403 results about "Pressure sensor array" patented technology

The invention discloses a hydropower station expansion tank water level prediction alarm method and system, belongs to the technical field of hydropower station automatic control, and aims to solve the technical problems of limited monitoring points, high false alarm rate, response delay and the like of a traditional hydropower station expansion tank water level alarm system. According to the invention, the multi-mode sensing network is constructed, and data of the pressure sensor array, the radar level meter and the float switch group are fused, so that space continuous monitoring is realized; a three-level sensing architecture is adopted, heterogeneous data is subjected to normalization processing, and dimensional differences are eliminated; the LSTM network is used for liquid level prediction, and a self-adaptive window adjustment mechanism is combined, so that the prediction flexibility and accuracy are improved; a DQN algorithm is adopted to optimize a control strategy, fine adjustment of the liquid level is achieved by adjusting the opening degree of the valve, the accuracy, timeliness and intelligent level of water level monitoring and alarming of the expansion water tank of the hydropower station are remarkably improved, the stability of the liquid level of the water tank is ensured, the system operation efficiency is optimized, the manual intervention requirement is reduced, and safety is improved.

The invention relates to the technical field of intelligent forming, in particular to an intelligent adjusting type medical cotton ball forming method and system.The intelligent adjusting type medical cotton ball forming method comprises the following steps that pressure data are collected through a distributed pressure sensor array, pressure feature vectors are generated through Gaussian filtering denoising, a pressure change trend is analyzed based on the feature vectors, and a gradient adjusting instruction is output; and controlling the valve to adjust air pressure to obtain compensation parameters, driving the servo motor to adjust a mold gap, collecting offset data to generate a feedback signal, and inputting a neural network to evaluate a forming result in combination with feedback and adjustment instructions. According to the method, a distributed sensor array collects data, multi-dimensional denoising improves feature extraction, a dynamic function analyzes a pressure trend, an offset adjustment parameter is identified, closed-loop compensation is realized through cooperative control, a displacement sensor feeds back gap change, parameter modeling optimizes precision consistency, a convolutional network extracts time sequence features, and a self-adaptive system is constructed through fusion analysis. And intelligent prediction and optimization of the forming quality are realized.

The invention discloses a pressure injury risk early warning method and equipment, and relates to the technical field of medical monitoring instruments. The pressure sensor array layout can be self-adaptive to the body shape of a patient, a key osseous process part is covered, no monitoring dead angle is ensured, a temperature compensation mechanism is built in, environmental interference is reduced, the measurement precision is improved, an abnormal pressure threshold value can be dynamically set based on individual medical record data, data verification is performed before early warning is triggered, false alarm is avoided, and the array structure is light, thin and flexible. The mask is comfortable to fit skin, supports long-term wearing and is easy to disinfect and maintain; environment temperature and humidity parameters and pressure data are subjected to fusion analysis, the influence of a high-temperature and high-humidity environment on skin microcirculation can be recognized, the risk of pressure sores can be evaluated in an auxiliary mode, a calibration algorithm is built in a sensor, environment fluctuation interference is reduced, and data reliability is ensured; and the early warning unit comprises sound-light alarm equipment which supports a multi-stage alarm mode and is used for triggering an early warning signal and pushing information when the risk index exceeds a threshold value, so that the early warning timeliness is ensured and the false alarm risk is reduced.

The invention discloses an oil storage tank oil-water interface measurement system and method and a storage medium, and relates to the technical field of oil-water interface measurement, and the system comprises a data acquisition module, a data processing module, a decision support module and a data security module. According to the oil-water interface measuring system and method for the oil storage tank and the storage medium, a three-dimensional sensing network (distributed sensor network) is constructed by adopting a pressure sensor array and phased array ultrasonic scanning technology and combining dielectric property detection of a microwave dielectric constant sensor; the pressure, the dielectric constant, the liquid level and the vibration data in the tank body are obtained, basic data are provided for subsequent processing, the comprehensiveness of data obtaining can be improved through the sensing network, the pressure data are dynamically calibrated through Takagi-Sugeno fuzzy logic, the influence of temperature drift is effectively eliminated, and the accuracy of data obtaining is improved. The ultrasonic signals are subjected to feature enhancement through the generative adversarial network, and the emulsion layer boundary is accurately recognized.

