Stepped pressurization mode capable of being used for medical hyperbaric oxygen chamber

Abstract

The invention relates to the technical field of medical hyperbaric oxygen chamber control, in particular to a stepped pressurization mode for a medical hyperbaric oxygen chamber, which comprises the following steps of: acquiring a heart rate variability basic value, a respiratory rate baseline value and individual physiological characteristic parameters of body surface area of a user, analyzing preset target treatment pressure, and determining the target treatment pressure; and generating a staged pressurization rate set containing the multi-stage pressure increasing rate and the corresponding target pressure sub-value through a preset stepped pressurization strategy model. After pressurization is started, the real-time heart rate variability and respiratory rate of a user are collected in real time, the pressurization rate of the current stage is adjusted according to dynamic physiological data in each pressure increasing stage, and after the pressure in the cabin reaches a target pressure sub-value, the next stage is started until the target treatment pressure is reached. According to the mode, stage pressurization parameters are customized by combining individual physiological characteristics, and the pressurization rate is dynamically regulated and controlled by real-time physiological data to adapt to the physiological state of a user.

Description

Technical Field

[0001] This invention relates to the field of medical hyperbaric oxygen chamber control technology, and in particular to a stepped pressurization method that can be used in medical hyperbaric oxygen chambers. Background Technology

[0002] Most existing hyperbaric oxygen chambers use a stepped pressurization mode with preset fixed parameters. The pressurization rate and the target pressure value at each stage are preset according to general treatment standards. The core basis for pressurization operation is only the target treatment pressure to be achieved. The setting of pressurization parameters does not take into account the individual physiological data of the user. The pressurization process only completes the pressure increase according to the preset program. No physiological indicators are involved in the planning and execution control of pressurization parameters.

[0003] Conventional hyperbaric oxygen chamber pressurization methods employ standardized pressurization parameters, which fail to accommodate individual differences in heart rate variability, baseline respiratory rate, and body surface area among users. The fixed pressurization rate and pressure stages are ill-suited to varying physiological tolerance levels, leading to mismatches between the pressurization process and the user's physiological state. Furthermore, conventional pressurization methods operate at preset rates during each pressure increment, failing to adjust the pressurization speed based on the user's real-time heart rate variability and respiratory rate, and unable to generate personalized, staged pressurization parameters based on individual physiological characteristics. Consequently, the pressurization process lacks a proper correlation with the user's baseline physiological state and real-time physiological response. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and propose a step pressurization method that can be used in medical hyperbaric oxygen chambers.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a stepped pressurization method applicable to medical hyperbaric oxygen chambers, comprising: The user's individual physiological characteristics parameters are obtained, including the user's baseline heart rate variability, baseline respiratory rate, and body surface area. Receive and analyze the preset target treatment pressure, which is the final gas pressure value that needs to be achieved in the medical hyperbaric oxygen chamber after the pressurization operation is completed; Based on the individual physiological characteristic parameters and the target treatment pressure, a set of pressure increase rates in stages is generated through a preset step-by-step pressure increase strategy model. The set of pressure increase rates includes the pressure increase rate of multiple pressure increase stages and the target pressure sub-value of the corresponding stage. After the pressurization operation is started, dynamic physiological monitoring data of the user in the medical hyperbaric oxygen chamber is collected in real time. The dynamic physiological monitoring data includes real-time heart rate variability and real-time respiratory rate. During each pressure increment stage, the pressure increment rate of the current stage is dynamically adjusted based on the dynamic physiological monitoring data. When the gas pressure inside the medical hyperbaric oxygen chamber reaches the target pressure value, the next pressure increment stage begins, until the target treatment pressure is reached.

[0006] As a further aspect of the present invention, the step of generating a set of phased pressurization rates based on the individual physiological characteristic parameters and the target treatment pressure through a preset stepped pressurization strategy model includes: The baseline heart rate variability is input into the pressure tolerance analysis unit of the stepped pressurization strategy model to calculate the user's initial pressure tolerance threshold. The baseline respiratory rate value is input into the respiratory adaptation analysis unit of the stepped pressurization strategy model to calculate the user's respiratory pressure load reference coefficient. Based on the body surface area, the initial stage duration of the pressure increase phase is determined in the calculation unit of the stepped pressurization strategy model, and the initial stage duration is negatively correlated with the body surface area. The target treatment pressure, the initial pressure tolerance threshold, the respiratory pressure load reference coefficient, and the initial phase duration are all input into the integrated calculation unit of the stepwise pressurization strategy model; The integrated calculation unit determines the total number of pressure escalation stages based on the difference between the target treatment pressure and the initial pressure tolerance threshold. The integrated calculation unit assigns different initial pressure increment rates to different pressure increment stages based on the respiratory pressure load reference coefficient, wherein the higher the respiratory pressure load reference coefficient, the lower the initial pressure increment rate assigned to the stage. The integrated calculation unit uses the initial stage duration as the initial stage duration of the first pressure increase stage, and combines it with the total number of stages and the total target pressure to calculate the initial stage duration of subsequent pressure increase stages, thus forming a preliminary time plan for the pressure increase stage.

[0007] As a further aspect of the present invention, the real-time acquisition of dynamic physiological monitoring data of users inside the medical hyperbaric oxygen chamber includes: The voltage waveform of the user's electrocardiogram signal is continuously collected by a bioelectrical signal sensor worn on the user's body. The voltage waveform of continuously acquired electrocardiogram signals is analyzed in real time, and the degree of variation of the time interval between adjacent heartbeat cycles is calculated as the real-time heart rate variability. The flow rate signal of the user's breathing airflow is monitored by a flow rate sensor installed in the oxygen mask or breathing circuit. The monitored flow rate signal is processed in real time to identify the duration of a single respiratory cycle, and the real-time respiratory rate is calculated based on the number of respiratory cycles per unit time.

[0008] As a further aspect of the present invention, the dynamic adjustment of the pressure increase rate at each pressure increase stage based on the dynamic physiological monitoring data during the pressurization process includes: During any pressure increase phase, the real-time heart rate variability and the real-time respiratory rate are continuously received; The real-time heart rate variability received at the current stage is compared with the baseline heart rate variability value of the stepped pressurization strategy model to calculate the heart rate variability deviation. The real-time respiratory rate received at the current stage is compared with the baseline respiratory rate value in the stepped pressurization strategy model to calculate the respiratory rate deviation. The calculated deviations in heart rate variability and respiratory rate are input into the preset rate adjustment decision logic. The rate adjustment decision logic is preset with a rate adjustment threshold. When the absolute value of either the heart rate variability deviation or the respiratory rate deviation exceeds the rate adjustment threshold, the rate adjustment decision logic generates a deceleration and pressurization command, and adjusts the initial pressure increase rate of the current pressure increase phase by one or more preset deceleration steps according to the magnitude of the deviation exceeding the threshold. When the absolute values ​​of the heart rate variability deviation and the respiratory rate deviation do not exceed the rate adjustment threshold, the rate adjustment decision logic queries a preset rate fine-tuning reference table based on the values ​​of the heart rate variability deviation and the respiratory rate deviation to obtain the correction increment of the pressure increase rate corresponding to the current stage, and fine-tunes the initial pressure increase rate of the current stage based on the correction increment.

