Intelligent medical object transfer trolley special for operating room

Abstract

The invention provides an intelligent medical object transfer trolley special for an operating room, and relates to the technical field of medical instrument data processing. The transfer trolley comprises a trolley body, a clean article bearing area, a waste storage area, a weighing sensing module and a central control unit, wherein the clean article bearing area and the waste storage area are arranged on the trolley body; the central control unit is configured to execute a surgical material closed loop verification logic. According to the novel intelligent transfer trolley, fluid interference can be overcome through algorithm logic, high-precision recognition is achieved through low-cost hardware, and safety verification logic based on physical data is constructed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical instrument data processing, and particularly relates to a special intelligent medical material transfer trolley for operating rooms. BACKGROUND

[0002] At present, in the complex environment of modern surgery, the management of operating room materials has long been faced with the contradiction that efficiency and safety cannot be reconciled. Among them, the counting and checking of surgical instruments and consumables are the most critical links in the preoperative preparation and postoperative closing stages. According to the statistical data of the Global Patient Safety Alliance, although a strict manual counting system is implemented, medical accidents of gauze, cotton balls and microsurgical instruments left in the patient's body still occur with a certain probability. Such accidents not only bring extremely serious secondary injury to patients, even endanger life, but also bring huge legal risks and economic compensation pressure to hospitals and medical staff.

[0003] In the prior art, in order to assist manual counting, some auxiliary systems based on electronic weighing or radio frequency identification (RFID) have appeared. However, these technologies have exposed significant limitations in actual clinical application.

[0004] Firstly, although the RFID technology can realize unique identification, in the high-humidity and liquid-rich environment of the operating room, the ultra-high frequency signal is easily shielded or interfered by human tissues and metal instruments. More seriously, for gauze, hemostatic cotton and other soft consumables, once they absorb a large amount of blood and fold and agglomerate, the reading rate of the RFID tag will be greatly reduced, resulting in missed reading phenomenon, which has significant safety hazards in the zero-error requirement of medical scene.

[0005] Secondly, the traditional electronic weighing technology faces the problem of fluid mass interference in physics. During the operation, the gauze, bandage and other consumables used will absorb a large amount of blood, body fluid and physiological saline for flushing. Physical laws determine the conservation of mass, but in the counting logic of the operation, this conservation is broken: the total weight of the recovered items is often much larger than the dry weight when it is put in. The existing weighing transfer trolley can only provide static weight reading and cannot distinguish the weight of the items themselves and the weight of the absorbed liquid. If the linear logic of subtracting the starting weight from the ending weight is simply adopted, the weight of the consumables filled with liquid may cover up the weight of a missing instrument (i.e. the increased liquid weight exactly offsets the weight of the missing instrument in numerical value), so as to cause the system to misjudge that the counting is correct, thereby burying a major safety hazard.

[0006] Furthermore, the in-hospital transportation of medical waste is a weak link in the control of hospital infections. The existing transport vehicles are mostly simple physical containers, lacking intelligent process control. During storage, bacteria rapidly multiply at suitable temperatures. Current disinfection methods rely on manual spraying or simple timed spraying, which not only depends on the compliance of medical staff, but also cannot dynamically adjust the amount of disinfectant according to the actual amount of waste generated, often resulting in waste of disinfectant due to empty spraying or incomplete disinfection due to insufficient spraying. In addition, the moving authority of the transport vehicle lacks a mandatory link with the contamination state, and it is not uncommon for contaminated vehicles to be mistakenly pushed into clean areas or transported in violation of the rules before sealing and packaging is completed, causing the secondary spread of pathogens.

[0007] Finally, in terms of the balance between hardware cost and accuracy, in order to reduce the threshold for the popularization of medical equipment, some designs tend to use lower-cost sensor materials such as acrylic elastic beams. However, acrylic, as a polymer material, has significant viscoelastic creep and hysteresis characteristics, and is sensitive to stress relaxation. During a surgery that lasts for several hours, a constant load can cause physical drift in the readings, and without a targeted compensation algorithm, the measurement accuracy of such devices will not meet medical-grade standards.

[0008] In summary, there is an urgent need for a new intelligent transport vehicle that can overcome fluid interference through algorithmic logic, achieve high-precision identification using low-cost hardware, and build a safety verification logic based on physical data. SUMMARY

[0009] The core purpose of the present application is to provide an intelligent medical material transport vehicle dedicated for operating rooms, which solves the technical pain points of being unable to eliminate the interference of body fluid weight gain, being unable to identify the material quality at low cost, and lacking a biological safety forced closed loop through the deep innovation of software and hardware cooperation.

