Multifunctional intelligent medical specimen temporary storage equipment

Abstract

The invention discloses a multifunctional intelligent medical specimen temporary storage device, and aims to solve the problem that the existing specimen temporary storage device is lack of predictive regulation and intelligent protection, the multifunctional intelligent medical specimen temporary storage device coordinates components such as a temperature and humidity sensor group through a main control chip module to construct a temperature and humidity historical sequence; the future temperature and humidity trend is predicted by using a time sequence prediction model, and advanced intervention and energy-saving temperature control are realized; the stability and the intelligent level of the specimen storage environment are improved, the predictability, the reliability and the safety of the system are enhanced, and the system is suitable for short-term specimen storage scenes such as hospitals and biological sample libraries.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical specimen storage equipment, in particular to a multifunctional intelligent medical specimen temporary storage equipment. BACKGROUND

[0002] The temporary storage of medical specimens is a key link in the medical examination process. The storage conditions of the specimens from collection to detection directly affect the accuracy of the test results and the effectiveness of the specimens. Different types of specimens have different requirements for the temperature and humidity of the storage environment. The existing medical specimen storage equipment mainly uses temperature threshold-based on-off control or simple PID control to achieve temperature and humidity regulation. Although this control method can achieve basic regulation of the storage environment, it still has the following technical problems in actual application: Firstly, the traditional control method adopts a "deviation response" mode, that is, the adjustment device is started only when the temperature and humidity deviate from the target value. This lag response mechanism leads to large fluctuations in temperature and humidity, especially when the external environment changes rapidly, it is difficult to maintain a stable microenvironment. Studies have shown that the drastic fluctuations in temperature and humidity can cause irreversible damage to the quality of the specimens, such as changes in enzyme activity in blood specimens and morphological changes in tissue specimens. Secondly, the existing system fails to effectively utilize the potential of passive temperature and humidity adjustment materials. Phase change materials (PCM) and humidity adjustment materials have good passive adjustment capabilities, but this technology has not been applied to the field of medical specimen storage. Thirdly, the purely data-driven prediction method lacks a deep understanding of the physical process and has insufficient generalization ability when facing changes in specimen types, sudden changes in external environment, and other non-training conditions, ignoring the differentiated requirements of different specimens for temperature and humidity control accuracy and response speed.

[0003] In addition, the existing system has a single safety protection mechanism, especially in special scenarios such as pediatric wards, there is a lack of effective protection measures against children's misuse. If the specimen storage equipment is opened or moved by children, it may cause damage to the specimens, loss of control of temperature and humidity, and even biosecurity risks. The existing simple locking mechanism cannot meet the dual requirements of safety and convenience in the medical environment. SUMMARY

[0004] The purpose of the present application is to develop an intelligent medical specimen temporary storage equipment that can achieve precise predictive control, active and passive collaborative regulation, specimen type adaptation, and multiple safety protection, to meet the higher requirements of modern medical examination for specimen storage quality and safety.

