Intelligent detection system for medical oxygen use time length and cumulative flow

Abstract

The present application relates to the technical field of medical management, and particularly relates to an intelligent detection system for medical oxygen use time length and cumulative flow, which comprises a flow monitoring unit, a data processing unit, a display interaction unit, an early warning unit, a data storage unit and an interface unit. The flow monitoring unit integrates a thermal mass flow sensing element and an environmental parameter compensation module, collects instantaneous flow and performs standard condition conversion; the data processing unit identifies oxygen use start and stop time through a state machine, adopts trapezoidal integration to accumulate oxygen use time length and flow, and internally builds an adaptive early warning model to realize individualized safety monitoring and leakage identification according to dynamic threshold and flow change rate; the data storage unit constructs a structured oxygen use file; the present application realizes automatic monitoring, accurate measurement, intelligent early warning and information tracing of the medical oxygen use process, and solves the problems of low data accuracy, heavy workload, lagging risk response and low management efficiency of the traditional manual monitoring mode.

Description

Technical Field

[0001] This invention relates to the field of medical management technology, specifically to an intelligent detection system for the usage time and cumulative flow of medical oxygen. Background Technology

[0002] In clinical medical treatment, medical oxygen is a core medical resource for rescuing critically ill patients and alleviating hypoxia symptoms. Accurate monitoring of its usage duration and cumulative flow directly affects the scientific evaluation of patient treatment effectiveness, the assessment of changes in their condition, and the calculation of medical costs. It is also a crucial link in achieving refined medical management in hospitals. Currently, the medical oxygen supply model adopted by medical institutions at all levels in China (especially primary hospitals, community health service centers, and inpatient wards) is still mainly based on traditional manual monitoring. This model generally suffers from prominent problems such as cumbersome operation, low monitoring accuracy, high labor costs, and difficulties in data traceability, failing to meet the needs of intelligent and efficient clinical treatment.

[0003] Currently, commonly used medical oxygen delivery devices in clinical practice mainly include central oxygen supply terminals, oxygen humidification bottles, float flow meters, nasal cannulas / masks, etc. Among them, float flow meters are the most widely used flow monitoring components. Their working principle is to use the flowing oxygen to blow up a float inside the tube, and the real-time flow is read through the scale where the float is located. However, this device has obvious defects: the float is easily affected by air pressure fluctuations and will sway up and down, resulting in large errors in manual reading and making it difficult to accurately obtain the actual oxygen flow. At the same time, this type of device can only display the real-time flow, cannot automatically record the usage time, and cannot accumulate the total oxygen flow, relying entirely on nurses to manually complete the data recording.

[0004] In combination with actual clinical work scenarios, the core problems of existing monitoring modes are specifically reflected in the following aspects: First, nurses need to regularly patrol the beds of each oxygen inhalation patient, manually record the starting time of oxygen inhalation and real-time flow, and manually calculate the cumulative flow and total duration after oxygen inhalation is completed. This not only occupies a large amount of nursing time and increases the work load of nurses, but also easily leads to data distortion due to untimely patrols and negligence in manual recording (such as missing records, wrong records, and incorrect records), which affects treatment evaluation and cost accounting; Second, for special scenarios such as intensive care unit (ICU) and emergency resuscitation room, patients need continuous oxygen inhalation for a long time, and the flow needs to be dynamically adjusted according to the patient's condition. Manual monitoring cannot achieve real-time tracking of flow changes, and it is difficult to accurately match the patient's condition requirements, which may affect treatment safety due to failure to detect abnormal flow in time; Third, existing monitoring methods lack data storage and traceability functions. Paper data recorded manually is easy to lose and tamper with, and cannot form a complete file of patients' oxygen use, which is not conducive to medical quality control, handling of doctor-patient disputes, and statistical analysis of medical data; Fourth, some existing oxygen monitoring devices (such as monitoring equipment supporting some central oxygen supply systems) can only achieve centralized flow monitoring, cannot accurately locate individual patients, have high equipment costs, and are difficult to be widely popularized and applied in primary medical institutions and general wards. Meanwhile, most devices do not realize the collaborative monitoring of duration and flow, have single functions, and cannot meet diversified clinical needs.