[0010] The present application provides an intelligent medical material transport vehicle dedicated for operating rooms, comprising a vehicle body, a clean article carrying area and a waste storage area arranged on the vehicle body, a weighing sensor module, and a central control unit. The central control unit is configured to execute a surgical material closed loop verification logic, which comprises: An initialization step: before the start of the operation, obtaining the reference dry weight data of the surgical instrument package And calculating the weighted biological fluid absorption coefficient The weighted biological fluid absorption coefficient is defined as: Wherein is the dry weight of the th absorbent consumable in the surgical package, is the specific absorption coefficient corresponding to the consumable; Real-time monitoring steps: During the operation, the total weight reduction of the clean item carrying area is monitored through the weighing sensor module. The total increase in weight of the waste storage area ; Endpoint verification step: In response to the end of surgery signal, calculate the total mass balance difference. The total mass balance difference ; Logical decision steps: If the total mass balance difference is... If the value is less than zero, it is determined to be a material loss state and a first-level alarm signal is triggered; if the total mass balance difference is... If the result is greater than or equal to zero, then the weight gain rate is further calculated. ,in When the weight gain rate Within the allowable deviation range Inner time, that is If the verification is successful, the second-level abnormal alarm signal will be triggered.

[0011] Optionally, the weighing sensing module includes a strain gauge sensor and an acrylic elastic beam; the central control unit is further configured to execute material impact characteristic recognition logic, the logic including: When a step change in weight is detected in the waste storage area, the system automatically switches to high-frequency sampling mode to collect transient oscillation waveform data of the weighing sensor output signal within a preset time window. Extract the characteristic parameters of the waveform data, wherein the characteristic parameters include at least the oscillation settling time and the first wave overshoot rate; The extracted feature parameters are compared with the pre-stored material fingerprint database. If the comparison results show that the object being thrown conforms to the characteristics of a rigid metal body and is currently in non-mechanical recycling mode, the system will immediately issue a false disposal warning.

[0012] Optionally, a temperature and humidity sensor is provided around the weighing sensor module; the central control unit also has built-in multi-dimensional environmental and rheological compensation logic to correct the physical drift of the acrylic elastic beam. The multidimensional environmental and rheological compensation logic includes: within a static period during which the load is kept constant, the deformation error and environmental drift generated over time are calculated in real time based on the rheological model of the acrylic material and the preset thermal and hygroscopic expansion model. Combined with the current temperature and humidity data, the deformation error and environmental drift are dynamically subtracted from the current weighing reading to maintain the stability of the measurement reference during long-term surgery.

[0013] Optionally, the transfer vehicle further includes a disinfection spray device installed inside the waste storage area; the central control unit executes adaptive incremental disinfection logic, specifically including: Real-time monitoring of the weight increase in the waste storage area; Whenever a new weight is detected that exceeds a preset trigger threshold and the reading stabilizes, a pulse width modulation control signal is generated to drive the disinfection spray device. The duty cycle of the pulse width modulation control signal is proportional to the added weight, so as to achieve dynamic matching between the amount of disinfectant sprayed and the amount of waste input.

[0014] Optionally, the transfer vehicle includes wheels with an electronically controlled locking mechanism; the central control unit is configured to execute biosafety physical interlock logic, including: Monitor the current total weight of the waste storage area; If the current total weight is greater than zero, the system automatically marks the transport vehicle as biologically contaminated and activates the electronic locking mechanism to lock the moving wheels; Only after receiving a signal that the endpoint verification step has passed and confirming that the sealed door of the waste storage area is closed, is the electronic locking mechanism released, allowing the transfer vehicle to move.

[0015] Optionally, in the logical decision step, the upper limit of the allowable deviation range is obtained by multiplying the initial consumable weight of the clean item carrying area by the weighted biofluid absorption coefficient.

[0016] Optionally, the central control unit also includes disinfectant remaining volume prediction logic; The logic estimates the remaining disinfectant volume in real time based on the cumulative duration of historical spraying and the pump's flow parameters. If the estimated amount of remaining disinfectant is insufficient to cover the theoretical maximum disinfection capacity required to cover the remaining capacity of the current waste storage area, the system is prohibited from recording new waste input actions or issuing maintenance requests for replenishing the liquid.