The invention relates to the technical field of health care, and discloses a bath chair self-adaptive adjusting system based on multi-modal sensing. According to the system, a pressure sensor array, an infrared thermal imager and an inertial measurement unit are used for collecting multi-dimensional real-time data, and the multi-modal sensing fusion module is used for processing the multi-dimensional real-time data to generate a structured physiological feature vector. The user intention recognition module predicts user behavior intention and gives a comfort level score on the basis, and the posture self-adaptive adjustment module optimizes seat supporting curved surface parameters according to the comfort level score to achieve real-time adjustment. In addition, the safety monitoring module evaluates the slip risk, the closed-loop control module guarantees safety, the online learning module optimizes the adjustment strategy, and the abnormal response module deals with the emergency situation. According to the system, the comfort and safety of the bath chair are improved, personalized adjustment is achieved, and the system has high practical value.

The invention discloses an adaptive multi-angle elbow airtightness detection method, which comprises the following steps: arranging a flexible pressure sensor array and a micro inertial measurement unit on the inner wall of an elbow, collecting multi-point sealing pressure and attitude signals in real time, fusing geometric parameters and a spatial mapping relation, and completing denoising, normalization and multi-curvature region mapping of pressure data; a distributed pressure-attitude database is combined, a function model associated with sealing pressure and pipeline geometric parameters is established, inflation, exhaust and deformation of each node are dynamically adjusted through an intelligent closed-loop regulation and control algorithm, collaborative optimization of multi-node pressure and a fitting state is achieved, and the sealing performance of the pipeline is improved. According to the method, the accuracy and the self-adaptive adjusting capacity of sealing pressure distribution under a complex bent pipe structure are effectively improved, the tiny leakage real-time positioning and self-learning optimization capacity is achieved, and the method is suitable for sealing quality guarantee of various types of curved surface pipelines.

The invention relates to the technical field of intelligent control of injection molding machines, in particular to an injection molding machine closed-loop mold adjustment control system and method based on multi-sensor fusion and a self-adaptive algorithm, and the system comprises a sensing layer which adopts a multi-sensor fusion closed-loop feedback architecture and comprises a pressure sensing array, a displacement sensing unit and a temperature sensing array. The data acquisition module is used for synchronously acquiring mold clamping force, position and temperature data of a mold, constructing a three-dimensional error compensation model and realizing dynamic correction of the parallelism of the mold through space force field analysis; the execution layer comprises a servo motor, a belt wheel and a ball screw and is used for adjusting the position of the template; a double-closed-loop control module is arranged in the control layer, the double-closed-loop control module comprises outer ring mold clamping force control and inner ring position control, mold clamping force deviation serves as input of an outer ring, position correction is generated through a self-adaptive PID algorithm, the inner ring converts the position correction into a servo motor rotation angle instruction, and therefore precise control over the mold clamping force is achieved.

The invention discloses an emotional interactive intelligent nursing system and method based on multi-modal perception, and belongs to the technical field of intelligent medical treatment and intelligent old-age care crossing. The matrix type pressure sensor array is integrated in the nursing mattress, multi-point pressure distribution of the body of the old people on the bed surface is obtained in real time, and high-resolution body pressure mapping is achieved. Compared with an existing single-point type or linear pressure monitoring structure, the system can accurately recognize the spatial position of a local pressed area, and early recognition and quantitative evaluation of a bedsore risk area are achieved. By fusing the pressure matrix, the heart rate, the blood oxygen, the environment temperature and humidity, the urine wetting and other multi-mode sensing data, the monitoring dimension is remarkably expanded, the health condition can be comprehensively evaluated from multiple physiological indexes, compared with a single physiological parameter monitoring mode, the more comprehensive information obtaining capacity is achieved, and the monitoring precision and the nursing efficiency are effectively improved.