[0005] In addition, with the improvement of medical informatization and intelligence levels, hospitals are gradually promoting the construction of smart nursing. The traditional manual monitoring mode can no longer meet the linkage requirements of modern medical facilities such as smart hospital beds and smart logistics management systems. There is an urgent need for an intelligent detection system that can automatically, accurately and real-time monitor the use duration and cumulative flow of medical oxygen, with convenient operation, controllable cost and adaptability to various clinical scenarios, so as to solve many pain points in the prior art, reduce the work burden of nursing staff, and improve the intelligent level of medical diagnosis and management. Summary of the Invention

[0006] The object of the present invention is to provide an intelligent detection system for medical oxygen use duration and cumulative flow, comprising a flow monitoring unit, a data processing unit, a display interaction unit, an early warning unit, a data storage unit and an interface unit, which realizes automatic identification of oxygen use behavior, accurate accumulation of duration and flow, abnormal early warning and data information management.

[0007] To achieve the above technical purpose and obtain the above technical effects, the present invention is implemented through the following technical solutions: An intelligent detection system for medical oxygen use duration and cumulative flow, comprising: a flow monitoring unit, configured to collect real-time instantaneous flow data in an oxygen delivery gas path; A data processing unit, connected to the flow monitoring unit, is used to automatically identify the start and stop times of oxygen delivery based on the instantaneous flow data, and to calculate the oxygen usage duration and cumulative flow based on the instantaneous flow data. The display interaction unit is connected to the data processing unit and is used to display the instantaneous flow data, the oxygen use duration and the cumulative flow in real time, and to receive control commands input by the user. An early warning unit, connected to the data processing unit, is used to issue an early warning signal when the instantaneous flow data deviates from a preset safety condition; A data storage unit, connected to the data processing unit, is used to store oxygen usage records including patient information, oxygen use start and end times, and cumulative oxygen use parameters. The interface unit is used to realize the physical connection and data communication between the system and external oxygen delivery equipment and hospital information system.

[0008] Furthermore, the data processing unit includes a state machine module, which is configured as follows: When the instantaneous flow rate data is continuously greater than the preset starting flow rate threshold within a preset first time window, it is determined to be the oxygen supply start state, and the start time of the first time window is recorded as the start time. When the instantaneous flow rate data is continuously less than the preset stop flow rate threshold within the preset second time window, it is determined that the oxygen supply has stopped, and the end time of the second time window is recorded as the stop time. The data processing unit is configured to use a numerical integration method to accumulate the instantaneous flow data over time in order to calculate the cumulative flow.

[0009] Furthermore, the numerical integration method is the trapezoidal rule for numerical integration, that is, through the formula... Calculate the cumulative flow ,in For the first Instantaneous flow data at each sampling time point, The sampling interval is... The starting time is... The stopping time is mentioned above.

[0010] Furthermore, the flow monitoring unit includes a flow sensing element and an environmental parameter compensation module, wherein the environmental parameter compensation module is used to collect ambient air pressure and / or ambient temperature. The data processing unit is further configured to compensate the raw flow signal output by the flow sensing element based on the ambient air pressure and / or ambient temperature to generate instantaneous flow data under standard conditions.

[0011] Furthermore, the compensation is based on the ideal gas law, and the compensated instantaneous flow rate data satisfy: in The original flow signal, Standard atmospheric pressure For standard temperature, For real-time collection of ambient air pressure, This refers to the ambient temperature collected in real time.

[0012] Furthermore, the data processing unit includes an adaptive early warning module, which is configured to: The system obtains the static safety threshold range set by the user and determines the dynamic adjustment factor based on the patient's clinical information. The dynamic adjustment factor is set by the user through the display interaction unit or obtained by the interface unit from the hospital information system. A dynamic safety threshold range is generated based on the static safety threshold range and the dynamic adjustment factor; When the instantaneous traffic data exceeds the dynamic safety threshold range, a traffic anomaly warning signal is generated; In addition, the rate of change of the instantaneous flow data within a preset time window is calculated, and an oxygen leak warning signal is generated when the absolute value of the rate of change exceeds a preset leakage rate of change threshold and the duration exceeds a preset leakage determination time.

[0013] Furthermore, the display interaction unit is configured as follows: Receive the user-defined target traffic value and allowable error bandwidth; The deviation between the instantaneous flow rate data and the target flow rate value is calculated in real time. When the absolute value of the deviation exceeds the allowable error bandwidth, an auxiliary adjustment signal containing adjustment direction prompts is generated in a visual manner to guide the user to adjust the oxygen flow rate.

[0014] Furthermore, the interface unit includes: A mechanical interface is used to connect the flow monitoring unit in series to the oxygen delivery circuit. The inlet port of the mechanical interface is adapted to the medical oxygen supply end, and the outlet port is adapted to the oxygen inhalation terminal. For example, the inlet port can be set as a quick-plug structure that matches the outlet of a standard medical oxygen humidification bottle, and the outlet port can be set as a conical connector that matches the inlet tube of a standard oxygen nasal cannula or mask.