[0009] As a further aspect of the present invention, the rate adjustment decision logic further generates a pause command based on the heart rate variability deviation and respiratory rate deviation, including: The rate adjustment decision logic has a preset pause pressure threshold, which is greater than the rate adjustment threshold. During any pressure increase phase, the absolute values ​​of the heart rate variability deviation and respiratory rate deviation are compared in real time with the magnitude of the pressure cessation threshold. When the absolute value of either the heart rate variability deviation or the respiratory rate deviation reaches or exceeds the pause pressurization threshold, the rate adjustment decision logic immediately generates a pause pressurization command. In response to the aforementioned pause pressurization command, the pressurization operation of the medical hyperbaric oxygen chamber is immediately stopped, and the current gas pressure value inside the medical hyperbaric oxygen chamber is maintained. During the pause in pressurization, the dynamic physiological monitoring data is continuously monitored. When the absolute values ​​of the heart rate variability deviation and respiratory rate deviation both fall below the rate adjustment threshold and remain stable for a preset period of time, the rate adjustment decision logic generates a command to resume pressurization. In response to the pressurization resumption command, the pressurization process of the current pressure increment phase is restarted at an initial pressure increment rate lower than the pressure before the pause.

[0010] As a further aspect of the present invention, before entering the next stage of increasing pressure, a step of conducting a phased adaptation assessment of the user is included, the step comprising: During the current pressure increase phase, when the gas pressure inside the medical hyperbaric oxygen chamber reaches the target pressure sub-value, the gas pressure is kept constant, and the phased adaptation assessment process is initiated. Under constant gas pressure, collect data on the stability of the user's heart rate variability and respiratory rate over a specific time period. The collected data on the stability of the user's heart rate variability and the stability of the user's respiratory rate are input into the adaptive evaluation module of the stepped pressurization strategy model. The adaptability assessment module calculates a comprehensive adaptability index based on the stability data of the user's heart rate variability and the stability data of the user's respiratory rate. The adaptive assessment module has a preset adaptation threshold for entering the next stage; Compare the comprehensive adaptation index with the adaptation threshold for entering the next stage; When the comprehensive adaptation index is greater than or equal to the adaptation threshold for entering the next stage, the adaptation assessment module generates an instruction to allow entry into the next stage; When the comprehensive adaptation index is less than the adaptation threshold for entering the next stage, the adaptation assessment module generates an instruction to extend the adaptation time of the current stage. In response to the instruction to extend the adaptation time of this stage, the time is extended by an integer multiple of the specific duration under the current gas pressure, and the process from collecting stability data to comparing the comprehensive adaptation index is re-executed until the comprehensive adaptation index meets the conditions or reaches the preset maximum extension time.

[0011] As a further aspect of the present invention, the step of inputting the collected user heart rate variability stability data and user respiratory rate stability data into the adaptive evaluation module of the stepped pressurization strategy model includes: The adaptive assessment module performs statistical analysis on the heart rate variability stability data over a specific time period, and calculates the ratio of the variance to the mean of the heart rate variability as the heart rate stability coefficient. The adaptive assessment module performs statistical analysis on respiratory rate stability data over a specific time period, and calculates the ratio of the variance to the mean of the respiratory rate as the respiratory stability coefficient. Extract the user's heart rate variability stability coefficient and respiratory rate stability coefficient at the end of the previous pressure increase phase from the historical data of the phased pressurization. Calculate the rate of change of the heart rate stability coefficient in the current stage relative to the heart rate stability coefficient at the end of the previous stage, and use it as the heart rate adaptive increment. Calculate the rate of change of the respiratory stability coefficient in the current stage relative to the respiratory stability coefficient at the end of the previous stage, as the respiratory adaptation increment; The comprehensive adaptation index is obtained by weighted summing of the heart rate stability coefficient, respiratory stability coefficient, heart rate adaptation increment, and respiratory adaptation increment.

[0012] As a further aspect of the present invention, the method also includes a dynamic safety assurance step during the pressurization process: Establish a safe range for dynamic physiological monitoring data, which includes the upper and lower limits of heart rate variability and respiratory rate. Throughout the pressurization process, the real-time heart rate variability and real-time respiratory rate are continuously compared with the safe range. When the real-time heart rate variability or real-time respiratory rate exceeds its corresponding safety range, a safety intervention command is immediately generated. The safety intervention command has a higher priority than any command that adjusts the rate of increase in pressure. In response to the safety intervention command, the pressurization process is immediately stopped, and the gas pressure inside the medical hyperbaric oxygen chamber is reduced to a preset safe pressure threshold at a preset safe decompression rate, and an audible and visual alarm is activated.

[0013] As a further aspect of the present invention, after the target therapeutic pressure is reached, a physiological state monitoring and reassessment step during the pressure maintenance phase is also included: During the period when the gas pressure in the medical hyperbaric oxygen chamber is stabilized at the target treatment pressure, heart rate variability and respiratory rate are continuously collected and recorded during the maintenance phase. Calculate the mean heart rate variability and mean respiratory rate during the maintenance phase; The calculated mean heart rate variability and mean respiratory rate during the maintenance phase are compared with the baseline heart rate variability and baseline respiratory rate values ​​in the individual physiological characteristic parameters. Based on the comparison results, the user's overall level of adaptation to the target therapeutic stress is assessed, and an adaptation level assessment report is generated.

[0014] As a further aspect of the present invention, the adaptation level assessment report, the dynamic physiological monitoring data of each pressure escalation stage, the final adjusted pressurization rate set, and the results of the phased adaptation assessment are stored together as a complete record of this pressurization treatment process, which is used to update the internal parameters of the stepwise pressurization strategy model.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: By combining the user's baseline heart rate variability, baseline respiratory rate, and individual physiological characteristics such as body surface area, and in conjunction with the preset target treatment pressure, a set of pressure increment rates and corresponding target pressure sub-values ​​for each stage is generated through a pre-set stepwise pressurization strategy model. The generation of pressurization parameters is directly related to the user's own physiological characteristics. The setting of the pressure increment rate for each stage is in line with the user's individual physiological tolerance. The division of target pressure sub-values ​​for each stage corresponds to the user's body surface area and basic physiological indicators. The parameter planning for the pressure increment stage can match the physiological conditions of different users.

[0016] During each stage of pressure escalation, real-time dynamic physiological monitoring data of heart rate variability and respiratory rate are collected. Based on this dynamic physiological monitoring data, the pressure escalation rate of the current stage is dynamically adjusted. The change in the pressure escalation rate is linked to the user's real-time physiological state, and the pressure escalation speed is adjusted synchronously with the changes in the user's real-time physiological indicators. The pressure escalation process enters the next escalation stage only after reaching the target pressure value of the corresponding stage. The staged pressure escalation method, combined with the rate adjustment of real-time physiological data, ensures that the rate change of the pressure escalation process matches the user's real-time physiological feedback, and the pressure escalation process always conforms to the user's current physiological response state. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a stepped pressurization method for use in a medical hyperbaric oxygen chamber, as described in this invention. Figure 2 A flowchart for real-time acquisition of dynamic physiological monitoring data; Figure 3 Changes in heart rate / respiratory stability indicators; Figure 4 A time-series analysis of the correlation between cabin pressure and physiological indicators; Figure 5 A graph showing the fluctuation trend of physiological indicators during the 20-minute pressure maintenance phase of a medical hyperbaric oxygen chamber. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0020] See Figure 1 The system acquires the user's individual physiological parameters, including baseline heart rate variability, baseline respiratory rate, and body surface area. It receives and analyzes a preset target treatment pressure, which is the final gas pressure to be achieved in the hyperbaric oxygen chamber after pressurization. Based on the individual physiological parameters and the target treatment pressure, a set of phased pressurization rates is generated using a pre-defined stepwise pressurization strategy model. This set includes multiple pressure increment rates for each pressure increment phase and a corresponding target pressure sub-value for each phase. After pressurization is initiated, real-time dynamic physiological monitoring data of the user inside the hyperbaric oxygen chamber is collected, primarily including real-time heart rate variability and real-time respiratory rate. During each pressure increment phase, the pressure increment rate is dynamically adjusted based on the real-time collected dynamic physiological monitoring data. When the gas pressure inside the hyperbaric oxygen chamber reaches the target pressure sub-value for the current phase, the system moves to the next pressure increment phase, continuing this process phase by phase until the gas pressure inside the chamber finally reaches the predetermined target treatment pressure.