The invention provides an unmanned aerial vehicle group cooperative suppression method and system based on a distributed antenna array, electronic equipment and a storage medium, and relates to the technical field of unmanned aerial vehicle group cooperative suppression and anti-interference control. Obtaining airflow pressure distribution information; performing vortex field calculation processing on a fluid motion state by using the information to generate vortex field information containing a disturbance area; dynamically adjusting the phase of the antenna array element based on the eddy current field information, compensating the physical deformation of the array and outputting a compensation result; performing cooperative phase correction processing on distributed antenna array beam pointing by using the result to generate a beam phase compensation amount; and finally, cooperative regulation and control processing is performed on the unmanned aerial vehicle group emission signals based on the compensation amount, and an anti-disturbance suppression wave beam pointing to the target is generated. And continuous directional suppression on a moving target in a strong wind disturbance environment can be realized.

The invention discloses a dexterous hand perception control method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps that under the condition that a target multi-fingered dexterous hand grabs a target object is recognized through a pressure sensor array, pressure collection data are obtained from a pressure sensor array, and current joint data of all finger joints of the target multi-fingered dexterous hand are obtained from an encoder; according to the pressure collection data and the current joint data, the current grabbing state of the target multi-fingered dexterous hand is determined; when it is recognized that the current grabbing state does not meet the safe grabbing condition, dexterous hand pose data of the target multi-fingered dexterous hand are obtained from an inertial sensor, and a target grabbing mode of the target multi-fingered dexterous hand is determined according to the current space pose data, the pressure collection data, the current joint data and the dexterous hand pose data; and the target multi-fingered dexterous hand is controlled to grab in a target grabbing mode. According to the scheme, the sensing grabbing efficiency and accuracy of the dexterous hand are improved.

The invention discloses an aircraft airfoil pressure self-adaptive calibration method for a wind tunnel environment, belongs to the technical field of pressure sensors, and aims to solve the problem that the sensitivity of the sensors is reduced during aircraft airfoil pressure testing. Comprising the steps that a flexible pressure sensor array is installed in a matched mode according to the airfoil shape of a to-be-tested aircraft, the to-be-tested aircraft is placed in a wind tunnel, wind tunnel parameters are adjusted, and pressure signals in a multi-scene environment are generated; each pressure sensor unit is regarded as an independent agent, and a calibration model is constructed by using an MADDPG algorithm; an Actor-Critic network architecture of multi-agent cooperative training is designed and obtained; and performing model compression on the trained Actor network, deploying the Actor network to an embedded system, fitting a nonlinear mapping relation between output of a pressure sensor unit and a real pressure value in real time, correcting a nonlinear error, and performing dynamic compensation on zero drift. The method is used for aircraft airfoil pressure distribution testing.

The invention provides an intelligent vein closing system and a control method thereof, and belongs to the technical field of medical instruments.The intelligent vein closing system comprises a radio frequency generator host and a closing catheter, and the radio frequency generator host is used for generating and controlling output of radio frequency energy; the closed catheter comprises a handle, a catheter body and a heating working end which are connected in sequence, and the handle is detachably connected with the radio frequency generator host; wherein an infusion pump is integrated on the radio frequency generator host, and the infusion pump is used for infusing swelling liquid to a surgical site and is controlled by a control unit in the radio frequency generator host; a pressure sensor array is arranged outside the heating working end of the closed catheter and used for detecting the attaching pressure between the heating working end and the blood vessel wall in real time. The device is high in integration, and vein closing effectiveness, stability and treatment consistency are improved.

The invention discloses a pressure mapping method based on a pressure sensor array, and the method comprises the steps: carrying out the gradient direction analysis of an original pressure matrix outputted by the pressure sensor array in real time, carrying out the matching with the motion direction of a material, and generating a direction sensitive pressure feature matrix; direction sensitive pressure feature matrixes generated at different collection time points are obtained in a preset time window, a track sequence is obtained, a pressure distribution kinematics feature vector sequence is generated and input into a pressure evolution state prediction model, and evolution state information is output; generating a single-point-global pressure evolution feature vector of each sensor unit, inputting the single-point-global pressure evolution feature vector into a sensing unit pressure mapping anomaly recognition and evaluation model, and outputting a local risk value of the sensor unit; and generating a risk thermodynamic diagram according to the local risk value of each sensor unit in the pressure sensor array, and identifying a pressure mapping abnormal region. Therefore, accurate monitoring, analysis and abnormal mapping of pressure distribution in the material movement process are realized.