[0015] The communication interface is used to establish a data connection with the hospital information system to realize the reporting of oxygen usage records and the synchronization of patient information.

[0016] Furthermore, it also includes an integrated housing, in which the flow monitoring unit, data processing unit, display and interaction unit, early warning unit, data storage unit and interface unit are all integrated. The back of the integrated housing is provided with a detachable fixing structure for fixing the system to an oxygen humidification bottle or a bed rail.

[0017] Furthermore, it also includes a power management unit for providing operating power to the system, the power management unit comprising: Rechargeable batteries; External power interface; The power path management module is used to automatically switch to power supply from the external power source when the external power source is connected, and to automatically switch to power supply from the rechargeable battery when the external power source is disconnected. The power monitoring module is used to monitor the remaining power of the rechargeable battery and generate a low power warning signal when the remaining power is lower than a preset threshold.

[0018] The beneficial effects of this invention are: This invention achieves fully automatic, high-precision acquisition of oxygen usage duration and cumulative flow by combining thermal mass flow sensing and environmental parameter compensation with time-window-based state machine decision-making and trapezoidal integration, eliminating data distortion caused by manual readings and recording. The thermal mass flow sensing element outputs an electrical signal linearly related to the mass flow rate, avoiding mechanical oscillation reading errors caused by air pressure fluctuations in float flowmeters. The environmental air pressure and temperature sensors dynamically compensate the original signal based on the ideal gas law, converting the actual operating condition measurement value into the volumetric flow rate under standard conditions, eliminating the influence of altitude and seasonal temperature on gas density. The state machine module requires that the instantaneous flow rate continuously exceeds the starting threshold within the first time window to determine the start of oxygen supply, and continuously falls below the stopping threshold within the second time window to determine the stop of oxygen supply. The time-window decision-making filters out non-steady-state factors such as breathing rhythm and pipeline disturbances, achieving reliable automatic recording of oxygen usage duration. The cumulative flow is obtained by using the trapezoidal method for numerical integration, which approximates the true area under the flow curve piecewise based on the average flow of adjacent sampling points. Compared with rectangular integration or simple accumulation, this method significantly improves the calculation accuracy in scenarios with frequent flow fluctuations, and enables both core parameters to be automatically generated without human intervention.

[0019] This invention employs a three-tiered progressive early warning model—comprising static threshold ranges, dynamic adjustment factors, and flow rate change monitoring—to achieve individualized safety boundary setting and proactive leak event identification during oxygen use. This addresses the problems of single early warning mechanisms, inability to adapt to individual differences, and the inability to detect slow leaks. The adaptive early warning module receives an externally input static safety threshold range as the basic safety boundary and introduces a dynamic adjustment factor based on patient clinical information to scale the static threshold, generating a dynamic safety threshold range. This achieves parameter mapping from group applicability to individual adaptation. For leak identification, the module calculates the rate of change of instantaneous flow within a preset time window and combines the rate of change threshold and duration threshold for dual judgment. This effectively distinguishes the continuous unidirectional decay unique to leak events from normal flow fluctuations and proactive adjustment behaviors, issuing an early warning before the leak develops to the point of severely impacting oxygen supply levels, thus shifting the risk intervention point forward.

[0020] This invention's system possesses universal deployment capabilities across medical institutions at different levels. The data storage unit constructs a time-series database comprising patient information tables, oxygen usage event tables, real-time data tables, and early warning event tables. Instantaneous flow sampling data, state transition times, and early warning records are stored in a structured manner, forming a digital archive that can be traced long-term and supports multi-dimensional queries. The communication interface supports establishing a bidirectional data link with the hospital information system. Uplink, oxygen usage records are automatically reported to achieve centralized data collection and automated cost calculation. Downlink, patient information synchronization commands are received to automatically enter basic information, allowing bedside monitoring data to be directly integrated into the hospital's information management system, replacing manual recording and repetitive data entry.

[0021] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Detailed Implementation

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] This embodiment provides an intelligent detection system for medical oxygen usage time and cumulative flow, mainly including a flow monitoring unit, a data processing unit, a display and interaction unit, an early warning unit, a data storage unit, an interface unit, and a power management unit that supplies power to the above units. Each unit is integrated into a compact housing, forming an independent, portable, and installable intelligent detection device. The system is connected in series with the oxygen delivery path between the medical oxygen humidification bottle and the nasal cannula or face mask via the interface unit. When a patient begins oxygen inhalation, the system automatically identifies the oxygen supply start-up status, collects instantaneous flow data in real time, calculates the cumulative oxygen usage time and flow, and presents this data in real time through the display and interaction unit. When an abnormal flow or equipment malfunction is detected, the early warning unit issues an audible and visual alarm. Data from the entire oxygen usage process is completely stored in the data storage unit and can be uploaded to the hospital information system via the interface unit.