[0021] In one embodiment of the invention, the stepwise pressurization strategy model operates based on acquired individual physiological characteristic parameters and target treatment pressure. Baseline heart rate variability is input to the pressure tolerance analysis unit of the stepwise pressurization strategy model. This unit calculates the user's initial pressure tolerance threshold using an internal algorithm. For example, the pressure tolerance analysis unit can compare the baseline heart rate variability with a preset mapping table and output a pressure tolerance threshold value in kilopascals. Baseline respiratory rate is input to the respiratory adaptation analysis unit of the stepwise pressurization strategy model. Based on this baseline value, the respiratory adaptation analysis unit calculates a respiratory pressure load reference coefficient, a dimensionless proportionality coefficient used to quantify the expected load of the user's respiratory system on pressure changes. The body surface area is input into the calculation unit of the stepped pressurization strategy model. The calculation unit determines the initial stage duration of the pressure increase phase based on the body surface area. In a specific example, the initial stage duration for a user with a body surface area of ​​1.6 square meters is calculated to be 180 seconds, while the initial stage duration for a user with a body surface area of ​​2.0 square meters is calculated to be 150 seconds. This demonstrates the negative correlation between the initial stage duration and the body surface area.

[0022] In some embodiments, the integrated calculation unit of the stepped pressurization strategy model receives the target therapeutic pressure, the initial pressure tolerance threshold, the respiratory pressure load reference factor, and the duration of the initial phase. The integrated calculation unit first determines the total number of pressure increment phases based on the difference between the target therapeutic pressure and the initial pressure tolerance threshold. One formula for calculating the total number of phases is as follows: Where: characters Represents the total number of calculated pressure increase stages, characters Represents the target therapeutic stress value, character Represents the initial pressure tolerance threshold, character Represents a preset pressure span constant, symbol This indicates rounding up. For example, the target therapeutic pressure value is 250 kPa, the initial pressure tolerance threshold is 50 kPa, and the preset pressure span constant is... If the pressure is 60 kPa, then the number of stages is calculated. The pressure ramping process is divided into four phases. The integrated calculation unit assigns an initial pressure ramping rate to each phase based on the respiratory pressure load reference coefficient, with phases having higher reference coefficients receiving lower initial pressure ramping rates. The integrated calculation unit uses the duration of the initial phase as the initial phase duration for the first pressure ramping phase, and, combined with the total number of phases and the total target pressure difference, calculates the initial phase duration for subsequent pressure ramping phases, thus forming a preliminary time plan for the pressurization phase.

[0023] In practice, real-time acquisition of dynamic physiological monitoring data is accomplished using dedicated sensors. (See also...) Figure 2 The system continuously collects the voltage waveform of the user's electrocardiogram (ECG) signal through a bioelectrical signal sensor worn on the user's body. It then analyzes the continuously collected ECG voltage waveforms in real time to calculate the variability of the time interval between adjacent heartbeat cycles. This variability is defined as real-time heart rate variability. A flow rate sensor installed in the oxygen mask or breathing tubing monitors the flow rate signal of the user's breathing air. The system processes the monitored flow rate signal in real time to identify the duration of a single respiratory cycle and calculates the real-time respiratory rate based on the number of respiratory cycles per unit time. For example, if 5 complete respiratory cycles are identified within 10 seconds, the real-time respiratory rate is calculated to be 30 breaths per minute.

[0024] The specific calculations of the stepped pressurization strategy model can be illustrated using an example scenario. In implementation, user A's individual physiological characteristics are: baseline heart rate variability of 65 milliseconds, baseline respiratory rate of 16 breaths per minute, and body surface area of ​​1.8 square meters. The preset target treatment pressure is 280 kPa. The pressure tolerance analysis unit of the stepped pressurization strategy model receives the baseline heart rate variability of 65 milliseconds and, by querying the internal mapping relationship, outputs an initial pressure tolerance threshold of 55 kPa. The respiratory adaptation analysis unit receives the baseline respiratory rate of 16 breaths per minute and, through internal calculation, obtains a respiratory pressure load reference coefficient of 0.8. Based on the body surface area of ​​1.8 square meters, the calculation unit queries the internal relationship table to determine the initial stage duration as 170 seconds. The comprehensive calculation unit receives the target treatment pressure of 280 kPa, the initial pressure tolerance threshold of 55 kPa, the respiratory pressure load reference coefficient of 0.8, and the initial stage duration of 170 seconds. The comprehensive calculation unit uses the aforementioned formula to calculate the total number of pressure increment stages, assuming a preset pressure span constant. If the pressure is 65 kPa, then the number of stages is calculated. The value is 4. Based on a respiratory pressure load reference factor of 0.8, the integrated calculation unit assigns initial pressure increment rates to the four pressure increment stages. Since 0.8 is a moderate reference factor, the assigned initial rates are 18 kPa, 20 kPa, 22 kPa, and 24 kPa per minute, respectively. The integrated calculation unit uses 170 seconds as the initial stage duration for the first stage and, combining the total pressure difference and the number of stages, calculates the initial stage durations for the second, third, and fourth stages to be 150 seconds, 140 seconds, and 130 seconds, respectively. This generates a complete set of pressurization rates and a preliminary time plan, including the target pressure sub-values ​​for each stage, the initial pressure increment rate, and the initial stage duration.

[0025] In one embodiment of the invention, the dynamic adjustment process during the pressure escalation phase is based on a continuous comparison between real-time acquired dynamic physiological monitoring data and baseline values ​​stored in the stepwise pressurization strategy model. During any pressure escalation phase, the system continuously receives real-time heart rate variability and real-time respiratory rate from sensors. The system compares the received real-time heart rate variability with the pre-stored baseline heart rate variability value in the stepwise pressurization strategy model to calculate a heart rate variability deviation. Similarly, the system compares the received real-time respiratory rate with the pre-stored baseline respiratory rate value in the stepwise pressurization strategy model to calculate a respiratory rate deviation. The calculated heart rate variability deviation and respiratory rate deviation are input in real-time to a preset rate adjustment decision logic, which has a pre-defined rate adjustment threshold.

[0026] In some embodiments, the rate adjustment decision logic assesses the input heart rate variability deviation and respiratory rate deviation. When the absolute value of either the heart rate variability deviation or the respiratory rate deviation exceeds the rate adjustment threshold, the rate adjustment decision logic generates a deceleration and pressurization command. Based on the magnitude of the deviation exceeding the threshold, the deceleration and pressurization command instructs the system to reduce the initial pressure increment rate of the current pressure increment phase by one or more preset deceleration steps; for example, one deceleration step corresponds to a pressurization rate decrease of 2 kPa per minute. When the absolute values ​​of both the heart rate variability deviation and the respiratory rate deviation do not exceed the rate adjustment threshold, the rate adjustment decision logic queries a preset rate fine-tuning lookup table based on the specific values ​​of the heart rate variability deviation and the respiratory rate deviation. The rate fine-tuning lookup table stores the correction increments for pressure increment rates corresponding to different combinations of deviations. The system fine-tunes the initial pressure increment rate of the current phase by increasing or decreasing based on the obtained correction increments.