The invention provides an intelligent detection method and system for an urban sewer pipeline, and the method comprises the steps: synchronously collecting pipeline data through laser, vision, ultrasound and a pressure sensing array, and generating aligned multi-source data through space-time registration; edge end defect preliminary screening is realized by using a lightweight AI model, and high-risk data is screened and uploaded to a cloud end; a pipeline digital twin model is constructed based on point cloud splicing and feature recognition, a multi-modal fusion neural network is adopted to realize accurate defect diagnosis, and a detection path is dynamically optimized in combination with an ant colony algorithm. According to the method, the technical problems that the adaptability is poor and the omission ratio is high in a complex sewer pipeline environment and multi-source data fusion analysis and active early warning cannot be realized by a traditional method can be solved.

The invention relates to the technical field of ice engineering measurement, and discloses an underwater special-shaped structure surface floating icebreaking load spatial and temporal distribution test system, which comprises a flexible high-density distributed pressure sensor array, a high-speed synchronous data acquisition module, an underwater data transmission system and a shore data processing platform, the flexible high-density distributed pressure sensor array is attached to the surface of an underwater target special-shaped structure; the high-speed synchronous data acquisition module is mounted in a sealed cabin in the special-shaped structure of the underwater target, is close to the flexible high-density distributed pressure sensor array and is used for digitalization; the underwater data transmission system is used for communication between the high-speed synchronous data acquisition module and the ashore data processing platform; and the ashore data processing platform is used for reconstructing and visually displaying the pressure field of the special-shaped structure of the underwater target. According to the method, more comprehensive and accurate ice-structure interaction load information can be obtained, and fine structure design is served.

The invention provides a multifunctional intelligent anti-thrombus PICC (peripherally inserted central catheter) for tumor chemotherapy, which comprises a catheter body, a catheter tip, a main infusion cavity, a first auxiliary cavity and a second auxiliary cavity, and the first auxiliary cavity and the second auxiliary cavity are arranged around the main infusion cavity to form a spiral structure; a micro pressure sensor array is embedded in the pipe wall of the first auxiliary cavity; a biological impedance measuring electrode pair is embedded in the pipe wall of the second auxiliary cavity; and the micro pressure sensor array, the biological impedance measuring electrode pair, the micro ultrasonic transducer and the temperature sensor are connected with a processor. According to the method, active thrombus prevention is achieved, passive treatment is changed into active prevention through a triple mechanism, and the thrombus occurrence rate is greatly reduced; meanwhile, the tube body is formed by mutually winding, fusing and extruding three independent cavities (a main infusion cavity, a first auxiliary cavity and a second auxiliary cavity) like a DNA double helix (triple helix is provided herein); and the mechanical stimulation and damage to the inner wall of the blood vessel are reduced.

The invention relates to the technical field of ice engineering measurement, and discloses an ice pool underwater special-shaped structure icebreaking load simulation test method comprising the following steps: test preparation: carrying out test preparation, and attaching a flexible pressure sensor array to the surface of an underwater test piece; data acquisition: synchronously acquiring data acquired by the flexible pressure sensor array in the icebreaking process; and data processing: reconstructing the data acquired by the flexible pressure sensor array by adopting a hybrid interpolation algorithm based on physical constraint and adaptive weight to obtain a simulated icebreaking evolution track. According to the method, the precision and reliability of ice load reconstruction are remarkably improved, and the method is particularly suitable for identification and analysis of local peak load on the surface of a special-shaped structure.