[0017] Optionally, it also includes a data communication module for performing the entire lifecycle data on-chain steps; The system packages the surgical identification code, baseline dry weight data, final mass balance difference, and abnormal alarm records throughout the surgical process into an encrypted data packet; After successful verification at the endpoint, the data packet is transmitted to the hospital information management system via wireless protocol as an electronic certificate for medical waste handover and surgical safety verification.

[0018] Optionally, the material fingerprint database includes at least three reference waveform features, corresponding to the high-damping long rise time feature of blood-stained cotton fabric, the low-damping short rise time feature of stainless steel surgical instruments, and the medium-damping feature of disposable plastic consumables.

[0019] Optionally, the central control unit is connected to an analog-to-digital converter circuit with programmable gain function. The central control unit automatically switches between a large range mode during the surgical preparation stage and a high sensitivity mode during the surgical procedure by dynamically adjusting the gain parameters of the analog-to-digital converter circuit.

[0020] The present invention has achieved the following beneficial effects: By introducing biofluid absorption coefficients and asymmetric verification logic, this invention successfully transforms uncontrollable fluid weight gain into a calculable safe threshold range. This logic establishes the rule of "reporting all changes in weight and assessing the proportion of changes in weight," effectively solving the fundamental problem that traditional electronic scales cannot distinguish between a hemostat and a piece of gauze soaked in blood, and significantly reducing the risk of Respiratory Syndrome Infection (RSI).

[0021] This invention creatively utilizes the high damping and easily deformable properties of low-cost acrylic materials, which are often considered a drawback, transforming them into a physical fingerprint for identifying the material of objects. This not only significantly reduces hardware costs by eliminating the need for expensive alloy steel sensors or cameras, but also enables the interception of accidentally thrown metal devices.

[0022] In response to the creep characteristics of acrylic materials, the built-in rheological compensation algorithm can calculate and deduct deformation errors caused by the passage of time in real time, ensuring that the system maintains a high-precision medical-grade benchmark during long-duration surgeries, thus solving the practicality problem of low-cost materials.

[0023] By physically interlocking the movement permission of the wheels with the weight of the waste and the sealing status, this invention upgrades the hospital infection control standard from a soft system to a hard physical constraint, effectively preventing the possibility of contaminated vehicles moving illegally and blocking the chain of infection within the hospital.

[0024] The adaptive spraying logic based on weight increments ensures that every new piece of waste receives a precisely matched amount of disinfectant coverage, guaranteeing disinfection effectiveness while avoiding liquid leakage and environmental pollution caused by over-spraying.

[0025] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0026] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0027] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the structure of the intelligent transfer vehicle of the present invention; Figure 2 This is a schematic diagram of the structure of the heavy-duty pallet of the present invention; Figure 3 This is a schematic diagram of the weighing sensor module of the present invention; Figure 4 This is a schematic diagram of the control circuit of the present invention, which includes the HX711 chip. Detailed Implementation

[0028] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0029] Example 1: like Figures 1 to 4 As shown, the intelligent medical supply transport vehicle for operating rooms provided by this invention has an ergonomically designed mobile workstation as its physical carrier. The vehicle frame is made of 304 medical-grade stainless steel, which has excellent corrosion resistance and easy cleaning properties, making it suitable for the frequent disinfection and wiping environment of the operating room. Four silent omnidirectional wheels are installed at the bottom of the vehicle, with at least two diagonal wheels integrating an electromagnetic braking mechanism controlled by a central processing unit, forming the basis of physical interlocking.

[0030] The upper part of the vehicle is designed as an open cleanroom storage area for sterile surgical packs, instrument boxes, and unopened consumables. The first set of high-precision weighing sensor modules is embedded in the supporting structure below this area. The lower interior of the vehicle is designed as a closed waste storage area, isolated from the outside by a door with sealing strips and an electronic lock, for collecting blood-stained gauze, cotton balls, and disposable medical waste generated during surgery. A second set of weighing sensor modules is installed at the bottom of this area. A digital display and touch-screen control panel are integrated on the side of the vehicle as the human-machine interface.

[0031] The system operates within a central control unit (MCU), which integrates a microprocessor based on the ARM Cortex-M series. To handle the weak weight signals, the system employs the HX711 as a 24-bit high-precision A / D converter chip. Figure 4As shown, the HX711 chip communicates with the central control unit via the PD_SCK and DOUT pins. U1 (ETA6002) is a power management chip, and U2 (ME6211) is a low dropout linear regulator that provides a highly stable 3.3V excitation voltage to the weighing module.