[0005] To achieve the above purpose, the present application provides a multifunctional intelligent medical specimen temporary storage equipment, comprising: a specimen storage box body, the specimen storage box body comprising a specimen storage box cover, a bottom plate, and a specimen cabin formed by the specimen storage box cover and the bottom plate; A main control chip module is arranged in the specimen storage box body; A temperature and humidity sensor group is arranged in the specimen cabin and electrically connected with the main control chip module; A passive temperature and humidity adjusting material is arranged in the specimen cabin and includes a phase change material and a humidity adjusting material; A temperature adjusting heating sheet is arranged in the specimen cabin or on the bottom plate and electrically connected with the main control chip module; A humidity adjusting air outlet is arranged on the specimen storage box body and electrically connected with the main control chip module; A magnetic child lock device is arranged between the bottom plate and the specimen cabin and includes a buckle groove arranged at the edge of the bottom plate and a slidable buckle piece, and the specimen cabin is locked by magnetic attraction; An unlocking device is electrically connected with the main control chip module and used for controlling the on-off state of the magnetic child lock device; The main control chip module stores a control program, and the control program realizes the following steps when executed: Step S1: periodically obtaining a current temperature value T_current and a current humidity value H_current from the temperature and humidity sensor group, and storing a temperature history data sequence and a humidity history data sequence by using a sliding window method; Step S2: calculating a temperature change rate dT / dt based on the temperature history data sequence; when T_current is in a preset phase change temperature range and lower than a preset rate threshold, it is determined that the phase change material is in an effective adjusting state; Step S3: based on the temperature history data sequence and the humidity history data sequence, a time series prediction model is used to predict a temperature prediction value T_predict and a humidity prediction value H_predict at a future time; Step S4: determining whether T_predict or H_predict exceeds a target temperature range or a target humidity range, if so, calculating a temperature deviation ΔT or a humidity deviation ΔH, and determining an early intervention time according to the deviation arrival time; Step S5: according to the temperature deviation ΔT, the phase change material state and the early intervention determination result, a hierarchical control strategy is executed: when the temperature deviation is less than a first threshold and the phase change material is in an effective adjusting state, the closing state of the temperature adjusting heating sheet and the humidity adjusting air outlet is maintained; when the temperature deviation is between the first threshold and a second threshold or the phase change material adjusting capacity is insufficient, the temperature adjusting heating sheet or the humidity adjusting air outlet is controlled to work at a low duty cycle by a PWM pulse width modulation mode; when the temperature deviation is greater than the second threshold, the temperature adjusting heating sheet or the humidity adjusting air outlet is controlled to work at a high duty cycle, and an alarm signal is triggered; Step S6: Calculate a prediction error e(t) = T_current(t) - T_predict(t), and adjust the parameters of the time series prediction model according to the prediction error using an adaptive algorithm.

[0006] The memory of the master chip module pre-stores a specimen parameter library, which contains multiple specimen types and their corresponding target temperature ranges , target humidity ranges , and control strategy parameters. The control program also implements a specimen type adaptive control step: receiving specimen type information; reading the corresponding target temperature range and target humidity range from the specimen parameter library according to the specimen type information; and dynamically adjusting the first threshold, the second threshold, and the PWM duty cycle range in step S5 according to the control strategy parameters corresponding to the specimen type.

[0007] In step S3, the time series prediction model uses a linear regression model or an ARMA autoregressive moving average model. When using a linear regression model, the prediction expression is: where a and b are regression coefficients. In step S6, the parameters of the prediction model are updated using an exponential weighted moving average (EWMA) algorithm.

[0008] In step S2, the preset phase change temperature range is determined according to the phase change temperature of the phase change material in the passive temperature and humidity adjusting material.

[0009] A display screen is provided on the specimen storage box cover, and the control program further implements the following steps: displaying the current temperature value T_current, the current humidity value H_current, and the specimen storage duration Δt in real time; recording the specimen entry time t0 and calculating the specimen storage duration Δt = t - t0; when Δt reaches a preset duration threshold, triggering a hierarchical prompt information or an alarm signal.

[0010] In step S4, the determination method of the early intervention time is: calculating the predicted time t_reach required for T_predict to reach the boundary of the target temperature range according to the temperature prediction sequence; and determining the intervention time of executing the hierarchical control strategy of step S5 according to the size of t_reach.

[0011] The master chip module further includes a wireless communication module, and the control program uploads the temperature history data sequence, the humidity history data sequence, the alarm record, and the operation log to a cloud server or a local server through the wireless communication module.

[0012] In step S5, the hierarchical control strategy of humidity is: when the humidity deviation AH is less than the first humidity threshold and the phase change material is in the effective adjustment state, the closing state of the humidity adjustment air port is maintained; when the humidity deviation AH is between the first humidity threshold and the second humidity threshold or the phase change material adjustment capacity is insufficient, the fan in the humidity adjustment air port is controlled to work at a low duty cycle by PWM pulse width modulation; when the humidity deviation AH is greater than the second humidity threshold, the fan in the humidity adjustment air port is controlled to work at a high duty cycle.

[0013] The passive temperature and humidity adjusting material is prepared by a vacuum impregnation method, and a composite structure is formed by impregnating the phase change material into the pores of the porous humidity adjusting material; the phase change material is selected from a paraffin-based phase change material, a fatty acid phase change material or an alkane phase change material; and the humidity adjusting material is selected from silica gel or molecular sieve.