The invention discloses a wireless sector ultrasonic scanning method, and relates to the technical field of veterinary ultrasonic diagnos.The wireless sector ultrasonic scanning method monitors contact pressure distribution of a probe and the body surface in real time through a three-dimensional pressure sensor array, a sound velocity correction model is constructed according to the contact pressure distribution, and the imaging precision under the complex body surface form is improved; ultrasonic radio frequency data and motion data are synchronously processed through millimeter wave dual-channel wireless transmission, in combination with motion speed self-adaptive frame rate regulation and control, the transmission load is greatly reduced while the image continuity is guaranteed, the coupling agent release is regulated and controlled by the integrated micro-fluidic unit in a partitioned manner, the acoustic coupling effect is effectively optimized, waste is reduced, and the sound quality is improved. The problems that a traditional wired probe is poor in body surface adaptability, low in data transmission efficiency and unreasonable in coupling agent dosage are solved, the system is suitable for dynamic detection scenes of animal medical treatment, and a convenient and efficient solution is provided for pet health management.

The embodiment of the invention provides a vehicle-mounted data acquisition method and device and electronic equipment, and relates to the technical field of Internet of Vehicles, and the method comprises the steps: monitoring whether the vehicle state of a target vehicle meets a preset vehicle state condition or not in the operation process of the target vehicle; the preset vehicle state condition comprises a logic combination condition of a plurality of vehicle state parameters; and in response to the condition that the vehicle state meets the preset vehicle state condition, obtaining pre-subscribed target working condition data from an electronic control unit (ECU) of the target vehicle. According to the embodiment of the invention, the collection of the vehicle working condition data is triggered by adopting a static logic combination parameter mode, the vehicle-mounted terminal is prevented from collecting and storing redundant data, the existing sensor data source of the ECU can be fully utilized, and an independent pressure sensor array does not need to be deployed, so that the accuracy of the collected vehicle working condition data is ensured; moreover, the hardware cost is reduced, and the overall reliability of the system is improved.

The invention relates to the technical field of disease monitoring, in particular to a multi-device collaborative disease risk prediction system. The system comprises a non-contact type signal receiving and transmitting device, a gait collecting device, an intelligent bracelet and a central processing unit, the non-contact type signal receiving and transmitting device captures macroscopic movement data of a user through a millimeter wave signal transmitting and receiving module, and the macroscopic movement data comprises periodic characteristics of gaits, movement tracks of four limbs and posture changes; the gait acquisition device acquires plantar pressure distribution data of a user through a pressure sensor array; the smart bracelet collects motion data of a user through an accelerometer and a gyroscope; and the central processing unit carries out space-time alignment on data of the non-contact signal transceiving device, the gait acquisition device and the intelligent bracelet through a timestamp synchronization algorithm, so that the disease risk is predicted according to the analysis data. The system supports all-weather and multi-scene monitoring, is suitable for disease risk assessment, and can early warn cardiovascular events and other health problems.

The invention relates to a pressure distribution identification and detection system and method based on a time sequence convolutional neural network. According to the system, a pressure sensor array is used for collecting pressure signals, after filtering processing, the pressure signals are input into a time sequence convolutional neural network for feature extraction and mode recognition, and high-precision pressure distribution detection and recognition are achieved. The method is particularly suitable for anti-interference input equipment under the scenes of man-machine interaction, electronic signature authentication and the like.

The invention discloses a self-adaptive waist tracking method, a computer readable storage medium and an intelligent seat, the self-adaptive waist tracking method is used for the intelligent seat, the intelligent seat is provided with a pressure sensor array and a waist support adjusting mechanism, and the method comprises the following steps: acquiring real-time pressure data of a current user collected by the pressure sensor array; extracting pressure characteristic parameters according to the real-time pressure data, and determining the body type category of the current user according to the pressure characteristic parameters by using a pre-trained body type recognition model; determining a current sitting posture type and an initial pressure threshold value of the current user according to the real-time pressure data by utilizing a pre-trained sitting posture recognition model; determining a target pressure threshold value according to the real-time pressure data, the body type category and the initial pressure threshold value; according to the target pressure threshold value, supporting parameters of a waist support adjusting mechanism are adjusted, so that the waist support is matched with the waist state of the user. According to the self-adaptive waist-following method, personalized waist-following adaptation of the user in multiple scenes is realized.