[0032] To address the core pain point of weight conservation issues caused by fluid absorption during surgery, this system executes the following logic: Initialization and dynamic gain settings: During surgical preparation, medical staff place the heavy surgical instrument packs (potentially weighing over 10 kg) into the clean area. At this time, the central control unit sends a command to the HX711 chip via the control bus, setting its internal programmable gain amplifier (PGA) to 64x gain (channel B or low gain mode) to accommodate large input ranges and prevent signal saturation overflow. The system records the total weight at this moment as the baseline dry weight. Simultaneously, medical staff scan the barcode on the surgical pack, and the system retrieves the corresponding biofluid absorption coefficient from a pre-set database. Specifically, the central control unit's storage space contains a pre-set associated mapping database. This database includes a surgical pack ID-Bill of Materials (BOM) mapping table. The BOM table details the name, material properties (absorbent / non-absorbent), and unit dry weight of each type of consumable contained in the surgical pack. ) and the standard absorption coefficient corresponding to this material ( The system dynamically calculates the weighting coefficients based on the data in this table.

[0033] This coefficient is an empirical value; for example, for an abdominal surgical kit, it might be set to 5, meaning that the consumables are allowed to weigh up to 5 times their own weight. For instance, a cesarean section surgical kit weighing 5000g might contain 4800g of stainless steel instruments (excluding absorbent components). ) and 200g of gauze (absorbent assembly, During the initialization process, the system automatically identifies the total dry weight of the aspiration consumables in the surgical kit based on the Bill of Materials (BOM) indexed by the barcode. The weighted tolerance coefficient is calculated based on 200g (excluding metal weight). During the verification phase, if a doctor removes a piece of gauze weighing 5g dry, absorbs blood, and then discards it into the waste disposal area weighing 25g... , ), calculated weight gain rate .because The system determines the outcome to be reasonable. Conversely, if a metal object is detected as being mistakenly thrown in, or... If the value is abnormally high, an alarm is triggered. This logic effectively avoids the dilution effect of the large weight of metal instruments on the liquid absorption coefficient.

[0034] Once the surgical procedure begins, when the system detects small and frequent changes in load (object handling), it automatically switches the HX711 gain to 128 times (channel A high sensitivity mode) to achieve precise gram-level resolution of weight changes in a single piece of gauze (approximately 2-5g).

[0035] Real-time monitoring and two-way data stream tracing: The system scans the sensors in two areas in parallel at a frequency of 10Hz. As the weight of the clean area decreases, the system accumulates and records the total weight reduction. When the weight of the waste area increases, the total increase in weight is accumulated and recorded. ).

[0036] Asymmetric endpoint verification logic: When the surgery ends and a count command is triggered, the system no longer executes the simple count command. Instead of verification, it performs asymmetric decision-making: Step 1: Calculate the total mass balance difference .

[0037] Step 2: Determine absolute loss. If (That is, the recovered weight is less than the input weight). According to the law of conservation of mass in physics, this means that some matter has disappeared. In the closed environment of an operating room, this most likely indicates that instruments or gauze have been left inside the patient's body. At this point, the system ignores any coefficients and immediately triggers the highest level audible and visual alarm (Level 1 alarm), and locks the screen to display "Severe: Item Missing" until manually deactivated.

[0038] Step 3: Relative weighting verification. If The system calculates the current weight gain rate. The system will use this ratio. With the preset biofluid absorption coefficient Compare them.

[0039] like The system determines that the increased weight is within a reasonable range of body fluid absorption and displays "Verification passed (green)".

[0040] like The system determined that the weight gain was abnormal and that non-surgical items (such as a mobile phone or saline bottle mistakenly placed in the bag by a doctor) might have been mixed in, triggering a second-level alarm and requiring an inspection of the waste bag.

[0041] Through this logic, this embodiment cleverly eliminates residual risks and avoids false alarms caused by normal fluid aspiration in surgical scenarios where physical mass is not conserved.

[0042] Furthermore, to construct an accurate pre-defined database of biofluid absorption coefficients (α), this invention employs a standardized experimental measurement method. This method is applied to different types of surgical consumables, and the specific steps are as follows: Sample preparation and dry weight measurement: Randomly select a sufficient number of samples (e.g., 100 tablets) from an unopened batch of consumables, stabilize them under standard conditions (e.g., temperature 23±2℃, relative humidity 50±5%), and record their precise initial dry weight (W). dry ).