[0014] Compared with the prior art, the present application has the following beneficial effects: Firstly, the present application predicts the future temperature and humidity change trend based on the time series analysis method through the predictive temperature and humidity control algorithm unit, and starts the adjusting device in advance before the temperature and humidity deviates from the target value, effectively overcoming the hysteresis problem of the traditional mode, and significantly reducing the fluctuation amplitude of the temperature and humidity in the specimen cabin. By intelligently estimating the working state of the phase change material, it is dynamically judged whether the passive adjustment capacity is sufficient, and the hierarchical control strategy is executed accordingly. In addition, the present application can effectively prevent children from misoperating or taking away the specimen cabin in the pediatric ward environment, and avoid specimen damage and biological safety risks. It is especially suitable for medical scenes such as pediatric wards, emergency departments and the like with complex personnel and frequent specimen circulation.

[0015] Secondly, the display screen on the specimen storage box cover displays the current temperature value, humidity value and specimen storage duration in real time, so that medical staff can intuitively understand the specimen storage state. The system automatically records the specimen entry time and calculates the storage duration in real time, and triggers an alarm signal when the duration threshold is reached. It provides convenience for medical staff to send for inspection.

[0016] In summary, the present application constructs an intelligent medical specimen temporary storage system with high precision, low energy consumption, self-adaptation and high safety, which can effectively meet the higher requirements of modern medical examination on specimen storage quality and safety, and has important clinical application value and broad market prospect. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments or examples of the present application, the drawings needed to be used in the embodiments or examples will be briefly introduced. Obviously, the drawings in the following description only some of the embodiments of the present application, and for those skilled in the art, without creative labor, other drawings can also be obtained according to the technical solutions shown in the drawings.

[0018] Figure 1 It is a multifunctional intelligent medical specimen temporary storage device structure exploded view; Figure 2 It is a multifunctional intelligent medical specimen temporary storage device part structure enlarged view; Figure 3 It is a multifunctional intelligent medical specimen temporary storage device working state diagram; Figure 4 It is a multifunctional intelligent medical specimen temporary storage device system flow chart. DETAILED DESCRIPTION

[0019] The present application will be further described below in conjunction with the drawings and examples.

[0020] It should be noted that the following detailed description is exemplary, and is intended to provide further explanation of the present application. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0021] It should be noted that the terms used herein are only for the purpose of describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form, and in addition, it should be understood that when the terms "comprise" and / or "include" are used in the specification, there is a feature, step, operation, device, component and / or combination thereof.

[0022] Reference Figures 1-4The embodiment provides a multifunctional intelligent medical specimen temporary storage device, which comprises a specimen storage box body 11, a main control chip module 112, a temperature and humidity sensor group 12, a passive temperature and humidity adjusting material 14, a temperature adjusting heating sheet 13, a humidity adjusting air outlet 15, a mechanical child lock device, a magnetic lock device and an unlocking device 17. The specimen storage box body 11 comprises a specimen storage box cover 111, a bottom plate 113 and a specimen cabin 16 enclosed by the specimen storage box cover 111 and the bottom plate 113. The specimen storage box body 11 adopts an opaque double-layer heat insulation structure, the outer layer is a medical-grade ABS engineering plastic, and the inner layer is a polyurethane heat preservation material, so that the influence of external light and environment on the temperature and humidity in the specimen cabin is effectively reduced. The volume of the specimen cabin 16 can be designed to be 5-20 liters according to actual needs. The specimen storage box cover 111 is integrated with a liquid crystal display screen, which displays the current temperature value, the current humidity value, the specimen storage time length and the system working state in real time. The display screen adopts a low-power design to ensure long-time continuous work. The bottom plate 113 is made of aluminum alloy and is subjected to anodic oxidation treatment on the surface, so that the bottom plate 113 has good corrosion resistance and heat conductivity. The bottom plate 113 is provided with a mounting groove of the temperature adjusting heating sheet 13 and a fixing hole position of the magnetic lock device.

[0023] The main control chip module 112 adopts an ARM architecture microcontroller, which is integrated with an ADC analog-digital converter, a PWM signal generator, a communication interface and other peripherals. The main control chip module 112 is internally provided with a Flash memory for storing a control program and a specimen parameter library and a RAM for data processing during running. The main control chip module 112 is integrated with a wireless communication module, supports Wi-Fi or 4G network, can be connected with a hospital information system (HIS) to realize real-time uploading and remote monitoring of specimen information.