[0027] In practical implementation, a specific pressure ramping scenario can be used as an example. Assume that during a certain pressure ramping phase, the user's baseline heart rate variability is 60 milliseconds, and the baseline respiratory rate is 18 breaths per minute. The initial pressure ramping rate for this phase is set to 20 kPa. At 50 seconds after the start of ramping, the system collects real-time heart rate variability of 55 milliseconds and real-time respiratory rate of 22 breaths per minute. The system calculates the heart rate variability deviation as -8.3% and the respiratory rate deviation as +22.2%. The preset rate adjustment threshold is 15%. At this point, the absolute value of the respiratory rate deviation of +22.2% exceeds the 15% rate adjustment threshold, and the rate adjustment decision logic generates a deceleration ramping command. Since it exceeds the threshold by 7.2 percentage points, according to preset rules, the system reduces the current pressure ramping rate from the initial 20 kPa to 16 kPa, a decrease of two deceleration steps. If, during subsequent monitoring, the heart rate variability deviation is -5% and the respiratory rate deviation is +10%, with neither absolute value exceeding the 15% threshold, the rate adjustment decision logic will query the rate fine-tuning reference table. The query results show that when the heart rate variability deviation is -5% and the respiratory rate deviation is +10%, the corresponding correction increment is -0.5 kPa per minute. Based on this result, the system will then fine-tune the current pressure increase rate from 16 kPa per minute to 15.5 kPa per minute.

[0028] It is understandable that the rate adjustment decision logic also includes an advanced control mechanism for pausing and resuming pressurization. The rate adjustment decision logic pre-sets a pressurization pause threshold whose value is greater than the rate adjustment threshold. During any pressurization phase of pressure increase, the system compares the absolute values ​​of heart rate variability deviation and respiratory rate deviation with the pressurization pause threshold in real time. When the absolute value of either heart rate variability deviation or respiratory rate deviation reaches or exceeds the pressurization pause threshold, the rate adjustment decision logic immediately generates a highest-priority pressurization pause command. In response to the pressurization pause command, the system immediately stops all pressurization operations in the hyperbaric oxygen chamber and maintains the current gas pressure value within the chamber unchanged.

[0029] In some embodiments, the resumption process after a pause follows preset logic. During the pause in pressurization, the system continuously monitors the user's dynamic physiological data and continuously calculates the deviation of heart rate variability and respiratory rate. When the absolute values ​​of both heart rate variability and respiratory rate deviation fall below the rate adjustment threshold, and this state remains stable for a preset period of time, such as 30 seconds, the rate adjustment decision logic generates a resumption pressurization command. In response to the resumption pressurization command, the system restarts the pressurization process of the current pressure increment phase at an initial pressure increment rate lower than that before the pause. For example, if the pressure increment rate before the pause was 18 kPa, the resumption rate after the pause might be 15 kPa.

[0030] Optionally, the rate adjustment decision logic can use a comprehensive deviation index to determine whether fine-tuning is needed. One formula for calculating the comprehensive deviation is as follows: Where: characters Represents the calculated overall deviation, character Represents the deviation of heart rate variability, character Represents the deviation of respiratory rate, character and These are the preset weighting coefficients assigned to the deviations of heart rate variability and respiratory rate. Overall deviation. It is compared with a preset fine-tuning threshold to query the rate fine-tuning lookup table or trigger other adjustment logic.

[0031] Optionally, the specific values ​​of the pause-inflation threshold and rate adjustment threshold can be set using clinical data. For example, the rate adjustment threshold can be set to a 15% deviation from the baseline, and the pause-inflation threshold to a 25% deviation from the baseline. When the heart rate variability deviation reaches -26%, since its absolute value of 26% exceeds the 25% pause-inflation threshold, the rate adjustment decision logic will immediately generate a pause-inflation command, interrupting the inflation process. During pressure maintenance, if the system detects that the heart rate variability deviation recovers to -12% after 45 seconds and the respiratory rate deviation recovers to +8%, with both absolute values ​​below the 15% rate adjustment threshold and remaining within this range for the subsequent 30 seconds of stability, the rate adjustment decision logic will generate a resume-inflation command, and the system will restart inflation at a preset, reduced rate.

[0032] In one embodiment of the present invention, the phased adaptation assessment step is automatically triggered when the gas pressure inside the medical hyperbaric oxygen chamber reaches the preset target pressure sub-value of the current pressure increment stage. The system controls the pressure regulating valve to maintain a constant gas pressure inside the chamber and initiates the phased adaptation assessment process. Under constant gas pressure, the system collects heart rate variability and respiratory rate stability data of the user over a specific time period using bioelectrical signal sensors and flow rate sensors. For example, the system sets the collection time to 180 seconds, continuously recording the instantaneous value sequence of heart rate variability and respiratory rate during these 180 seconds. The collected heart rate variability and respiratory rate stability data are input into the adaptation assessment module of the stepped pressurization strategy model. The adaptation assessment module processes the input data and calculates a comprehensive adaptation index. The adaptation assessment module has a preset adaptation threshold for entering the next stage; this adaptation threshold is a calibrated numerical constant. The system compares the calculated comprehensive adaptation index with the adaptation threshold for entering the next stage. When the comprehensive adaptation index is greater than or equal to the threshold, the adaptation assessment module generates a control command allowing entry into the next stage. This command is sent to the oxygen chamber main controller, which then initiates the pressurization procedure for the next pressure increment stage. When the comprehensive adaptation index is less than the threshold, the adaptation assessment module generates a control command to extend the adaptation time for this stage. In response, the system extends the constant pressure duration by an integer multiple of the specified duration, while maintaining the current gas pressure value, for example, by another 180 seconds. After the extended period, the entire process from collecting stability data to comparing the comprehensive adaptation index is re-executed. This process is repeated until the latest calculated comprehensive adaptation index meets the condition of being greater than or equal to the adaptation threshold for entering the next stage, or the cumulative extension time reaches a preset maximum extension time limit, for example, a preset maximum extension time of 900 seconds.