[0043] Simulated absorption experiment: Prepare a test liquid that simulates a surgical environment. Preferably, use synthetic blood conforming to industry standards or anticoagulated animal blood, maintained at a temperature close to that of the human body (37°C). Completely immerse the sample in the test liquid until saturation absorption is achieved (e.g., the weight increase tends to stabilize after continuous immersion).

[0044] Wet weight measurement and standardized dripping: After removing the sample, a standardized dripping procedure is performed. For example, the sample is suspended on a support frame and allowed to drip naturally under gravity until no significant leakage occurs (e.g., the interval between two consecutive drips exceeds 10 seconds), and then its wet weight (W) is recorded. wet ).

[0045] Coefficient Calculation and Statistical Setup: Calculate the absorption ratio R = (W) for each sample. wet - W dry ) / W dry Repeated experiments were conducted on the same type of consumables. To cover clinical procedural biases and ensure safety redundancy, the final biofluid absorption coefficient α was set as the upper limit of the statistically high confidence interval of the experimentally obtained absorption ratio, for example, by using the mean plus three standard deviations (Mean+3σ), or by using the 95th percentile (P95).

[0046] Example 2: In this embodiment, the weighing sensing module does not use expensive alloy steel elastomers, but instead uses acrylic to make an elastic beam. Although acrylic is not as stable as metal in terms of measurement, as a polymer, it has extremely high mechanical damping. This means that when an object impacts an acrylic beam, the way its vibration energy is dissipated is completely different from that of a metal beam. This invention utilizes this characteristic, which is usually considered a disadvantage, to transform it into a "tactile fingerprint" for identifying the material of an object.

[0047] The central control unit continuously monitors the sensor data stream at the waste inlet.

[0048] When the central control unit detects a step change in the weight reading of the waste storage area exceeding a preset threshold (e.g., 10g) within 200ms, it immediately sends a command to the HX711 chip via the GPIO pin to switch its data output rate from the default 10Hz high-precision mode to the 80Hz high-speed sampling mode.

[0049] Although an 80Hz sampling rate cannot capture microsecond-level acoustic impact signals, this invention utilizes the low-frequency mechanical response characteristics of a 'spring-mass-damping' system composed of an acrylic elastic beam and a waste container. When an object is thrown in, this mechanical system generates macroscopic low-frequency structural oscillations between 3Hz and 8Hz. An 80Hz sampling rate is sufficient to completely capture the waveform envelope of this low-frequency oscillation.

[0050] The central control unit intercepts a continuous sequence of sampled data within 1.5 seconds after the input action and executes the following feature extraction logic: Extracting the oscillation settling time ): Defined as the period from the moment the weight step occurs until the amplitude of the sensor output signal fluctuation remains continuously at the final steady-state value. The time required within the error band. Because metal instruments are rigid bodies, momentum transfer is highly efficient at the moment of impact, and they lack inherent deformation damping, leading to prolonged mechanical aftershocks in the system. The latter is relatively long; while soft consumables such as blood-stained gauze, as high-damping loads, can quickly absorb vibration energy, that is... Extremely short.

[0051] Extracting the first-wave overshoot (Max Overshoot) ): Calculate the reading of the first peak in the oscillating waveform. With final stable weight The ratio relationship: The initial overshoot triggered by a rigid collision is significantly higher than that triggered by a soft collision.

[0052] The system compares the extracted feature parameters with the pre-stored fingerprint thresholds: Material Type Ring-down Stability Time (Ts) First Wave Overshoot Ratio (Mp) System Determination Blood-soaked gauze / dressing Short (< 400 ms) Low (< 10%) Pass (over-damped signature) Stainless steel surgical instruments Long (> 800 ms) High (> 25%) Trigger false alarm (under-damped signature) Disposable plastic consumables Medium (~ 600 ms) Medium (~ 15%) Pass By transforming microscopic acoustic recognition into macroscopic mechanical damping recognition, this invention achieves effective interception of mistakenly thrown metal devices without increasing the cost of high-speed ADC hardware.

[0053] Example 3: In this embodiment, a high-precision digital temperature and humidity sensor (such as the SHT3x series) is integrated into the peripheral circuit of the weighing sensor module to collect the temperature of the microenvironment in which the sensor is located in real time. ) and relative humidity ( ).

[0054] Acrylic materials are viscoelastic; when subjected to a constant external force, their polymer chains undergo slow slippage and rearrangement, resulting in a macroscopic increase in deformation over time, known as "creep." In load cells, this manifests as the output electrical signal slowly drifting over time after a fixed weight is placed on it (typically showing a slight increase or decrease in weight, depending on the strain gauge's placement).