[0024] The temperature and humidity sensor group 12 comprises a digital temperature and humidity sensor, the sampling period of the sensor can be set to 10 seconds to 5 minutes, and is set to 1 minute in the embodiment. The sensor communicates with the main control chip module 112 through an I2C bus and transmits temperature and humidity data in real time.

[0025] The passive temperature and humidity adjusting material 14 adopts a composite temperature and humidity control material, and the composite material is fixed on the inner wall of the specimen cabin 16 in the form of a plate or particles.

[0026] The temperature regulating heating sheet 13 adopts PTC ceramic heating sheet or semiconductor thermoelectric refrigeration sheet. The heating sheet is fixed on the bottom plate 113 or the inner wall of the specimen chamber 16 by bolts and is electrically connected with the PWM output end of the main control chip module 112. The main control chip module 112 realizes fine adjustment of temperature by adjusting the PWM duty cycle. The humidity regulating air outlet 15 includes a micro fan and an air hole. The rated power of the micro fan is 2 to 5 watts, and the rotating speed can be adjusted by a PWM signal. The air hole is provided with a HEPA filter screen to prevent dust and microorganisms from the outside from entering the specimen chamber. When the humidity in the specimen chamber is too high, the fan starts to exhaust the humid air, and when the humidity is too low, the fan reverses or is turned off to reduce water loss.

[0027] The magnetic lock device is an electromagnetic lock, the unlocking process scans the authorized two-dimensional code, the main control chip module 112 verifies the validity of the password or the two-dimensional code, and after verification, the main control chip module 112 controls the magnetic lock device to be powered off to release the magnetic force. At this time, the authorized personnel can manually press and slide the buckle of the mechanical child lock to complete the unlocking, and the specimen chamber 16 can be taken down or opened.

[0028] The control program stored in the main control chip module 112 realizes intelligent temperature and humidity control, and the core of the control program is the combination of predictive control algorithm and passive-active collaborative regulation strategy. The main control chip module 112 reads the current temperature value T_current and the current humidity value H_current from the temperature and humidity sensor group 12 every preset sampling period, and the sampling period is set to 1 minute in this embodiment. The collected data is stored in the form of time stamp data pairs in the circular buffer. The length of the historical data window is set to N sampling periods, and N is not less than 10, and N is set to 30 in this embodiment. The system maintains two arrays with a length of N, a temperature history array and a humidity history array, which respectively store the temperature and humidity data of the last N sampling periods. Each time new data arrives, the array performs first-in first-out update, discards the oldest data and inserts the new data at the head of the array.

[0029] The phase change material has a large heat capacity near the phase change temperature, which can effectively buffer temperature fluctuations. The system determines the working state of the phase change material by the following algorithm. First, calculate the temperature change rate dT / dt, use the last M sampling points to calculate the slope as the temperature change rate, M is not greater than N, and M is set to 5 in this embodiment. The calculation formula of the temperature change rate is dT / dt equal to M times the sum of the time series and the temperature value product minus the product of the time series sum and the temperature value sum, and then divided by M times the square sum of the time series minus the square of the time series sum. The time series t_i and the corresponding temperature value T_i are taken from the last M sampling points.

[0030] When the current temperature T_current is within the phase transition temperature range and the absolute value of the temperature change rate is less than a preset rate threshold K1, it is determined that the phase change material is in an effective adjustment state, otherwise it is determined that the phase change material is insufficient in adjustment capacity. The physical meaning of this determination is that when the temperature is within the phase transition interval and changes slowly, it indicates that the phase change material is absorbing or releasing heat through the phase change process to effectively buffer temperature fluctuations, otherwise if the temperature deviates from the phase transition interval or the change rate is too fast, it indicates that the buffering capacity of the phase change material is insufficient and the active adjustment device needs to be involved.

[0031] The system uses a time series prediction model to predict the temperature and humidity change trend in the future L sampling periods in advance, L is not less than 5, and in this embodiment, L is set to 10, i.e. 10 minutes in the future. For temperature prediction, a linear regression model is used, and the predicted temperature T_predict is equal to the regression coefficient a multiplied by the prediction time plus the regression coefficient b. The regression coefficients a and b are calculated according to the temperature history data by the least squares method. The coefficient a is equal to N multiplied by the sum of the product of the time series and the temperature value, minus the product of the sum of the time series and the sum of the temperature value, divided by N multiplied by the sum of the squares of the time series minus the square of the sum of the time series. The coefficient b is equal to the sum of the temperature value minus the coefficient a multiplied by the sum of the time series, divided by N. The humidity prediction H_predict uses the same method.