[0033] In some embodiments, the adaptability assessment module can calculate the comprehensive adaptability index based on a preset formula, which transforms heart rate variability stability data and respiratory rate stability data into a single evaluation index. One formula for calculating the comprehensive adaptability index is as follows: Where: characters Represents the calculated overall fitness index, character This represents a heart rate stability index derived from statistical analysis of heart rate variability stationarity data over a specific duration. This represents a respiratory stability index derived from statistical analysis of respiratory rate stability data over a specific time period. and characters These are the preset weighting coefficients assigned to the heart rate stability index and the respiratory stability index, respectively. Heart rate stability index The calculation can be performed by taking the reciprocal of the standard deviation of all heart rate variability values ​​collected within a specific time period, and the respiratory stability index. The calculation can be performed by taking the reciprocal of the standard deviation of all respiratory rate values ​​collected within a specific time period. Weighting coefficient. and satisfy Relationships, for example Set to 0.6. Set it to 0.4. The adaptation threshold can be set to 1.0. Assuming a 180-second acquisition window, the standard deviation of heart rate variability is calculated to be 12 milliseconds, its reciprocal of which is approximately 0.0833, and the standard deviation of respiratory rate is 2.5 breaths per minute, its reciprocal of which is approximately 0.4. Substituting these values ​​into the formula, the overall adaptation index is calculated. The calculated overall adaptation index of 0.21 is much lower than the adaptation threshold of 1.0, therefore the adaptation assessment module generates an instruction to extend the adaptation time of this phase. The system extends the current pressure maintenance phase by another 180 seconds. After the second 180 seconds, data is collected and recalculated. If the standard deviation of heart rate variability decreases to 8 milliseconds and the standard deviation of respiratory rate decreases to 2 breaths per minute in the second calculation, then the heart rate stability index... It changed to 0.125, the respiratory stability index. The overall fitness index is changed to 0.5. If the overall adaptation index of 0.275 is still less than the adaptation threshold of 1.0, the system will extend the adaptation time by another 180 seconds. This process will repeat until the overall adaptation index calculated after a certain evaluation cycle reaches or exceeds 1.0, or the total extension time reaches the preset upper limit of 900 seconds.

[0034] It is understandable that the values ​​of the adaptation threshold and the maximum extension time need to be set based on clinical experience and safety guidelines. A higher adaptation threshold means that the conditions for entering the next stage are more stringent, and a maximum extension time of 900 seconds means that the system can perform a maximum of five consecutive assessment cycles during a single stress plateau. In practice, when the system re-collects stationarity data after each extension of the adaptation time, the specific duration of the data collection can be the same as the initial assessment duration, for example, 180 seconds each time. The adaptation assessment module independently calculates the comprehensive adaptation index in each assessment cycle and compares it with the same adaptation threshold.

[0035] Optionally, the calculation method for the comprehensive adaptation index is not limited to the weighted linear combination mentioned above. The adaptation assessment module can use other multi-parameter fusion algorithms, such as inputting heart rate variability stability data and respiratory rate stability data into a trained neural network model, which can then directly output the comprehensive adaptation index. The adaptation threshold for entering the next stage can also not be a fixed value, but a value that is dynamically adjusted based on the current stress stage ordinal number or the target stress sub-value. For example, a stricter adaptation threshold can be used in higher stress stages.

[0036] See Figure 3 In the phased adaptation assessment process of the step-by-step pressurization method in medical hyperbaric oxygen chambers, the dynamic changes of heart rate stability index and respiratory stability index directly reflect the user's physiological adaptation process to the current pressure plateau. The figure presents the changing trends of the two types of stability indexes over the assessment period using a dual Y-axis: the left Y-axis corresponds to the heart rate stability index (1 / standard deviation), and the right Y-axis corresponds to the respiratory stability index (1 / standard deviation). Higher index values ​​indicate smaller physiological signal fluctuations and a more stable adaptation state. The horizontal axis represents the cumulative assessment duration, including the initial assessment (180s) and four extended assessments (360s, 540s, 720s, 900s). The data trends show that in the initial stage (180s), both the heart rate stability index and respiratory stability index are at their lowest levels, approximately 0.08 and 0.4 respectively, indicating that when the user first enters the current pressure plateau, the physiological signal fluctuations are relatively large, and the adaptation state is not yet stable. Extended assessment phase (360s~900s): Both types of stability indicators showed a monotonically increasing trend with the extension of assessment time, and the rate of increase gradually accelerated, reaching a peak simultaneously at 900s (heart rate stability indicator approximately 0.5, respiratory stability indicator approximately 1.25), indicating that a sustained constant pressure state can gradually reduce the variability of the user's physiological signals and improve adaptation stability. Coordinated change characteristics: The trends of change in heart rate stability indicators and respiratory stability indicators were highly synchronized, with no significant divergence, reflecting the coordinated regulatory characteristics of the cardiovascular and respiratory systems during the pressure adaptation process, and also verifying the rationality of using a weighted fusion of the two types of indicators for the comprehensive adaptation index. The figure provides a quantitative basis for the decision-making of the phased adaptation assessment module: when the two types of stability indicators increase to the point where the corresponding comprehensive adaptation index meets the preset threshold, it can be determined that the user has fully adapted to the current pressure plateau period, allowing entry into the next pressure increment phase; if the indicator growth is slow or does not reach the threshold, the current constant pressure time needs to be extended until the conditions are met or the maximum extension time limit (900s) is reached.

[0037] In one embodiment of the present invention, the adaptive assessment module performs statistical analysis on the heart rate variability stability data collected within a specific time period, calculates the ratio of the variance to the mean of the heart rate variability, and defines the result as the heart rate stability coefficient. The adaptive assessment module also performs statistical analysis on the respiratory rate stability data collected within a specific time period, calculates the ratio of the variance to the mean of the respiratory rate, and defines the result as the respiratory stability coefficient. The user's heart rate variability stability coefficient and respiratory rate stability coefficient at the end of the previous pressure increase phase are extracted from the system's stored historical records of phased pressurization. The adaptive assessment module calculates the rate of change of the heart rate stability coefficient in the current phase relative to the heart rate stability coefficient at the end of the previous phase, and defines the rate of change as the heart rate adaptive increment. The adaptive assessment module calculates the rate of change of the respiratory stability coefficient in the current phase relative to the respiratory stability coefficient at the end of the previous phase, and defines the rate of change as the respiratory adaptive increment. The adaptive assessment module performs a weighted summation of the heart rate stability coefficient, respiratory stability coefficient, heart rate adaptive increment, and respiratory adaptive increment; the result of the weighted summation is the comprehensive adaptation index.

[0038] In some embodiments, the specific formula for calculating the comprehensive fitness index is as follows: Where: characters Represents the calculated overall fitness index; character Represents the heart rate stability coefficient; character Represents the respiratory stability coefficient; character Represents adaptive heart rate increments; character Represents respiratory adaptation increment; character ,character ,character ,character These are the preset weighting coefficients assigned to the heart rate stability coefficient, respiratory stability coefficient, heart rate adaptive increment, and respiratory adaptive increment. Weighting coefficients , , , The sum is 1. See Table 1 for an example of a possible weighting coefficient allocation.

[0039] Table 1: Weighting Coefficient Table It's understandable that the above calculation process can be clarified with specific examples. Assume that at the end of the second-stage stress plateau period (i.e., the historical record point), the calculated heart rate stability coefficient is 0.08 and the respiratory stability coefficient is 0.12. In the current assessment of the third-stage stress plateau period, the heart rate stability coefficient calculated based on data collected over 180 seconds is 0.10 and the respiratory stability coefficient is 0.15. Therefore, the adaptive heart rate increment... Calculated as (i.e., 25%), respiratory adaptation increment Calculated as (i.e., 25%). Using the example weighting coefficients in the table above, the overall fitness index is calculated. The calculated overall fitness index It will be compared with the preset adaptation threshold for entering the next stage to determine whether to enter the fourth pressurization stage.