The invention discloses an electrolytic cell power feed-forward control method for an off-grid hydrogen production system, which comprises the following steps: acquiring high-frequency pressure data through a pressure sensor array, and analyzing and generating flow-electricity coupling physical information based on the high-frequency pressure data; performing spatio-temporal evolution prediction on the local pressure field by using the flow-electricity coupling physical information and the high-frequency pressure data to generate predicted local pressure field evolution data; and according to the predicted local pressure field evolution data, a feedforward control instruction used for adjusting the input power of the electrolytic cell is generated. According to the method, accurate prediction and active inhibition of the flow-electricity coupling instability in the electrolytic cell are realized, and the operation stability and the energy utilization efficiency of the off-grid hydrogen production system are improved.

The invention discloses an intelligent exoskeleton bone auxiliary conduction hearing aid system capable of being remotely controlled and having an electroencephalogram control function, and relates to the technical field of intelligent rehabilitation robots and hearing aid devices. The wearable mechanical part comprises a flexible actuator, an elastic fabric base material, an inertial measurement unit IMU, a plantar pressure sensor array, a surface myoelectricity EMG sensor and an electroencephalogram EEG sensor. And the information processing communication part comprises a central controller, a bone conduction hearing aid module, a multi-mode sensor, an embedded SoC, a DSP / AI accelerator, a 4G / 5G / Wi-Fi module and a power management unit. The flexible exoskeleton walking aid system and the bone conduction hearing aid module are integrated, the electroencephalogram EEG sensor is additionally arranged to achieve the electroencephalogram control function, and cooperation of the three functions of movement assistance, auditory perception and neural intention recognition is achieved. A user can directly control the exoskeleton action mode through electroencephalogram signals, meanwhile, intelligent assistance of lower limb joints is obtained in the walking process, and environment sounds and voice prompts are clearly received in a bone conduction mode. According to the system, the perception ability, the control flexibility and the social participation degree of old people or rehabilitation patients who are inconvenient to move and accompanied with hearing impairment in a complex environment are remarkably improved, and more natural and convenient man-machine interaction experience is provided for users.

The invention relates to a sleeping posture recognition and self-adaptive pillow height adjustment system and method and a storage medium, and the sleeping posture recognition and self-adaptive pillow height adjustment system comprises a data collection module, a sleeping posture recognition module, a pillow height adjustment module and a user interaction module; the user interaction module is used for acquiring personalized prior data and historical sleep comfort score of a user; the data acquisition module is used for acquiring a pressure data set of the pressure sensor array in real time; the sleeping posture recognition module is used for constructing a plurality of groups of time domain data slices for the pressure data set according to a preset time window, inputting the time domain data slices into a time domain feature model to obtain a plurality of groups of low-dimensional pressure data feature parameters, and further recognizing an effective sleeping posture state; and the pillow height adjusting module is used for calculating and calibrating the pillow height based on the personalized prior data of the user, the effective sleeping posture state and the historical sleeping comfort score, and adjusting the pillow surface. According to the method and the device, the problems of high computing power consumption and difficulty in meeting precise and personalized sleep requirements of the user in related technologies are solved.

The invention discloses an autoclave forming method which comprises the following steps: dividing a component into a stress sensitive area and a conventional area through finite element simulation analysis on the basis of geometrical characteristics of a three-dimensional model of the component to be formed, establishing a thermal-mechanical coupling finite element analysis model of each area, and presetting a differential temperature-pressure-time process curve; secondly, a distributed optical fiber sensor is arranged in the composite material prefabricated body, a micro pressure sensor array is arranged at the key position of the surface of the mold, and the distributed optical fiber sensor and the micro pressure sensor are both connected with a central control system; then, performing differential pressure and temperature control on each area by adopting closed-loop control in sequence; and finally, the central control system collects sensor data in real time, judges whether the forming process is abnormal or not through a defect recognition algorithm, automatically starts a grading early warning mechanism when detecting that the forming process is abnormal, and executes a self-adaptive adjustment strategy, including inter-region cooperative pressure compensation, so as to eliminate forming defects.