[0032] For the case where the temperature and humidity change law is relatively complex, the system can select an ARMA autoregressive moving average model. The expression of the ARMA(p, q) model is that the current temperature T(t) is equal to a constant term c plus the sum of the products of p autoregressive coefficients and the corresponding historical temperatures, plus the sum of the products of q moving average coefficients and the corresponding error terms, and finally plus the current error term. Among them, φ_1 to φ_p are autoregressive coefficients, θ_1 to θ_q are moving average coefficients, and ε(t) is a white noise error term. The model parameters are solved by Yule-Walker equation or maximum likelihood estimation method. The predicted value is T_predict which is equal to the constant term c plus the sum of the products of the autoregressive coefficients and the temperature values before the prediction time. In this embodiment, according to the calculation resources and real-time requirements, the linear regression model is preferred, and when it is detected that the temperature and humidity fluctuation is large, such as the standard deviation exceeding the threshold, the ARMA model is automatically switched to improve the prediction accuracy.

[0033] The system calculates the standard deviation of the historical prediction error as an indicator of prediction confidence. The standard deviation σ_e is equal to the sum of the squares of the prediction error divided by N and then taking the square root, where the prediction error e_i is equal to the actual temperature minus the predicted temperature. When the standard deviation is less than 0.5 degrees Celsius, the prediction model is considered reliable, and when the standard deviation is greater than 1.0 degrees Celsius, the system reduces the prediction weight and increases the proportion of real-time feedback control.

[0034] The system determines whether to intervene in advance according to the prediction result. First, the prediction deviation is calculated, the temperature deviation ΔT is equal to the absolute value of the difference between the predicted temperature and the target temperature, and the humidity deviation ΔH is equal to the absolute value of the difference between the predicted humidity and the target humidity. The target temperature T_target is equal to half of the sum of the upper and lower limits of the target temperature range, and the target humidity H_target is equal to half of the sum of the upper and lower limits of the target humidity range, and the target range is read from the specimen parameter library. When the predicted temperature is less than the lower limit of the target temperature or greater than the upper limit of the target temperature or the predicted humidity is out of the target humidity range, it is determined that intervention in advance is needed.

[0035] The linear extrapolation method is used to calculate the time t_reach required for the predicted temperature to reach the boundary of the target range. If the predicted temperature is lower than the target lower limit, the reaching time is equal to the target lower limit minus the current temperature divided by the temperature change rate, and if the predicted temperature is higher than the target upper limit, the reaching time is equal to the target upper limit minus the current temperature divided by the temperature change rate. When the predicted reaching time is less than or equal to 2 times the prediction window length, the control strategy is immediately executed, when the predicted reaching time is between 2 times and 4 times the prediction window length, the control strategy is executed at the time of the predicted reaching time minus one prediction window length, otherwise, no intervention is made and monitoring continues. The physical meaning of this mechanism is that when the temperature is predicted to exceed the target range in a short time, the control is started immediately, and when the predicted exceeding time is long, the control is started at an appropriate advanced time to avoid wasting energy due to premature intervention.

[0036] The system executes the hierarchical control strategy according to the temperature deviation, the state of the phase change material, and the judgment result of the intervention in advance. The first level response is passive adjustment priority, and the trigger condition is that the temperature deviation is less than the first temperature threshold and the phase change material is in an effective adjustment state. In this embodiment, the first temperature threshold is set to 0.5 degrees Celsius. At this time, the PWM duty cycle of the temperature adjustment heating piece and the humidity adjustment air outlet is set to 0% which is the closed state. The physical meaning is that when the temperature deviation is small and the phase change material is working effectively, the passive adjustment material can rely on the natural adjustment ability to maintain the temperature stable without starting the active device to achieve zero energy consumption adjustment.