[0024] The flow monitoring unit includes a flow sensing element and an environmental parameter compensation module. In this embodiment, the flow sensing element uses a thermal mass flow sensor chip, such as a MEMS-based thermal film flow sensor. This sensor utilizes the principle of heat transfer; when oxygen flows across the sensor surface, it carries away heat. By detecting changes in heat, an electrical signal proportional to the mass flow rate can be output. Thermal mass flow sensors have advantages such as fast response speed, low pressure loss, and no moving parts, making them particularly suitable for the accurate monitoring of medical oxygen. The flow sensing element acquires the raw flow signal in the oxygen delivery path in real time at a sampling frequency of not less than 1Hz and transmits it to the signal conditioning circuit. The signal conditioning circuit filters, amplifies, and performs analog-to-digital conversion on the raw flow signal to generate digitized instantaneous flow data.

[0025] Considering that changes in ambient air pressure and temperature in the clinical environment affect gas density, and thus the accuracy of the conversion between mass flow rate and volumetric flow rate, the environmental parameter compensation module includes a pressure sensor and a temperature sensor. The pressure sensor is used to collect the absolute ambient air pressure value in real time, and the temperature sensor is used to collect the ambient temperature value in real time. The data processing unit dynamically compensates the original flow signal based on the above environmental parameters to generate instantaneous flow data under standard conditions, thereby eliminating measurement errors caused by factors such as altitude and seasonal changes. Specifically, the compensated instantaneous flow data satisfies the following formula: in The original flow signal, Standard atmospheric pressure For standard temperature, For real-time collection of ambient air pressure, The ambient temperature is collected in real time. The compensation formula is derived based on the ideal gas law and can convert the mass flow rate under actual operating conditions into the volumetric flow rate under standard conditions, thereby ensuring the consistency and comparability of monitoring data under different environments. It is understood that in other embodiments, the environmental parameter compensation module may also include only a pressure sensor or only a temperature sensor to adapt to different accuracy requirements and cost considerations.

[0026] The data processing unit is implemented using a low-power microcontroller, such as the STM32L4 series microcontroller. This microcontroller has a state machine model, an integral calculation model, and an adaptive early warning model embedded in it, which are used to execute the core data processing and control logic.

[0027] To address the issue of false triggering caused by interference factors such as airflow fluctuations and float swaying, the state machine model in the data processing unit is configured to employ a time window-based de-jitter algorithm to automatically identify the start and stop times of oxygen delivery. Specifically, when the system is in standby mode, the data processing unit continuously monitors instantaneous flow data. If within the preset first time window Within the sample, the flow rate values ​​of more than a preset proportion of sampling points all exceeded the preset initial flow rate threshold. If the condition is met, it is determined to be the oxygen supply start state, the state machine jumps to the oxygen supply working state, and the start time of this first time window is recorded as the oxygen supply start time. Accordingly, when the system is in oxygen supply mode, if within the preset second time window... Within the sample, the flow rate values ​​of more than a preset proportion of sampling points are all less than the preset stop flow rate threshold. If the oxygen supply stops, the state machine transitions to standby mode and records the end time of the second time window as the oxygen supply stop time. Through the aforementioned anti-jitter algorithm, the system can effectively filter out sudden changes in flow caused by patient breathing, slight pipe vibration, or equipment fluctuations, ensuring accurate and reliable determination of start and stop times.

[0028] When the system is in oxygen supply operation, the data processing unit is configured to use trapezoidal rule numerical integration to accumulate the instantaneous flow rate data over time to calculate the cumulative flow rate. Specifically, the data processing unit calculates the cumulative flow rate according to the following formula: in, This represents the cumulative oxygen flow rate from the start of oxygen supply to the stop of oxygen supply. Indicates the first Instantaneous flow data at each sampling time; This is the starting point of oxygen supply; This is the moment when oxygen supply stops; The sampling interval is set to 1 second in this embodiment. A trapezoidal method is used to approximate the integral, which involves multiplying the average flow rate of two adjacent sampling points by the sampling interval to approximate the flow rate integral over that time period. Compared to simple rectangular integration, this method more accurately approximates the area under the actual flow rate curve, thereby improving the accuracy of the cumulative flow rate calculation. Simultaneously, the oxygen usage duration... According to the formula Calculation, where and All results are in seconds, and the calculation results are displayed in minutes, accurate to the minute.