[0055] To eliminate this error, the central control unit incorporates a viscoelastic creep compensation model. This model is based on the Kelvin-Voigt rheological model.

[0056] The logical flow is as follows: State recognition: The system determines whether the sensor is in a static load holding state (i.e., the object has not been moved after being placed) by detecting the variance of the weight data.

[0057] Timing and Calculation: Once static retention is confirmed, the system starts an internal timer. The compensation algorithm is based on the current load weight. and the specific creep coefficient of the material Real-time calculation of the theoretical error caused by creep The formula is: ,in The relaxation time constant is τ. To ensure the accuracy of the viscoelastic creep compensation logic, the rheological parameters of the acrylic elastic beam used must be accurately measured, especially the relaxation time constant (τ). It should be noted that the relaxation time constant in the above model... This data was obtained through the factory static calibration procedure. During the quality inspection phase of the transport vehicle production, the system automatically performs a constant load calibration lasting up to 2 hours, records the creep curve output by the sensors, and uses the least squares method to backfit the specific values ​​of the acrylic beam of the equipment. The value is then fixed in the MCU to eliminate batch variations in materials.

[0058] This invention uses a standard static creep test method to obtain this parameter, and the specific steps are as follows: Experimental environment control: The weighing sensor module is placed in a constant temperature environment (e.g., maintained at 25°C, which is common in operating rooms) to eliminate the influence of temperature changes on material properties.

[0059] Constant load application and data acquisition: A known, constant standard load (F) is applied to the sensor. Immediately after the load is applied, the deformation readings output by the sensor are continuously recorded as a curve (creep curve) over time. The acquisition process should continue for a sufficiently long period, such as 8 hours.

[0060] Model fitting and parameter extraction: The collected time series data are fitted with the theoretical formula of the Kelvin-Voyt model. Nonlinear least squares methods (such as the Levenberg-Marquardt algorithm) are used to perform regression analysis on the experimental data to find the value τ that minimizes the sum of squared errors between the model predictions and the measured values.

[0061] Through this calibration process, the system can accurately parameterize the material properties of specific sensors, ensuring the effectiveness of the compensation algorithm.

[0062] Environmental drift and dynamic correction: Besides creep error, acrylic material has a large coefficient of thermal expansion and a certain degree of hygroscopicity. To eliminate zero-point drift caused by environmental factors, the central control unit incorporates a thermal and hygroscopic expansion model. The system calculates the temperature based on real-time data (…). ) and humidity ( ), calculate environmental drift .

[0063] The calculation formula is: .in, and The reference temperature and humidity are those used for factory calibration. and These are the temperature drift coefficient and humidity drift coefficient of acrylic material, respectively (measured using an environmental test chamber).

[0064] Finally, the system outputs the weight reading. At that time, multi-dimensional compensation calculations are performed, and the original sampled values ​​are analyzed in real time. Subtract creep error and environmental drift .

[0065] The revised final formula is: .

[0066] Through this real-time software-level correction, the present invention eliminates the impact of temperature fluctuations and humidity changes on the baseline of low-cost sensors, ensuring that the baseline data for instrument counting remains medical-grade accurate throughout a surgical procedure that can last for several hours.

[0067] Example 4: The waste storage area of ​​the transfer vehicle is equipped with miniature atomizing nozzles installed at the top, which are connected to a disinfectant tank and a miniature high-pressure pump at the bottom via pipelines. To address the limitation of traditional timed disinfection methods that cannot match the actual amount of waste, this system implements adaptive incremental disinfection logic.

[0068] The system monitors the weight of the waste area in real time. Whenever a valid input event is detected (weight increase and stable reading), the system records the increased weight of that input. The system is based on The required disinfectant spray volume is calculated. For precise control, the system generates a pulse width modulation (PWM) signal to drive the water pump. The duty cycle D of the PWM signal is proportional to the added weight. To achieve precise dynamic matching between the disinfectant spray volume and the waste input volume, the proportionality coefficient (k) must be calibrated. The calibration method is as follows: Determine the unit disinfection dosage: Based on the technical specifications for medical waste disinfection, determine the minimum effective disinfectant dosage (V) required per unit mass of medical waste. min / m).

[0069] Pump flow characteristics were measured: The average flow rate (Q) of the miniature high-pressure pump in this system under different PWM duty cycles was measured. avg / D). This can be obtained by running the water pump at different duty cycles and measuring the volume of liquid discharged per unit time.