[0037] The second level response is low-power active adjustment, and the triggering condition is that the temperature deviation is between the first temperature threshold and the second temperature threshold or the phase change material adjustment capacity is insufficient. In this embodiment, the second temperature threshold is set to 1.5 degrees Celsius. When the predicted temperature is lower than the target temperature, the PWM duty cycle of the heating sheet is set to 10% plus a proportional coefficient multiplied by the difference between the target temperature and the current temperature, and the duty cycle upper limit is limited to 30%. When the predicted temperature is higher than the target temperature, the cooling is needed by increasing the ventilation and heat dissipation, and the PWM duty cycle of the fan is set to 20% plus a proportional coefficient multiplied by the difference between the current temperature and the target temperature, and the duty cycle upper limit is limited to 40%. The proportional coefficient k_P is set to 2 in this embodiment, realizing simple proportional control. The physical meaning is that when the temperature deviation is moderate or the phase change material buffer capacity is insufficient, the active adjustment device is started but kept at low power, and the waste heat and cold effect of the phase change material is used to realize the synergistic adjustment of high efficiency and energy saving.

[0038] The third level response is full-power active adjustment plus alarm, and the triggering condition is that the temperature deviation is greater than the second temperature threshold. When the predicted temperature is lower than the target temperature, the PWM duty cycle of the heating sheet is set to 100% full-power operation, and when the predicted temperature is higher than the target temperature, the PWM duty cycle of the fan is set to 100% full-speed operation. At the same time, the system triggers an alarm signal to display warning information on the display screen and emits a beep, and records an abnormal event log. The physical meaning is that when the temperature deviation is large and the sample is at risk of exceeding the safety range, the active device is operated at full power for rapid adjustment and alarm to prompt the administrator to pay attention.

[0039] The humidity control adopts a similar hierarchical strategy, and the deviation threshold is set to a first humidity threshold of 5% and a second humidity threshold of 15%. The first level response is to maintain the fan off when the humidity deviation is less than 5% and the phase change material is effective, the second level response is that the fan works at a duty cycle of 20% to 40% when the humidity deviation is between 5% and 15% or the phase change material is insufficient, and the third level response is that the fan works at full speed when the humidity deviation is greater than 15%.

[0040] The system continuously optimizes the prediction model parameters by comparing the error between the actual temperature and the predicted temperature to realize self-adaptive learning. The prediction error e(t) is calculated as the actual temperature minus the predicted temperature at the current time. The exponential weighted average method is used to update the regression coefficients, the new coefficient a is equal to the old coefficient a plus the learning rate a multiplied by the prediction error and then multiplied by the time, and the new coefficient b is equal to the old coefficient b plus the learning rate a multiplied by the prediction error. The learning rate a is in the range of 0.01 to 0.1, and is set to 0.05 in this embodiment. A too large learning rate will cause the model to oscillate, and a too small learning rate will slow down the convergence speed.

[0041] To prevent abnormal values in the parameter update process, the coefficients a and b are reasonably tested and limited. When the absolute value of the new coefficient a is greater than 0.5, it is limited to within plus or minus 0.5, limiting the absolute value of the slope to no more than 0.5 degrees Celsius per minute. When the new coefficient b is less than negative 50 or greater than 150, it remains the old value and is not updated, because the intercept is beyond the physically reasonable range. The system automatically adjusts the learning rate according to the trend of the prediction error, and when the absolute value of the prediction error is less than 0.2 degrees Celsius, the learning rate is reduced to 0.02 to maintain stability, and when the absolute value of the prediction error is greater than 1.0 degrees Celsius, the learning rate is increased to 0.1 to speed up convergence, and under normal circumstances the learning rate is maintained at 0.05. The self-learning mechanism enables the prediction model to adapt to different environmental conditions, specimen types and seasonal changes, without the need for human intervention to maintain high prediction accuracy, and the prediction accuracy of the system will significantly improve after long-term operation.

[0042] The specimen parameter library is pre-stored in the memory of the master chip module 112, containing the optimal storage conditions of common specimen types. In some embodiments, the target temperature range of blood specimens is 2 to 8 degrees Celsius, and the target humidity range is 30% to 50%.