[0029] The data processing unit also incorporates an adaptive early warning model for individualized oxygen safety monitoring. This model first acquires the static safety threshold range set by the user through the interactive display unit. For example, for adult patients, the static safety threshold can be preset to 0.5 L / min to 3 L / min; for pediatric patients, it can be preset to 0.25 L / min to 1 L / min. To adapt to the personalized needs of patients in different departments and with different conditions, the adaptive early warning model also introduces a dynamic adjustment factor. This dynamic adjustment factor can be manually set by medical staff based on the patient's clinical information or automatically obtained from the hospital information system through the interface unit. Based on the dynamic adjustment factor, the system generates a dynamic safety threshold range, as follows: Among them, Dynamic safety lower threshold; This is a dynamic safety upper limit threshold; This is a dynamic adjustment factor, typically ranging from 0.5 to 1.5. This is the static safety lower limit threshold. This is a static safety upper limit threshold. For example, for critically ill patients in the ICU, it can be set to... To relax the threshold range; for patients requiring strict control of oxygen consumption, a setting can be made. The threshold range is tightened. During oxygen supply, the data processing unit compares instantaneous flow data in real time. With dynamic safety threshold range, when instantaneous traffic data Below the dynamic lower limit threshold A low flow warning signal is generated in real time when the instantaneous flow data... Above the dynamic upper limit threshold A high traffic warning signal is generated in real time.

[0030] In addition, the adaptive early warning model is also configured to detect oxygen leak events. Specifically, the data processing unit calculates the rate of change of instantaneous flow data within a preset time window, using the following formula: in, This represents the rate of change of instantaneous flow data with respect to time. This represents the instantaneous flow data at the current moment. for Instantaneous flow data prior to the current moment; The preset time window length is 10 seconds in this embodiment. When the absolute value of the rate of change exceeds the preset leakage rate of change threshold and the duration exceeds the preset leakage detection time, the system determines that an oxygen leak has occurred and generates an oxygen leak warning signal. For example, when the absolute value of the rate of change exceeds 0.5 L / min / s and lasts for more than 3 seconds, a leak alarm is triggered. This timely detection of abnormal leaks caused by pipe detachment, loose connections, or damaged humidification bottles ensures the safety of patients' oxygen use.

[0031] The display and interaction unit uses a high-resolution capacitive LCD touchscreen, such as a 3.5-inch TFT color screen with a resolution of 480×320, embedded in the front of the housing. The graphical user interface of the display and interaction unit is configured to include multiple functional interfaces. The real-time monitoring interface dynamically plots instantaneous flow data in the form of a graph. The real-time waveform is displayed, along with the cumulative oxygen consumption time shown in large-font numerical format. and cumulative traffic The system overlays the upper and lower limits of the dynamic safety threshold range onto the graph, automatically highlighting the threshold line when it is reached, facilitating intuitive judgment by medical staff. The parameter configuration interface receives user-input start / stop thresholds. , Static safety threshold range Dynamic adjustment factor The system includes target flow rate values ​​and patient identification information; all configuration parameters have default values, allowing healthcare professionals to flexibly adjust them according to clinical needs. The historical data query interface retrieves corresponding oxygen usage records from the data storage unit based on patient identification, time range, or alert type, displaying them in a table and graph overlay format. Users can preview, print, or export the query results. A fault prompt interface automatically pops up when the device experiences sensor malfunctions, loose interfaces, or insufficient battery power, displaying the cause of the fault and simple troubleshooting methods for quick handling by nursing staff. The display and interaction unit also supports one-click start and stop monitoring functions, allowing healthcare professionals to quickly turn patient oxygen monitoring on and off using virtual buttons on the touchscreen.

[0032] The early warning unit includes a buzzer and an LED indicator, both located on the top of the housing for easy detection by medical staff from a distance. The buzzer features an adjustable volume design, ranging from 50dB to 70dB to suit different ward environments. The LED indicator uses high-brightness red light-emitting diodes with a strobe function. When the data processing unit generates an early warning trigger signal, the early warning unit executes the corresponding alarm level based on the anomaly type identifier. For example, for high or low flow warnings, the buzzer sounds intermittently, and the LED indicator remains constantly lit; for oxygen leak warnings, the buzzer sounds rapidly, and the LED indicator flashes frequently; for equipment malfunction or low battery warnings, the buzzer sounds continuously, and the LED indicator flashes slowly. After medical staff have investigated and confirmed the handling of the anomaly, they can confirm the alarm cancellation via the touchscreen of the display interaction unit. The trigger time, cancellation time, and anomaly type of all early warning events are recorded in the data storage unit for subsequent traceability and analysis.

