, after which it will switch to the adaptive threshold.

[0083] Difficulty Adaptation Phase: The pass rate was collected from the most recent 10 consecutive breaths (determined by the number of times the abdominal breathing pattern was completed).

[0084] If the target achievement rate is >80%, then adjust: Inspiratory target achievement threshold = P_max × 0.9. Exhalation target achievement threshold = P_min × 0.9.

[0085] If the target achievement rate is <50%, then adjust: Inspiratory target achievement threshold = P_max × 0.7. Exhalation target achievement threshold = P_min × 1.1.

[0086] If the target achievement rate is between 50% and 80%, then the current inhalation target achievement threshold and expiration target achievement threshold will remain unchanged.

[0087] This application also provides an embodiment, which differs from the above embodiments in that the microprocessor in this embodiment is further used for anomaly detection. In an exemplary embodiment, the microprocessor is further used for respiratory anomaly detection, specifically: The system calculates the current respiratory rate in real time. If the respiratory rate is <8 breaths / min or >30 breaths / min, an abnormality alert is triggered. Specifically, this includes controlling the red LED indicator to flash at a frequency of 2Hz, controlling the vibration motor to vibrate in an intermittent mode (vibrate for 200ms, stop for 800ms, cycle), and sending an abnormality alert notification to the data terminal via the Bluetooth module.

[0088] Calculate the coefficient of variation (CV). If CV > 20%, it is determined that the breathing rhythm is irregular. Control the blue LED indicator to flash and display the prompt message "irregular breathing" through the data terminal.

[0089] In practical applications, the Bluetooth module transmits real-time breathing data to a mobile app, such as... Figure 4 As shown. The APP interface includes: Real-time breathing waveform display area: Dynamically plots time-pressure curves based on abdominal pressure values, intuitively displaying the fluctuations in current breathing.

[0090] Training data statistics area: Displays "Number of training sessions today" (e.g., 20 times) and "Completion rate" (e.g., 85%).

[0091] Gamified training entry: Provides interactive training modules such as "Blowing up balloons mini-game". Click to enter the gamified breathing training mode.

[0092] The nurse-side data dashboard displays the training status of multiple patients in a list format, such as "Patient A: 20 training sessions, 85% pass rate", "Patient B: 15 training sessions, 72% pass rate", "Patient C: 18 training sessions, 90% pass rate", etc., which makes it convenient for medical staff to remotely view and manage the patients' rehabilitation progress.

[0093] In one exemplary embodiment, the data terminal is further configured to record historical training data and generate a rehabilitation trend graph based on the historical data.

[0094] The historical data includes at least one or more of the following: I. Training Overview Data: The date and start and end times of each training session; the total duration of each training session; and the total number of breaths during each training session.

[0095] The effective number of breaths per training session (i.e., the number of times the breathing pattern is determined to be diaphragmatic breathing).

[0096] The number of inhalations and exhalations that met the target in each training session; the breathing target rate for each training session (i.e., the percentage of effective breathing counts out of the total number of breathing counts, or the percentage of inhalations / exhalations that met the target out of the corresponding number of breaths).

[0097] II. Respiratory quality data: Peak and trough inspiratory pressure for each effective breath during each training session; average peak and trough inspiratory pressure for each training session; average respiratory depth for each training session (i.e., the average difference between peak and trough inspiratory pressure); average respiratory rate for each training session; average rhythm evenness score or average rhythm variation coefficient for each training session.

[0098] III. Physiological Coupling Data: Average heart rate per training session; heart rate variability index per training session; respiratory-heart rate coupling phase synchronization index per training session.

[0099] IV. Training Mode and Feedback Data: The training mode for each training session (free training mode or gamified training mode); if it is gamified training mode, record the game type and game score; record abnormal events, including the type of abnormality (abnormal breathing rate, irregular rhythm, continuous chest breathing, etc.), the time of occurrence and the duration.

[0100] The recovery trend chart is generated as follows: The data terminal aggregates and statistically analyzes the historical data according to a preset time dimension (daily, weekly, or monthly) to generate at least one of the following recovery trend charts: Daily / weekly respiratory target achievement rate trend chart; Daily / weekly average respiratory depth trend chart.

[0101] Daily / weekly effective respiratory rate trend chart; Daily / weekly average respiratory rate trend chart.