[0043] When the specimen is placed in the specimen compartment 16, the medical staff can let the system automatically identify the specimen type by scanning the barcode or two-dimensional code on the specimen container, or manually select the specimen type through the touch interface of the display screen, or input the specimen type code through the external keyboard. The system reads the corresponding control parameters from the parameter library according to the specimen type and performs adaptive adjustment. First, update the target temperature and humidity range, and use the read temperature range and humidity range for early intervention judgment. Then adjust the hierarchical control threshold, for temperature-sensitive specimens such as blood and microbiological culture specimens, reduce the temperature deviation threshold, the first temperature threshold is adjusted to 0.3 degrees Celsius and the second temperature threshold is adjusted to 1.0 degrees Celsius, for humidity-sensitive specimens such as tissue sections, reduce the humidity deviation threshold, the first humidity threshold is adjusted to 3% and the second humidity threshold is adjusted to 10%. Next, adjust the PWM duty cycle range, for specimens that need fast response, increase the power upper limit of the secondary response from 30% to 50%. Finally, adjust the rate threshold for phase change material state judgment.

[0044] In some implementations, in the application scenario of a certain hospital pediatric ward, after the nurse collects the blood samples of the children, the nurse puts the test tubes containing the samples into the sample storage device of the present application. The nurse automatically identifies the blood samples by scanning the bar code system on the test tubes and loads the control parameters from the parameter library, the target temperature is 4-6 degrees Celsius, the target humidity is 40%, the first time threshold is 30 minutes, and the second time threshold is 60 minutes. The system immediately starts the temperature and humidity control and adjusts the temperature of the sample cabin. After 30 minutes of storage, the background of the display screen turns yellow and displays a prompt message that the sample has been stored for 30 minutes and should be sent for inspection in a timely manner. The nurse sees the prompt and notifies the laboratory transport personnel. If the sample cannot be sent for inspection in time due to special circumstances, the system triggers a secondary alarm buzzer and displays a double warning that the sample has been stored for 60 minutes on the display screen, and sends an alarm message to the nurse station workstation and the laboratory information system. The laboratory immediately arranges personnel to come to take the sample, avoiding the quality degradation of the sample due to overtime storage.

[0045] The whole system continuously improves the prediction accuracy through a self-learning optimization mechanism, realizes traceable management of the whole life cycle data of the samples through a wireless communication module, provides data support for sample quality monitoring and quality improvement for medical institutions, and has important clinical application value and broad market promotion prospects.