The invention belongs to the field of article carrying, and particularly relates to a self-adaptive terrain load moving vehicle based on multi-mode AI navigation, which comprises a crawler-type chassis driving mechanism, a lock catch arranged on the outer side wall of a chassis main body, crawler main bodies arranged on the two sides of the chassis main body, a plurality of groups of gears arranged in the crawler main bodies, and a plurality of groups of driving mechanisms arranged on the crawler main bodies, through organic combination of infrared following, pattern recognition and the SLAM technology, full-autonomous path planning and dynamic obstacle avoidance of the load moving vehicle are achieved, manual intervention is completely eliminated, the automation level and efficiency of operation are greatly improved, and the load moving vehicle is suitable for complex and changeable operation environments. The terrain sensing system composed of the crawler chassis and the pressure sensor array is matched with the AI terrain surveying and mapping technology, complex terrains such as slopes, pits and non-hardened grounds can be accurately recognized and adapted, the space and terrain limitation of traditional weight moving equipment is effectively broken through, and the operation range is widened.

The invention discloses a bedridden patient sign measurement and medication assisting system based on multi-sensor fusion, which belongs to the technical field of medical instruments and comprises a multi-sensor fusion measurement module, a self-adaptive calibration compensation module, an intelligent evaluation decision module, a medication assisting calculation module and a closed-loop feedback optimization module. A pressure sensor array, an ultrasonic sensor and an acceleration sensor are used for cooperatively measuring the height and weight of a patient, a deformation compensation model and a body position correction model are adopted for accurate calibration, a BMI index is automatically calculated, a VTE risk score, a falling risk score and a self-care ability score are generated, and the medication dosage is intelligently recommended according to medicine characteristics and patient physique. And continuously optimizing system parameters through an incremental learning algorithm to form a measurement-evaluation-medication-optimization deep coupling closed-loop system, so that the physical sign measurement precision, clinical evaluation efficiency and medication safety of the bedridden patient are remarkably improved, and the nursing labor intensity and the medical error risk are reduced.

The invention discloses an intelligent mattress control method based on height, an intelligent mattress and related products. The method comprises the steps of obtaining height parameters of a human body; according to the height parameters, through a preset micro-partition mapping algorithm, to-be-activated micro-partitions, corresponding to all the body parts of the human body, on the mattress are determined, a preset number of micro-partitions are pre-divided in the length direction of the mattress, and a plurality of air bags are distributed in each micro-partition; activating the air bag of the micro-partition to be activated to obtain a current activated micro-partition, and collecting a plurality of pressure values of the micro-partition through a pressure sensor array of the mattress; according to a preset air pressure adjusting strategy, the air pressure of the air bag in the current activation differential area is adjusted according to the pressure value. According to the method, the air bag supporting subareas can be dynamically adjusted according to the heights of the users, the problem that traditional mattress subareas are fixed and are difficult to adapt to the users with different heights and weights is solved, accurate supporting and personalized adjustment are achieved, and the supporting effect and sleep comfort are improved.

The invention relates to the technical field of medical monitoring equipment, in particular to an intelligent drainage monitoring system and method after a hepatotomy based on multi-modal sensing, and the system comprises a sensing data collection module, a signal processing module, a data fusion analysis module and an abnormity recognition early warning module. The sensing data acquisition module comprehensively acquires pressure, component and diffusion state data of drainage liquid by utilizing an optical fiber pressure sensor array, a micro spectral analysis device and a biological impedance sensor, the signal processing module converts sensing data into digital signals, and the data fusion analysis module performs fusion analysis on the drainage liquid based on the signals. According to the system, the content of bilirubin and hemoglobin in drainage liquid and the diffusion state of the bilirubin and hemoglobin in the abdominal cavity are recognized and comprehensively analyzed, the abnormity recognition and early warning module compares an analysis result with a preset normal index, the abnormal condition is determined, an early warning signal is generated, the intelligence and accuracy of drainage management are effectively improved, and the working efficiency is improved. Postoperative complications can be reduced, and the rehabilitation quality of a patient can be improved.