[0070] Calculation and verification of the proportionality coefficient k: The coefficient k should be set so that the duty cycle generated per unit weight of waste input drives the spray volume to meet the minimum effective disinfectant dosage. In practice, a known weight of simulated waste can be used to set the k value for spraying, and the disinfection coverage and effect can be evaluated using biological or chemical indicator cards. The k value can be fine-tuned based on the experimental results until the ideal disinfection effect is achieved without significant liquid redundancy.

[0071] For example, add a piece of gauze (5g) and spray for 0.2 seconds; add a bag of waste (500g) and spray for 3 seconds. This ensures that the surface of the newly added waste is completely covered by the disinfectant, while avoiding excessive liquid accumulation that could lead to leakage.

[0072] The system uses an integral estimation method to monitor the remaining disinfectant solution. The system records the historical cumulative operating time of the water pump. Combined with the nominal flow rate of the water pump Calculate the amount of liquid consumed. When the remaining liquid volume ( When the maximum liquid volume falls below the warning threshold (e.g., insufficient to support the disinfection needs of the remaining trash can capacity), the system will prohibit new waste disposal records (and lock if there is an electrically controlled lid) and issue a maintenance request to replenish the disinfectant. This eliminates the safety hazard of false disinfection caused by running the system without liquid.

[0073] Example 5: This system forcibly binds vehicle movement permissions to biometric security status.

[0074] Clean state: When the weight of the waste area is 0, the wheel electromagnetic lock is de-energized (or energized to unlock, depending on the fail-safe design), and the vehicle can move freely.

[0075] Contaminated State (Locked): Once the weight in the waste area is greater than 0, the system determines that the vehicle is contaminated. At this point, regardless of whether it is plugged in, the wheel electromagnetic locks immediately activate, locking the wheels. This physically prevents nurses during surgery from accidentally pushing the untreated waste cart into the corridor.

[0076] Transition Status (Unlocked): The wheel will only unlock if all of the following conditions are met: The surgery has ended.

[0077] The closed-loop verification logic for surgical materials passed (no instruments were lost).

[0078] The door sensor confirms that the sealed door is closed and locked.

[0079] Vehicles are only permitted to be pushed into the waste disposal room if both data flow and physical status are compliant.

[0080] The system is equipped with a Wi-Fi / NB-IoT communication module. Throughout the entire surgical procedure, the system locally encrypts and caches all critical data: surgical ID, baseline dry weight, timestamps and weights of each insertion / removal, abnormal records triggered by waveform recognition, disinfection spray records, and the final quality balance report.

[0081] Once the endpoint verification is successful, the system packages and uploads this data to the Hospital Information System (HIS) or a blockchain traceability platform. This provides the hospital with an immutable electronic certificate proving that the instruments used in the surgery were counted correctly and that waste was disposed of in compliance with regulations, greatly improving the transparency of medical management and the hospital's ability to withstand legal risks.

[0082] In summary, by organically combining the above embodiments, this invention upgrades the traditional medical transport vehicle into an intelligent terminal with sensing, thinking, and execution capabilities, comprehensively solving the core pain points in operating room material management.

[0083] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An intelligent medical supplies transport vehicle specifically for operating rooms, characterized in that, It includes a vehicle body, a clean goods carrying area and a waste storage area installed on the vehicle body, a weighing sensor module, and a central control unit; The central control unit is configured to execute closed-loop verification logic for surgical materials, the logic including: Initialization steps: Before the surgery begins, obtain the baseline dry weight data of the surgical instrument pack. And calculate the weighted biofluid absorption coefficient. The weighted biofluid absorption coefficient is defined as follows: ,in The first one in the surgical kit The dry weight of the liquid absorption consumables. This refers to the specific absorption coefficient corresponding to this consumable. Real-time monitoring steps: During the operation, the total weight reduction of the clean item carrying area is monitored through the weighing sensor module. The total increase in weight of the waste storage area ; Endpoint verification step: In response to the end of surgery signal, calculate the total mass balance difference. The total mass balance difference ; Logical decision steps: If the total mass balance difference is... If the value is less than zero, it is determined to be a material loss state and a first-level alarm signal is triggered; if the total mass balance difference is... If the result is greater than or equal to zero, then the weight gain rate is further calculated. ,in When the weight gain rate Within the allowable deviation range Inner time, that is If the verification is successful, the second-level abnormal alarm signal will be triggered.