Claims

1. A multifunctional intelligent medical specimen temporary storage device, characterized in that, The application relates to a specimen storage box, which comprises a specimen storage box body (11), a main control chip module (112), a temperature and humidity sensor group (12), passive temperature and humidity adjusting material (14), a temperature adjusting heating sheet (13), a humidity adjusting air outlet (15), a magnetic child lock device and an unlocking device (17). The specimen storage box body (11) comprises a specimen storage box cover (111), a bottom plate (113) and a specimen cabin (16) enclosed by the specimen storage box cover (111) and the bottom plate (113). The main control chip module (112) is arranged in the specimen storage box body (11). The temperature and humidity sensor group (12) is arranged in the specimen cabin (16) and electrically connected with the main control chip module (112). The passive temperature and humidity adjusting material (14) is arranged in the specimen cabin (16) and comprises phase change material and humidity adjusting material. The temperature adjusting heating sheet (13) is arranged in the specimen cabin (16) or on the bottom plate (113) and electrically connected with the main control chip module (112). The humidity adjusting air outlet (15) is arranged on the specimen storage box body (11) and electrically connected with the main control chip module (112). The magnetic child lock device is arranged between the bottom plate (113) and the specimen cabin (16) and comprises a buckle groove arranged on the edge of the bottom plate (113) and a slidable buckle piece, and the specimen cabin (16) is locked by magnetic adsorption. The unlocking device (17) is electrically connected with the main control chip module (112) and used for controlling the on-off state of the magnetic child lock device. The main control chip module (112) stores a control program, and the control program realizes the following steps when executed: Step S1: periodically obtaining a current temperature value T_current and a current humidity value H_current from the temperature and humidity sensor group (12) and storing a temperature history data sequence and a humidity history data sequence by using a sliding window method; Step S2: calculating the temperature change rate dT / dt based on the temperature history data sequence; when T_current is within the preset phase change temperature range and lower than the preset rate threshold, determining that the phase change material is in an effective regulation state; Step S3: based on the temperature history data sequence and the humidity history data sequence, predicting a temperature prediction value T_predict and a humidity prediction value H_predict by using a time sequence prediction model; Step S4: judging whether T_predict or H_predict exceeds a target temperature range or a target humidity range, calculating a temperature deviation AT or a humidity deviation AH if exceeding, and determining an early intervention time according to the deviation arrival time; Step S5: according to the temperature deviation AT, the phase change material state and the early intervention judgment result, executing a hierarchical control strategy: when the temperature deviation is less than a first threshold value and the phase change material is in an effective adjusting state, maintaining the closing state of the temperature adjusting heating sheet (13) and the humidity adjusting air outlet (15); when the temperature deviation is between the first threshold value and a second threshold value or the phase change material adjusting capacity is insufficient, controlling the temperature adjusting heating sheet (13) or the humidity adjusting air outlet (15) to work at a low duty cycle by using a PWM pulse width modulation mode; when the temperature deviation is greater than the second threshold value, controlling the temperature adjusting heating sheet (13) or the humidity adjusting air outlet (15) to work at a high duty cycle and triggering an alarm signal. Step S6: calculating a prediction error e(t) = T_current(t) - T_predict(t), and adjusting parameters of the time series prediction model according to the prediction error by using an adaptive algorithm. 2.The multifunctional intelligent medical specimen temporary storage device according to claim 1, characterized in that, The specimen parameter library is pre-stored in the memory of the master chip module (112), and contains multiple specimen types and corresponding target temperature ranges , target humidity ranges and control strategy parameters; The control program further implements a specimen type adaptive control step: receiving specimen type information; reading a corresponding target temperature range and target humidity range from the specimen parameter library according to the specimen type information; and dynamically adjusting the first threshold value, the second threshold value, and the PWM duty cycle range in step S5 according to the control strategy parameters corresponding to the specimen type. 3.The multifunctional intelligent medical specimen temporary storage device according to claim 1, characterized in that, In step S3, the time series prediction model uses a linear regression model or an ARMA autoregressive moving average model. When a linear regression model is employed, the prediction expression is: where a and b are regression coefficients. In step S6, an exponential weighted moving average (EWMA) algorithm is used to update the parameters of the prediction model. 4.The multifunctional intelligent medical specimen temporary storage device according to claim 1, characterized in that, In the step S2, the preset phase change temperature range According to the phase change temperature of the phase change material in the passive temperature and humidity adjusting material (14). 5.The multifunctional intelligent medical specimen temporary storage device according to claim 1, characterized in that, The specimen storage box cover (111) is provided with a display screen, and the control program further implements the following steps: displaying the current temperature value T_current, the current humidity value H_current, and the specimen storage duration Δt in real time; recording the specimen entry time t0, and calculating the specimen storage duration Δt = t - t0; and triggering a hierarchical prompt information or an alarm signal when the Δt reaches a preset duration threshold. 6.The multifunctional intelligent medical specimen temporary storage device according to claim 1, characterized in that, In step S4, the determination method of the early intervention time is: calculating the predicted time t_reach required for the temperature prediction sequence T_predict to reach the boundary of the target temperature range; and determining the intervention time of executing the hierarchical control strategy of step S5 according to the size of t_reach. 7.The multifunctional intelligent medical specimen temporary storage device according to claim 1, characterized in that, The main control chip module (112) further includes a wireless communication module, and the control program uploads the temperature historical data sequence, the humidity historical data sequence, the alarm record, and the operation log to a cloud server or a local server through the wireless communication module. 8.The multifunctional intelligent medical specimen temporary storage device according to claim 1, wherein, In step S5, the hierarchical control strategy of humidity is: when the humidity deviation ΔH is less than the first humidity threshold value and the phase change material is in an effective adjustment state, maintaining the closed state of the humidity adjustment air outlet (15); when the humidity deviation ΔH is between the first humidity threshold value and the second humidity threshold value or the phase change material adjustment capacity is insufficient, controlling the fan in the humidity adjustment air outlet (15) to work at a low duty cycle by PWM pulse width modulation; and when the humidity deviation ΔH is greater than the second humidity threshold value, controlling the fan in the humidity adjustment air outlet (15) to work at a high duty cycle. 9.The multifunctional intelligent medical specimen temporary storage device according to claim 1, wherein, The passive temperature and humidity adjustment material (14) is prepared by a vacuum impregnation method, and a composite structure is formed by impregnating a phase change material into the pores of a porous humidity adjustment material; the phase change material is selected from a paraffin-based phase change material, a fatty acid phase change material, or an alkane phase change material; and the humidity adjustment material is selected from silica gel or molecular sieve.

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