[0033] The data storage unit employs embedded non-volatile memory, such as eMMC or NAND Flash chips, with a capacity of at least 16GB, for structured storage of complete oxygen usage records. Internally, the data storage unit contains a time-series database, whose data structure includes at least a patient information table, an oxygen usage event table, a real-time data table, and an early warning event table. The patient information table associates patient unique identifiers with bed numbers, names, clinical diagnosis information, etc., and supports synchronization with the hospital information system. The oxygen usage event table records the unique identifier, patient unique identifier, start time, stop time, oxygen usage duration, and cumulative flow for each oxygen administration event. The real-time data table records the instantaneous flow data and corresponding system operating status at each sampling moment, indexed by timestamps, forming a complete oxygen usage process curve. The early warning event table records the unique identifier, trigger time, release time, abnormality type identifier, and the unique identifier of the associated oxygen usage event for each early warning event. Through this structured data storage method, the system can achieve rapid querying, statistical analysis, and long-term traceability of oxygen usage data.

[0034] The interface unit consists of two parts: a mechanical interface and a communication interface. The mechanical interface connects the flow monitoring unit in series with the oxygen delivery circuit. Its inlet port has a quick-connect structure compatible with the outlet of a standard medical oxygen humidification bottle, and its outlet port has a tapered connector compatible with the inlet tube of a standard oxygen nasal cannula or face mask. During installation, medical personnel simply connect the device between the humidification bottle and the nasal cannula; no tools are required to complete the circuit connection. The interface uses a medical-grade silicone sealing ring to ensure airtightness. The communication interface includes a wired communication interface and a wireless communication interface. The wired communication interface uses a Micro-USB or USB Type-C interface, which can be used for data transfer and device charging. Through this interface, the device can be connected to a computer to enable local export of oxygen usage records and firmware upgrades. The wireless communication interface uses Wi-Fi or Bluetooth Low Energy protocols to establish a secure data connection with the hospital information system. The device reports oxygen usage records to the hospital's HIS system, nursing management system, or smart logistics management platform in real time or on a schedule according to preset rules via the wireless network, realizing automatic synchronization and centralized management of oxygen usage data. At the same time, the device can also receive patient information synchronization instructions from the hospital information system via the wireless interface, reducing the workload of manual data entry by medical staff.

[0035] All the aforementioned units are integrated and packaged within an integrated housing, forming an independent portable device. The integrated housing has a rounded rectangular structure, with preferred external dimensions of 9cm in length, 5.5cm in width, and 3.5cm in height, and a weight not exceeding 200g, facilitating installation in the limited space around the hospital bed. The rounded corners of the housing prevent sharp edges from scratching medical staff or patients. The housing is medical white with a stain-resistant treatment for easy cleaning and disinfection. The front of the housing features a touchscreen for the display and interaction unit, while the top of the housing houses the buzzer and LED indicator for the warning unit. The sides of the housing include a power button, volume control buttons, and various interfaces for the interface unit. The back of the housing features a detachable fixing structure, an adjustable-radius medical-grade silicone clamp that can be clamped onto the oxygen humidification bottle or the bed rail. The clamp has a built-in spring mechanism to accommodate cylindrical structures of different diameters, ensuring a secure clamping without damaging the instrument surface. In other embodiments, the fixing structure may also use medical-grade waterproof adhesive pads, which can be repeatedly applied and are suitable for fixing to walls or other flat surfaces.

[0036] The power management unit provides a stable and reliable power supply for all modules of the system, including a rechargeable lithium battery pack, an external power interface, a power path management module, and a power monitoring module. The rechargeable lithium battery pack uses high-energy-density lithium polymer batteries with a nominal capacity of no less than 3000mAh, supporting continuous system operation for at least 24 hours on a full charge, meeting the patient's 24 / 7 oxygen monitoring needs. The external power interface uses a USB Type-C interface, supports fast charging protocols, and can be connected to an AC adapter or power bank. The power path management module is configured to automatically switch to external power supply to power the system and simultaneously charge the lithium battery pack when external power is connected, and seamlessly switch back to lithium battery power when external power is disconnected. This design ensures uninterrupted system operation during power switching, preventing data loss due to power outages. The power monitoring module is used to monitor the remaining power and voltage of the lithium battery pack in real time. When the remaining power is lower than the preset low power threshold or the voltage is lower than the preset minimum operating voltage, the power monitoring module generates a low power warning signal, and the data processing unit triggers the warning unit to issue a low power audible and visual alarm. At the same time, it automatically saves all current operating data to ensure data integrity.