[0102] Daily / weekly rhythm evenness score trend chart; daily / weekly training duration trend chart.

[0103] Daily / weekly respiratory-heart rate coupling index trend chart.

[0104] Specifically, the gamified training mode is provided by the data terminal through a companion app, and includes the following steps: The data terminal receives real-time comprehensive pressure values, peak inspiratory pressure, trough expiratory pressure, breathing patterns, and target achievement results from the microprocessor via the Bluetooth module. The app maps these real-time comprehensive pressure values ​​to dynamic changes in virtual objects within the game, according to preset game rules. For example, in the "Blow Up a Balloon" game, the virtual object is a balloon. When the patient inhales, the balloon expands as the inspiratory pressure increases. When the inspiratory pressure reaches the target threshold, the balloon reaches the target size and displays a target achievement animation. When the patient exhales, the balloon contracts as the expiratory pressure decreases. When the expiratory pressure reaches the target threshold, the balloon completely contracts and displays visual feedback indicating that the expiratory pressure has been achieved.

[0105] If multiple consecutive breaths are identified as chest breathing, the virtual balloon will turn red and shake, while a prompt will appear to guide the patient to switch to abdominal breathing.

[0106] After completing the preset training objectives, a training summary is displayed, including the achievement rate, effective breathing count, and breathing depth trend graphs.

[0107] like Figure 4 As shown, the app allows nurses to remotely view training data from multiple patients and adjust training plans.

[0108] In practical applications, the feedback system also includes: a buzzer: used for serious error messages or emergency alerts.

[0109] This application aims to provide a vest for diaphragmatic breathing training that can sense abdominal breathing movements in real time, provide multimodal biofeedback, and adaptively adjust training goals. It solves the problems of lagging feedback, inaccurate assessment, and low patient compliance in related technologies, and can be widely used in pulmonary rehabilitation training for patients after lung cancer surgery, COPD, etc.

[0110] Related technologies use single-point sensors, which are prone to displacement errors. This application uses a flexible pressure sensor array to capture pressure distribution and resist displacement interference.

[0111] In related technologies, there is no feedback or the information is only available on the app. This application provides real-time vibration and LED feedback to reinforce correct behavior.

[0112] The related technologies are tedious and difficult to stick to, resulting in low patient compliance. This application uses gamification and remote supervision to improve participation.

[0113] In related technologies, nurses and patients need one-on-one guidance. This application allows nurses to remotely view data from multiple patients and manage it centrally.

[0114] This application employs a multimodal feedback system: vibration alert + LED indicator. Based on the same inventive concept, this application also provides a control method for the aforementioned vest used for diaphragmatic breathing training. The control method includes: The breathing pattern, peak pressure of each inhalation, and trough pressure of each exhalation are determined based on real-time abdominal pressure data.

[0115] The first result of achieving the target is obtained by determining whether each inhalation meets the target based on the pressure peak value of each inhalation.

[0116] The second result of achieving the target is obtained by judging whether each exhalation meets the target based on the pressure trough value of each exhalation.

[0117] The device provides feedback and guides the patient to breathe correctly based on the first target achievement result, the second target achievement result, and the breathing mode control feedback for each breath; the breathing mode is either chest breathing mode or abdominal breathing mode.

[0118] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0119] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A vest for diaphragmatic breathing training, characterized in that, The vest used for diaphragmatic breathing training includes: The vest body, a flexible pressure sensor array, a microprocessor, and a feedback device; the flexible pressure sensor array is located in the abdominal area of ​​the vest body. A flexible pressure sensor array is used to collect abdominal pressure in real time; a microprocessor is used to determine the breathing pattern, the pressure peak value of each inhalation, and the pressure trough value of each exhalation based on the real-time collected abdominal pressure, and to determine whether each inhalation meets the target based on the pressure peak value of each inhalation, obtaining a first target result; and to determine whether each exhalation meets the target based on the pressure trough value of each exhalation, obtaining a second target result. The microprocessor then uses the first target result, the second target result, and the breathing pattern control feedback device to provide feedback and guide the patient to breathe correctly; the breathing pattern can be either thoracic breathing or abdominal breathing.

2. The vest for diaphragmatic breathing training according to claim 1, characterized in that, The feedback device includes: a vibration motor, a red LED indicator, a green LED indicator, and a blue LED indicator.