[0040] In practice, dynamic safety measures are independent of and take precedence over any adjustment logic. The system establishes clear safety ranges for dynamic physiological monitoring data, including upper and lower limits for heart rate variability and respiratory rate. These safety range values ​​are based on clinical safety guidelines; for example, the lower safety limit for heart rate variability is 20 milliseconds, and the upper safety limit is 150 milliseconds; the lower safety limit for respiratory rate is 10 breaths per minute, and the upper safety limit is 30 breaths per minute. Throughout the entire process from initiating pressurization to reaching the target therapeutic pressure, the system continuously compares real-time heart rate variability and real-time respiratory rate with their respective safety ranges. When either real-time heart rate variability or real-time respiratory rate exceeds its corresponding safety range, the system immediately generates a highest-priority safety intervention instruction. This safety intervention instruction has higher priority than any instruction generated by the rate adjustment decision logic to adjust the pressure increment rate. In response to a safety intervention command, the system immediately stops the current pressurization or constant pressure process, regardless of the stage, and reduces the gas pressure inside the medical hyperbaric oxygen chamber to a preset safe pressure threshold at a preset safe decompression rate. At the same time, it activates an audible and visual alarm device to alert the operators outside the chamber.

[0041] Optionally, the safe decompression rate and safe pressure threshold are preset fixed parameters. For example, the safe decompression rate is set to 30 kPa per minute, and the safe pressure threshold is set to 101.3 kPa, equal to the current ambient atmospheric pressure. Assuming user B's real-time heart rate variability continuously decreases during pressurization, reaching 18 milliseconds at a certain moment, this value is below the preset 20 milliseconds safe lower limit, and the system immediately generates a safety intervention command. The system controls the pressure regulating valve to stop air intake and begin venting, reducing the cabin pressure from the current 180 kPa to 101.3 kPa at a rate of 30 kPa per minute. Simultaneously, the red alarm light on the control panel flashes and an alarm sounds. In some embodiments, the boundary values ​​of the safe range can be fine-tuned according to the user's individual physiological characteristics, for example, setting 50% of the baseline heart rate variability as the safe lower limit and 200% of the baseline respiratory rate as the safe upper limit. After the safety intervention command is triggered, the system locks the control interface until the operator manually confirms and resets the alarm status.

[0042] Understandably, the dynamic safety mechanism provides an independent protective layer based on absolute safety boundaries throughout the pressurization process. Real-time heart rate variability exceeding the lower limit may indicate excessive suppression of autonomic nervous function, while real-time respiratory rate exceeding the upper limit may indicate respiratory distress. Once such conditions are detected, the system no longer follows a gradual adjustment or assessment process but instead executes the most direct abort and decompression operation to ensure user safety. The activation of audible and visual alarms ensures that external monitoring personnel can immediately detect abnormalities and take further action. The setting of safe pressure thresholds ensures that the cabin pressure can quickly recover to a safe level equal to the external pressure, creating conditions for emergency response.

[0043] See Figure 4 During the stepwise pressurization process in a medical hyperbaric oxygen chamber, the dynamic correlation between chamber pressure and physiological indicators can be quantitatively analyzed using multi-dimensional time-series curves. The figure uses pressurization duration as the horizontal axis, simultaneously presenting the time-series changes of three core variables: Chamber pressure (solid line): Employing a stepwise increasing strategy, starting from an initial 101.3 kPa (ambient atmospheric pressure), it gradually increases at a segmented constant rate, reaching and stabilizing at the target therapeutic pressure of 160 kPa after approximately 25 minutes, reflecting a phased and controllable pressurization logic. Heart rate variability (dashed line): Measured in milliseconds, it exhibits significant fluctuations with increasing pressure in the initial stage of pressurization, reflecting the autonomic nervous system's stress response to pressure load; during the pressure plateau period (e.g., after 10-20 minutes, and 25 minutes), the fluctuation amplitude gradually narrows, reflecting the body's adaptation process to the pressure environment. Respiratory rate (dotted line): Measured in breaths per minute, it exhibits synchronous fluctuations with heart rate variability, with increased volatility during rapid pressure increases (e.g., 0-10 minutes, 20-25 minutes), indicating that the respiratory and cardiovascular systems jointly participate in the stress response. From the coordinated changes in the curves: Pressure increase phase: When the chamber pressure increases rapidly, the fluctuations in heart rate variability and respiratory rate amplify synchronously, indicating that the rate of pressure change is a key trigger for physiological stress. Pressure plateau phase: During the period when the chamber pressure remains constant, the fluctuations in both physiological indicators gradually decrease, verifying the effectiveness of the phased constant pressure adaptation mechanism and providing a direct basis for the "inter-phase constant pressure assessment" in the stepwise pressurization strategy. Target pressure maintenance phase: After 25 minutes, the chamber pressure stabilizes at 160 kPa, and both heart rate variability and respiratory rate enter a low-amplitude, stable range, indicating that the body has gradually adapted to the target treatment pressure environment. The figure visually reveals the quantitative correlation between stepwise pressurization rate, phased constant pressure adaptation, and physiological indicator stability, providing visual support for optimizing personalized pressurization strategies and defining safety boundaries for medical hyperbaric oxygen chambers.

[0044] In one embodiment of the invention, the physiological state monitoring and reassessment steps during the pressure maintenance phase are automatically executed after the gas pressure in the hyperbaric oxygen chamber reaches and stabilizes at the target treatment pressure. Throughout the entire period when the gas pressure in the hyperbaric oxygen chamber stabilizes at the target treatment pressure, the system collects and records the user's heart rate variability (HRV) and respiratory rate (RR) sequences using continuously operating bioelectrical signal sensors and flow rate sensors. The system calculates the average HRV data recorded during the maintenance phase to obtain the average HRV for the maintenance phase, and calculates the average RRR data recorded during the maintenance phase to obtain the average RRR for the maintenance phase. The system compares the calculated average HRV and RRR values ​​during the maintenance phase with the baseline HRV and RRR values ​​initially acquired as individual physiological characteristic parameters. Based on the comparison results, the system assesses the user's overall adaptation level to the target treatment pressure and generates a structured adaptation level assessment report.

[0045] In some embodiments, the adaptation level assessment report includes specific numerical comparisons and a comprehensive evaluation value. A formula for calculating the overall adaptation level comprehensive evaluation value is expressed as follows: Where: characters This represents the overall adaptation level as a comprehensive evaluation value; the closer the value is to 1, the higher the adaptation level. Represents the mean heart rate variability during the maintenance phase; character Represents the baseline value of heart rate variability among individual physiological characteristic parameters; character Represents the average respiratory rate during the maintenance phase; character Represents the baseline value of respiratory rate among individual physiological characteristic parameters; character and characters These are the weighting coefficients for differences in heart rate variability and respiratory rate, respectively, and they satisfy the following conditions: The adaptation level assessment report records the mean heart rate variability during the maintenance phase, the mean respiratory rate during the maintenance phase, the baseline heart rate variability, the baseline respiratory rate, the calculated overall adaptation level assessment value, and a description of the adaptation level level.

[0046] In practical implementation, a complete treatment process example can be used for illustration. User C's individual physiological characteristics are: baseline heart rate variability of 70 milliseconds and baseline respiratory rate of 16 breaths per minute. The target treatment pressure for this treatment is 250 kPa. During the 20 minutes that the pressure reaches and is maintained at 250 kPa, the system continuously collects physiological data. The calculated average heart rate variability during the maintenance phase is 72 milliseconds, and the average respiratory rate during the maintenance phase is 17 breaths per minute. Weighting coefficients are then set. , Substitute the values ​​into the formula to calculate the overall adaptation level comprehensive evaluation value: The system-generated adaptation level assessment report will include an average heart rate variability of 72 milliseconds, an average respiratory rate of 17 breaths / min, a baseline heart rate variability of 70 milliseconds, a baseline respiratory rate of 16 breaths / min, an overall adaptation level score of 0.96, and a description of a "well adapted" rating. The report indicates that the user's physiological state under target stress changes only slightly compared to the baseline state, and the overall adaptation level is high.