[0037] The following describes the system's operation process using typical usage scenarios. During installation, medical staff remove the connecting tube between the oxygen humidification bottle and the nasal cannula or mask. Insert the system's mechanical interface inlet port into the oxygen humidification bottle's outlet port until a "click" sound confirms a lock. Insert the nasal cannula or mask's inlet tube into the system's mechanical interface outlet port. Secure the device to the oxygen humidification bottle or bed rail using the fixing structure on the back of the casing. After powering on, press and hold the power button for 3 seconds to start the device. Once started, the system automatically enters standby mode, and the interactive display unit presents the parameter configuration interface. Medical staff input the patient's bed number and name via the touchscreen, or quickly input information by scanning the patient's wristband with a barcode scanner. Based on the patient's condition, they can select a preset safety threshold template or manually adjust the static safety threshold range and dynamic adjustment factor. Optional settings include a target flow rate and allowable error bandwidth for auxiliary adjustment guidance. Clicking the "Start Monitoring" button puts the system into oxygen supply monitoring mode. The system automatically identifies the oxygen delivery status, collects flow data in real time, calculates cumulative duration and cumulative flow, and dynamically displays the flow curve and cumulative data on the real-time monitoring interface. After the patient finishes receiving oxygen, medical staff can click the "Stop Monitoring" button. The system will automatically save the oxygen usage data for this session, and the data can be printed or exported.

[0038] In terms of data management, under local management mode, medical staff can access the historical data query interface via the device's touchscreen, select patients or time ranges, and query oxygen usage event records, real-time flow curves, and early warning event records. Data can also be exported to a USB drive or computer. In remote linkage mode, the device connects to the hospital's HIS system and nursing management system via a wireless communication interface, enabling real-time uploading of oxygen usage data. Nurses can view the oxygen usage of all patients at the nurse station terminal, achieving centralized management without the need for individual bedside checks. The system automatically backs up oxygen usage data, which can be stored for at least one year for subsequent traceability and statistical analysis.

[0039] To ensure long-term stable operation of the system, this embodiment also provides maintenance and calibration solutions. For routine maintenance, regularly wipe the device surface with medical alcohol, check the interface connections for secureness, and regularly charge the lithium battery to prevent long-term undercharging and battery damage. For troubleshooting, the touchscreen will display fault prompts when a malfunction occurs, such as sensor abnormality, insufficient power, or loose interface. Medical personnel can perform simple troubleshooting based on the prompts. If the problem persists, contact professional maintenance personnel to read the fault log through the data transmission interface for targeted repair. Regarding accuracy calibration, it is recommended to perform accuracy calibration on the flow sensor every 3 months. Calibration can be performed using dedicated calibration equipment. Connect the device to a standard flow source; the system will automatically detect flow deviation and generate calibration coefficients, making the operation simple and convenient.

[0040] It should be understood that the above embodiments are merely preferred embodiments of the present invention and do not constitute a limitation on the scope of protection of the present invention. Based on the concept of the present invention, those skilled in the art can make various equivalent transformations or modifications, all of which fall within the scope of protection of the present invention. For example, in some embodiments, the system can provide two specifications of devices: a basic model adapted to primary healthcare institutions with core monitoring, alarm, and local storage functions, and an advanced model adapted to large hospitals with remote linkage, data statistics, and multi-scenario adaptation functions. Both specifications support compatibility with existing medical oxygen supply equipment without large-scale modifications. Furthermore, in some embodiments, the touchscreen of the display interaction unit can support multi-language switching to meet the usage needs of different medical personnel. Moreover, in some embodiments, the power management unit can be further configured to support wireless charging, improving the convenience of device use. The above descriptions are merely specific embodiments of the present invention, and the scope of protection of the present invention should be determined by the scope of the claims.

[0041] In summary, this invention proposes an intelligent detection system for medical oxygen usage duration and cumulative flow, comprising a flow monitoring unit, a data processing unit, a display and interaction unit, an early warning unit, a data storage unit, and an interface unit. The flow monitoring unit integrates a thermal mass flow sensor and an environmental parameter compensation module, collecting instantaneous flow and performing standard condition conversion. The data processing unit identifies the start and end times of oxygen use through a state machine, integrates the cumulative oxygen usage duration and flow using a trapezoidal method, and incorporates an adaptive early warning model to achieve individualized safety monitoring and leak identification based on dynamic thresholds and flow change rates. The data storage unit constructs a structured oxygen usage archive. The interface unit supports standardized gas path connections and bidirectional data communication with hospital information systems. This invention achieves automated monitoring, accurate metering, intelligent early warning, and information-based traceability of medical oxygen usage, solving the problems of low data accuracy, heavy workload, delayed risk response, and low management efficiency associated with traditional manual monitoring methods.