2. The intelligent medical supply transport vehicle for operating rooms according to claim 1, characterized in that, The weighing sensing module includes a strain gauge sensor and an acrylic elastic beam; the central control unit is also configured to execute material impact characteristic recognition logic, the logic including: When a step change in weight is detected in the waste storage area, the system automatically switches to high-frequency sampling mode to collect transient oscillation waveform data of the weighing sensor output signal within a preset time window. Extract the characteristic parameters of the waveform data, wherein the characteristic parameters include at least the oscillation settling time and the first wave overshoot rate; The extracted feature parameters are compared with the pre-stored material fingerprint database. If the comparison results show that the object being thrown conforms to the characteristics of a rigid metal body and is currently in non-mechanical recycling mode, the system will immediately issue a false disposal warning.

3. The intelligent medical supply transport vehicle for operating rooms according to claim 2, characterized in that, Temperature and humidity sensors are installed around the weighing sensing module; the central control unit also has built-in multi-dimensional environmental and rheological compensation logic to correct the physical drift of the acrylic elastic beam. The multidimensional environmental and rheological compensation logic includes: within a static period during which the load is kept constant, the deformation error and environmental drift generated over time are calculated in real time based on the rheological model of the acrylic material and the preset thermal and hygroscopic expansion model. Combined with the current temperature and humidity data, the deformation error and environmental drift are dynamically subtracted from the current weighing reading to maintain the stability of the measurement reference during long-term surgery.

4. The intelligent medical supply transport vehicle for operating rooms according to claim 1, characterized in that, The transfer vehicle also includes a disinfection spray device installed inside the waste storage area; The central control unit executes adaptive incremental disinfection logic, specifically including: Real-time monitoring of the weight increase in the waste storage area; Whenever a new weight is detected that exceeds a preset trigger threshold and the reading stabilizes, a pulse width modulation control signal is generated to drive the disinfection spray device. The duty cycle of the pulse width modulation control signal is proportional to the added weight, so as to achieve dynamic matching between the amount of disinfectant sprayed and the amount of waste input.

5. The intelligent medical supply transport vehicle for operating rooms according to claim 1, characterized in that, The transfer vehicle includes wheels with an electronically controlled locking mechanism; The central control unit is configured to execute biosafety physical interlock logic, including: Monitor the current total weight of the waste storage area; If the current total weight is greater than zero, the system automatically marks the transport vehicle as biologically contaminated and activates the electronic locking mechanism to lock the moving wheels; Only after receiving a signal that the endpoint verification step has passed and confirming that the sealed door of the waste storage area is closed, is the electronic locking mechanism released, allowing the transfer vehicle to move.

6. The intelligent medical supply transport vehicle for operating rooms according to claim 1, characterized in that, In the logical decision step, the upper limit of the allowable deviation range is obtained by multiplying the initial consumable weight of the clean item carrying area by the weighted biofluid absorption coefficient.

7. The intelligent medical supply transport vehicle for operating rooms according to claim 4, characterized in that, The central control unit also includes disinfectant remaining volume prediction logic; The logic estimates the remaining disinfectant volume in real time based on the cumulative duration of historical spraying and the pump's flow parameters. If the estimated amount of remaining disinfectant is insufficient to cover the theoretical maximum disinfection capacity required to cover the remaining capacity of the current waste storage area, the system is prohibited from recording new waste input actions or issuing maintenance requests for replenishing the liquid.

8. The intelligent medical supply transport vehicle for operating rooms according to claim 1, characterized in that, It also includes a data communication module, used to perform the entire lifecycle data uploading process; The system packages the surgical identification code, baseline dry weight data, final mass balance difference, and abnormal alarm records throughout the surgical process into an encrypted data packet; After successful verification at the endpoint, the data packet is transmitted to the hospital information management system via wireless protocol as an electronic certificate for medical waste handover and surgical safety verification.

9. The intelligent medical supply transport vehicle for operating rooms according to claim 2, characterized in that, The material fingerprint database contains at least three baseline waveform features, corresponding to the high-damping long rise time feature of blood-stained cotton fabric, the low-damping short rise time feature of stainless steel surgical instruments, and the medium-damping feature of disposable plastic consumables.

10. The intelligent medical supply transport vehicle for operating rooms according to any one of claims 1 to 9, characterized in that, The central control unit is connected to an analog-to-digital converter circuit with programmable gain function. The central control unit automatically switches between a large range mode during the surgical preparation stage and a high sensitivity mode during the surgical procedure by dynamically adjusting the gain parameters of the analog-to-digital converter circuit.

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