[0047] Understandably, the system performs data integration and storage after treatment. The adaptation level assessment report, dynamic physiological monitoring data for each pressure escalation phase, the final adjusted pressurization rate set, and the results of all interim adaptation assessments are packaged together and associated with a unique identifier for this treatment session, stored as a complete record of this pressurization treatment process. This complete record is stored in a structured data format, including, for example, a sequence of physiological data with timestamps, the actual pressurization rate and duration used for each pressure escalation phase, the comprehensive adaptation index and decision results for each interim adaptation assessment, and the final adaptation level assessment report.

[0048] Optionally, the stored complete records are used to subsequently update the internal parameters of the stepwise compression strategy model. The model update process can be performed offline, analyzing a large number of complete treatment records to uncover the correlation between individual physiological parameters, actual compression process data, and the final adaptation level. For example, the system can analyze multiple successful treatment records with similar baseline heart rate variability and respiratory rate values, calculating the statistical characteristics of the set of actual compression rates used, to optimize the rules in the stepwise compression strategy model for assigning initial pressure increment rates to similar users. As another example, the system can analyze the relationship between interim adaptation assessment results and the final overall adaptation level to correct the adaptation threshold for entering the next stage in the adaptation assessment module, or adjust the weighting coefficients in the comprehensive adaptation index calculation formula.

[0049] In some embodiments, the complete record's data structure comprises multiple data blocks. The first block stores session metadata such as the user identifier, treatment date, and target treatment pressure. The second block stores, in chronological order, dynamic physiological monitoring data from the start of pressurization to the end of pressure maintenance, including timestamps, real-time heart rate variability, and real-time respiratory rate. The third block stores pressurization process data, including the target pressure sub-value for each pressure increment phase, the initial pressure increment rate, the dynamically adjusted actual pressurization rate, and the start and end times of each phase. The fourth block stores phased adaptation assessment data, including stability data collected at each assessment, the calculated comprehensive adaptation index, and the assessment decision results. The fifth block stores the final adaptation level assessment report. These blocks are linked by a unified session identifier, forming a complete data entity.

[0050] Understandingly, storing complete treatment process records provides a data foundation for the continuous optimization of the stepwise pressurization strategy model. The model can utilize successful and unsuccessful cases from historical data for machine learning training, thereby making the generated pressurization strategies more personalized, safe, and effective. The adaptation level assessment report is not only a summary of a single treatment session, but its data itself also serves as an important feedback signal for model optimization. The adjustment records of the pressurization rate set reflect the user's dynamic responses during actual treatment; this information, compared to preset model parameters, better reflects an individual's true tolerance and adaptation to pressure changes.

[0051] See Figure 5The figure presents the dynamic fluctuation characteristics of heart rate variability and respiratory rate during the 20-minute maintenance period, providing a quantitative basis for assessing user adaptation levels. The figure uses a dual-axis coordinate system to represent the two core physiological indicators: the left vertical axis represents heart rate variability (ms), with the dotted line representing real-time heart rate variability and the dotted line representing the baseline heart rate variability (70ms); the right vertical axis represents respiratory rate (breaths / min), with the boxed line representing real-time respiratory rate and the dotted line representing the baseline respiratory rate (16 breaths / min); the horizontal axis represents pressure maintenance time (minutes), covering the complete maintenance phase from 0 to 20 minutes. The fluctuation trends show the following: Heart rate variability: It fluctuated slightly around the baseline value of 70ms, ranging from 69.5 to 74ms, with the fluctuation range controlled within ±5.7%, reflecting the stability of the user's autonomic nervous system regulation under target pressure; Respiratory rate: It fluctuated around the baseline value of 16 breaths / min, ranging from 15 to 18.5 breaths / min, with the fluctuation range controlled within ±15.6%, and the respiratory rhythm did not show significant disturbances; Indicator synergy: The peak and trough values ​​of the two indicators showed weak temporal synchrony, reflecting the coordinated regulatory response of the cardiovascular and respiratory systems under pressure, and no extreme fluctuations deviating from the baseline state were observed. The figure provides intuitive time-series evidence for the assessment of adaptation level during the pressure maintenance phase: the average heart rate variability was approximately 72ms, and the average respiratory rate was approximately 17 breaths / min. The slight deviation from the baseline values ​​verifies the user's good tolerance to the target treatment pressure, which can directly support the subsequent calculation of the comprehensive adaptation index and the determination of the adaptation level.

[0052] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A stepped pressurization method applicable to medical hyperbaric oxygen chambers, characterized in that, include: The user's individual physiological characteristics parameters are obtained, including the user's baseline heart rate variability, baseline respiratory rate, and body surface area. Receive and analyze the preset target treatment pressure, which is the final gas pressure value that needs to be achieved in the medical hyperbaric oxygen chamber after the pressurization operation is completed; Based on the individual physiological characteristic parameters and the target treatment pressure, a set of pressure increase rates in stages is generated through a preset step-by-step pressure increase strategy model. The set of pressure increase rates includes the pressure increase rate of multiple pressure increase stages and the target pressure sub-value of the corresponding stage. After the pressurization operation is started, dynamic physiological monitoring data of the user in the medical hyperbaric oxygen chamber is collected in real time. The dynamic physiological monitoring data includes real-time heart rate variability and real-time respiratory rate. During each pressure increment stage, the pressure increment rate of the current stage is dynamically adjusted based on the dynamic physiological monitoring data. When the gas pressure inside the medical hyperbaric oxygen chamber reaches the target pressure value, the next pressure increment stage begins, until the target treatment pressure is reached.

2. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 1, characterized in that, The step of generating a set of phased pressurization rates based on the individual physiological characteristic parameters and the target treatment pressure through a preset stepped pressurization strategy model includes: The baseline heart rate variability is input into the pressure tolerance analysis unit of the stepped pressurization strategy model to calculate the user's initial pressure tolerance threshold. The baseline respiratory rate value is input into the respiratory adaptation analysis unit of the stepped pressurization strategy model to calculate the user's respiratory pressure load reference coefficient. Based on the body surface area, the initial stage duration of the pressure increase phase is determined in the calculation unit of the stepped pressurization strategy model, and the initial stage duration is negatively correlated with the body surface area. The target treatment pressure, the initial pressure tolerance threshold, the respiratory pressure load reference coefficient, and the initial phase duration are all input into the integrated calculation unit of the stepwise pressurization strategy model; The integrated calculation unit determines the total number of pressure escalation stages based on the difference between the target treatment pressure and the initial pressure tolerance threshold. The integrated calculation unit assigns different initial pressure increment rates to different pressure increment stages based on the respiratory pressure load reference coefficient, wherein the higher the respiratory pressure load reference coefficient, the lower the initial pressure increment rate assigned to the stage. The integrated calculation unit uses the initial stage duration as the initial stage duration of the first pressure increase stage, and combines it with the total number of stages and the total target pressure to calculate the initial stage duration of subsequent pressure increase stages, thus forming a preliminary time plan for the pressure increase stage.

3. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 2, characterized in that, The real-time acquisition of dynamic physiological monitoring data of users inside the medical hyperbaric oxygen chamber includes: The voltage waveform of the user's electrocardiogram signal is continuously collected by a bioelectrical signal sensor worn on the user's body. The voltage waveform of continuously acquired electrocardiogram signals is analyzed in real time, and the degree of variation of the time interval between adjacent heartbeat cycles is calculated as the real-time heart rate variability. The flow rate signal of the user's breathing airflow is monitored by a flow rate sensor installed in the oxygen mask or breathing circuit. The monitored flow rate signal is processed in real time to identify the duration of a single respiratory cycle, and the real-time respiratory rate is calculated based on the number of respiratory cycles per unit time.

4. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 3, characterized in that, During the pressurization process at each pressure increment stage, the pressure increment rate for the current stage is dynamically adjusted based on the dynamic physiological monitoring data, including: During any pressure increase phase, the real-time heart rate variability and the real-time respiratory rate are continuously received; The real-time heart rate variability received at the current stage is compared with the baseline heart rate variability value of the stepped pressurization strategy model to calculate the heart rate variability deviation. The real-time respiratory rate received at the current stage is compared with the baseline respiratory rate value in the stepped pressurization strategy model to calculate the respiratory rate deviation. The calculated deviations in heart rate variability and respiratory rate are input into the preset rate adjustment decision logic. The rate adjustment decision logic is preset with a rate adjustment threshold. When the absolute value of either the heart rate variability deviation or the respiratory rate deviation exceeds the rate adjustment threshold, the rate adjustment decision logic generates a deceleration and pressurization command, and adjusts the initial pressure increase rate of the current pressure increase phase by one or more preset deceleration steps according to the magnitude of the deviation exceeding the threshold. When the absolute values ​​of the heart rate variability deviation and the respiratory rate deviation do not exceed the rate adjustment threshold, the rate adjustment decision logic queries a preset rate fine-tuning reference table based on the values ​​of the heart rate variability deviation and the respiratory rate deviation to obtain the correction increment of the pressure increase rate corresponding to the current stage, and fine-tunes the initial pressure increase rate of the current stage based on the correction increment.

5. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 4, characterized in that, The rate adjustment decision logic also generates a pause command based on the heart rate variability deviation and respiratory rate deviation, including: The rate adjustment decision logic has a preset pause pressure threshold, which is greater than the rate adjustment threshold. During any pressure increase phase, the absolute values ​​of the heart rate variability deviation and respiratory rate deviation are compared in real time with the magnitude of the pressure cessation threshold. When the absolute value of either the heart rate variability deviation or the respiratory rate deviation reaches or exceeds the pause pressurization threshold, the rate adjustment decision logic immediately generates a pause pressurization command. In response to the aforementioned pause pressurization command, the pressurization operation of the medical hyperbaric oxygen chamber is immediately stopped, and the current gas pressure value inside the medical hyperbaric oxygen chamber is maintained. During the pause in pressurization, the dynamic physiological monitoring data is continuously monitored. When the absolute values ​​of the heart rate variability deviation and respiratory rate deviation both fall below the rate adjustment threshold and remain stable for a preset period of time, the rate adjustment decision logic generates a command to resume pressurization. In response to the pressurization resumption command, the pressurization process of the current pressure increment phase is restarted at an initial pressure increment rate lower than the pressure before the pause.

6. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 5, characterized in that, Before moving to the next stage of escalating stress, the process also includes a phased adaptation assessment of the user, including: During the current pressure increase phase, when the gas pressure inside the medical hyperbaric oxygen chamber reaches the target pressure sub-value, the gas pressure is kept constant, and the phased adaptation assessment process is initiated. Under constant gas pressure, collect data on the stability of the user's heart rate variability and respiratory rate over a specific time period. The collected data on the stability of the user's heart rate variability and the stability of the user's respiratory rate are input into the adaptive evaluation module of the stepped pressurization strategy model. The adaptability assessment module calculates a comprehensive adaptability index based on the stability data of the user's heart rate variability and the stability data of the user's respiratory rate. The adaptive assessment module has a preset adaptation threshold for entering the next stage; Compare the comprehensive adaptation index with the adaptation threshold for entering the next stage; When the comprehensive adaptation index is greater than or equal to the adaptation threshold for entering the next stage, the adaptation assessment module generates an instruction to allow entry into the next stage; When the comprehensive adaptation index is less than the adaptation threshold for entering the next stage, the adaptation assessment module generates an instruction to extend the adaptation time of the current stage. In response to the instruction to extend the adaptation time of this stage, the time is extended by an integer multiple of the specific duration under the current gas pressure, and the process from collecting stability data to comparing the comprehensive adaptation index is re-executed until the comprehensive adaptation index meets the conditions or reaches the preset maximum extension time.

7. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 6, characterized in that, The step of inputting the collected user heart rate variability stability data and user respiratory rate stability data into the adaptive evaluation module of the stepwise pressurization strategy model includes: The adaptive assessment module performs statistical analysis on the heart rate variability stability data over a specific time period, and calculates the ratio of the variance to the mean of the heart rate variability as the heart rate stability coefficient. The adaptive assessment module performs statistical analysis on respiratory rate stability data over a specific time period, and calculates the ratio of the variance to the mean of the respiratory rate as the respiratory stability coefficient. Extract the user's heart rate variability stability coefficient and respiratory rate stability coefficient at the end of the previous pressure increase phase from the historical data of the phased pressurization. Calculate the rate of change of the heart rate stability coefficient in the current stage relative to the heart rate stability coefficient at the end of the previous stage, and use it as the heart rate adaptive increment. Calculate the rate of change of the respiratory stability coefficient in the current stage relative to the respiratory stability coefficient at the end of the previous stage, as the respiratory adaptation increment; The comprehensive adaptation index is obtained by weighted summing of the heart rate stability coefficient, respiratory stability coefficient, heart rate adaptation increment, and respiratory adaptation increment.

8. The stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 7, characterized in that, It also includes dynamic safety assurance measures during the pressurization process: Establish a safe range for dynamic physiological monitoring data, which includes the upper and lower limits of heart rate variability and respiratory rate. Throughout the pressurization process, the real-time heart rate variability and real-time respiratory rate are continuously compared with the safe range. When the real-time heart rate variability or real-time respiratory rate exceeds its corresponding safety range, a safety intervention command is immediately generated. The safety intervention command has a higher priority than any command that adjusts the rate of increase in pressure. In response to the safety intervention command, the pressurization process is immediately stopped, and the gas pressure inside the medical hyperbaric oxygen chamber is reduced to a preset safe pressure threshold at a preset safe decompression rate, and an audible and visual alarm is activated.

9. A stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 8, characterized in that, After the target therapeutic pressure is reached, the process also includes physiological state monitoring and reassessment during the pressure maintenance phase. During the period when the gas pressure in the medical hyperbaric oxygen chamber is stabilized at the target treatment pressure, heart rate variability and respiratory rate are continuously collected and recorded during the maintenance phase. Calculate the mean heart rate variability and mean respiratory rate during the maintenance phase; The calculated mean heart rate variability and mean respiratory rate during the maintenance phase are compared with the baseline heart rate variability and baseline respiratory rate values ​​in the individual physiological characteristic parameters. Based on the comparison results, the user's overall level of adaptation to the target therapeutic stress is assessed, and an adaptation level assessment report is generated.

10. A stepped pressurization method for use in a medical hyperbaric oxygen chamber according to claim 9, characterized in that, The adaptation level assessment report, dynamic physiological monitoring data of each pressure escalation stage, the final adjusted pressurization rate set, and the results of the phased adaptation assessment are stored together as a complete record of this pressurization treatment process, which is used to update the internal parameters of the stepwise pressurization strategy model.

Images