[0042] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent detection system for medical oxygen usage time and cumulative flow, characterized in that, include: The flow monitoring unit is used to collect instantaneous flow data in the oxygen delivery circuit in real time; A data processing unit, connected to the flow monitoring unit, is used to automatically identify the start and stop times of oxygen delivery based on the instantaneous flow data, and to calculate the oxygen usage duration and cumulative flow based on the instantaneous flow data. The display interaction unit is connected to the data processing unit and is used to display the instantaneous flow data, the oxygen use duration and the cumulative flow in real time, and to receive control commands input by the user. An early warning unit, connected to the data processing unit, is used to issue an early warning signal when the instantaneous flow data deviates from a preset safety condition; A data storage unit, connected to the data processing unit, is used to store oxygen usage records including patient information, oxygen use start and end times, and cumulative oxygen use parameters. The interface unit is used to realize the physical connection and data communication between the system and external oxygen delivery equipment and hospital information system.

2. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, The data processing unit includes a state machine module, which is configured as follows: When the instantaneous flow rate data is continuously greater than the preset starting flow rate threshold within a preset first time window, it is determined to be the oxygen supply start state, and the start time of the first time window is recorded as the start time. When the instantaneous flow rate data is continuously less than the preset stop flow rate threshold within the preset second time window, it is determined that the oxygen supply has stopped, and the end time of the second time window is recorded as the stop time. The data processing unit is configured to use a numerical integration method to accumulate the instantaneous flow data over time in order to calculate the cumulative flow.

3. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 2, characterized in that, The numerical integration method is the trapezoidal rule, i.e., through the formula: Calculate the cumulative flow ,in For the first Instantaneous flow data at each sampling time. The sampling interval is... The starting time is... The stopping time is mentioned above.

4. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, The flow monitoring unit includes a flow sensing element and an environmental parameter compensation module, wherein the environmental parameter compensation module is used to collect ambient air pressure and / or ambient temperature. The data processing unit is further configured to compensate the raw flow signal output by the flow sensing element based on the ambient air pressure and / or ambient temperature to generate instantaneous flow data under standard conditions.

5. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 4, characterized in that, The compensation is based on the ideal gas law, and the compensated instantaneous flow rate data... satisfy: in The original flow signal, Standard atmospheric pressure Standard temperature For real-time collection of ambient air pressure, This refers to the ambient temperature collected in real time.

6. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, The data processing unit includes an adaptive early warning module, which is configured to: The system obtains the static safety threshold range set by the user and determines the dynamic adjustment factor based on the patient's clinical information. The dynamic adjustment factor is set by the user through the display interaction unit or obtained by the interface unit from the hospital information system. A dynamic safety threshold range is generated based on the static safety threshold range and the dynamic adjustment factor; When the instantaneous traffic data exceeds the dynamic safety threshold range, a traffic anomaly warning signal is generated; In addition, the rate of change of the instantaneous flow data within a preset time window is calculated, and an oxygen leak warning signal is generated when the absolute value of the rate of change exceeds a preset leakage rate of change threshold and the duration exceeds a preset leakage determination time.

7. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, The display interaction unit is configured as follows: Receive the user-defined target traffic value and allowable error bandwidth; The deviation between the instantaneous flow rate data and the target flow rate value is calculated in real time. When the absolute value of the deviation exceeds the allowable error bandwidth, an auxiliary adjustment signal containing adjustment direction prompts is generated to guide the user to adjust the oxygen flow rate.

8. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, The interface unit includes: A mechanical interface is used to connect the flow monitoring unit in series to the oxygen delivery circuit. The inlet port of the mechanical interface is adapted to the medical oxygen supply end, and the outlet port is adapted to the oxygen inhalation terminal. The communication interface is used to establish a data connection with the hospital information system to realize the reporting of oxygen usage records and the synchronization of patient information.

9. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, It also includes an integrated housing, in which the flow monitoring unit, data processing unit, display and interaction unit, early warning unit, data storage unit and interface unit are all integrated. The back of the integrated housing is provided with a detachable fixing structure for fixing the system to an oxygen humidification bottle or a bed rail.

10. The intelligent detection system for medical oxygen usage time and cumulative flow rate as described in claim 1, characterized in that, It also includes a power management unit for providing operating power to the system, the power management unit comprising: Rechargeable batteries; External power interface; The power path management module is used to automatically switch to power supply from the external power source when the external power source is connected, and to automatically switch to power supply from the rechargeable battery when the external power source is disconnected. The power monitoring module is used to monitor the remaining power of the rechargeable battery and generate a low power warning signal when the remaining power is lower than a preset threshold.

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