3. The vest for diaphragmatic breathing training according to claim 2, characterized in that, The vest for diaphragmatic breathing training also includes a control box, which is detachably mounted on the side of the vest body; the control box contains the microprocessor, the red LED indicator, the green LED indicator, and the blue LED indicator.

4. The vest for abdominal breathing training according to claim 2, characterized in that, The vest for diaphragmatic breathing training also includes: a data terminal, a Bluetooth module, and a power supply; the control box integrates the Bluetooth module and the power supply; the microprocessor is further used to determine the respiratory rate, the time-abdominal pressure curve for each breath, the respiratory depth for each breath, the rhythm evenness score for each breath, the effective number of breaths in a single training session, the achievement rate of a single training session, the number of training sessions per day, the daily respiratory depth trend chart, and the daily rhythm evenness trend chart based on the real-time collected abdominal pressure; the microprocessor is also used to transmit the respiratory rate, the time-abdominal pressure curve for each breath, the respiratory depth for each breath, the rhythm evenness score for each breath, the effective number of breaths in a single training session, the achievement rate of a single training session, and the daily training frequency through the Bluetooth module. The training sessions, daily respiratory depth trend charts and daily rhythm uniformity trend charts, breathing patterns for each breath, peak pressure for each inhalation, trough pressure for each exhalation, achievement results for each inhalation, and achievement results for each exhalation are sent to the data terminal. The data terminal is used to display and record respiratory rate, time-abdominal pressure curves for each breath, respiratory depth for each breath, rhythm uniformity score for each breath, effective number of breaths in a single training session, achievement rate for a single training session, daily training sessions, daily respiratory depth trend charts and daily rhythm uniformity trend charts, breathing patterns for each breath, peak pressure for each inhalation, trough pressure for each exhalation, achievement results for each inhalation, and achievement results for each exhalation, and provides a gamified training mode.

5. The vest for diaphragmatic breathing training according to claim 1, characterized in that, Determine whether each inhalation meets the target based on the peak pressure of each inhalation. Specifically: For any single inhalation, if the peak pressure of the inhalation during that number of inhalations is greater than or equal to the inhalation threshold, then the inhalation during that number of inhalations is considered to have met the inhalation standard.

6. The vest for diaphragmatic breathing training according to claim 1, characterized in that, The determination of whether each exhalation meets the target is based on the trough pressure value of each exhalation. Specifically: For any given exhalation, if the trough pressure value of the exhalation under the specified number of exhalations is less than or equal to the exhalation target threshold, then the exhalation under the specified number of exhalations is determined to have met the target.

7. The vest for abdominal breathing training according to claim 2, characterized in that, Based on the first target achievement result, the second target achievement result, and the breathing pattern control feedback device for each breath, feedback is provided to guide the patient to breathe correctly, specifically as follows: If the first target is met, then control the vibration motor to vibrate; If the second target is met, the green LED indicator light will flash. If the set number of abdominal breathing cycles is completed, the blue LED light will remain on and the vibration motor will vibrate. If the breathing pattern is chest breathing for three consecutive breaths, the red LED indicator will flash and the vibration motor will vibrate, guiding the patient to breathe correctly.

8. The vest for diaphragmatic breathing training according to claim 5, characterized in that, The inspiratory threshold is determined by the formula: Inspiratory threshold = P_max × α, where P_max is the baseline pressure peak and α is the adjustable inspiratory parameter.

9. The vest for diaphragmatic breathing training according to claim 6, characterized in that, The target expiratory pressure threshold is determined by the formula: Expiratory pressure threshold = P_min × β, where P_min is the baseline pressure trough value and β is the adjustable expiratory parameter.

10. A control method for a vest used for diaphragmatic breathing training as described in any one of claims 1-9, characterized in that, The control method includes: The breathing pattern, peak pressure of each inhalation, and trough pressure of each exhalation are determined based on the real-time abdominal pressure data. Determine whether each inhalation meets the target based on the pressure peak value of each inhalation, and obtain the first target-meeting result; The second target result is obtained by judging whether each exhalation meets the target based on the trough pressure value of each exhalation; The device provides feedback and guides the patient to breathe correctly based on the first target achievement result, the second target achievement result, and the breathing mode control feedback for each breath; the breathing mode is either chest breathing mode or abdominal breathing mode.

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