36 results about "Body surface temperature" patented technology

The invention relates to the technical field of intelligent glasses, and discloses an intelligent glasses wearing identification method based on multi-modal perception, and the method comprises the steps: collecting the capacitance change rate, the facial contour matching degree, the body surface temperature, the vital signs, the head attitude angle and other multi-source feature data in real time, generating five groups of feature data, and carrying out the standardization processing and weight fusion, forming a comprehensive feature vector; calculating a preliminary confidence score by combining a dynamic weight adjustment mechanism and a rule engine, and correcting a deviation caused by head movement; judging a wearing state according to the corrected confidence score, outputting a label, and realizing function control in linkage with a gesture interaction module; the abnormal state triggers local or cloud alarm; the sampling frequency of the sensor is dynamically adjusted according to the wearing state, the frequency is reduced to 1Hz when the sensor is not worn, the frequency is improved to 10Hz when the sensor is worn so as to enhance the response precision, and the decision process is only triggered when the feature is suddenly changed in combination with an event-driven strategy. According to the invention, the precision and the reliability can be improved, and low-power-consumption design is realized.

The invention relates to the technical field of temperature monitoring, in particular to a severe pneumonia patient body surface temperature distribution monitoring method based on thermal imaging. The method comprises the following steps: solving a dynamic deformation field of the body surface of a patient relative to a standard three-dimensional body surface model through a minimized deformation energy function, and generating an initial monitoring area by using the dynamic deformation field and an internal parameter matrix of a thermal imager; an active contour model is adopted to optimize the boundary of the initial monitoring area, and a self-adaptive optimization monitoring area matched with the current temperature distribution characteristics is generated; if the credibility of the temperature feature vector is low, the temperature feature vector is compensated in combination with vascular active drug infusion information, and a pathophysiological residual feature sequence is obtained. According to the method, an initial monitoring area capable of tracking a target anatomical structure in real time is generated, the spatial consistency and anatomical accuracy of data acquisition are ensured, and a temperature feature sequence for precise time sequence analysis can be generated.

The invention relates to the technical field of diving suit detection, and discloses a high-pressure diving suit detection device and method, and the device comprises the following steps: a high-pressure simulation cabin which is used for simulating the high-pressure environment of a deep sea, and providing the testing conditions of a diving suit under different depth pressures; the warm dummy simulates a human body and can heat different parts of the dummy in an underwater high-pressure environment, so that real-time visualization of body surface temperatures of all the parts of the human body in the underwater high-pressure environment is achieved, temperature control data can be recorded in real time, and a diving suit in detection can be worn on the warm dummy in real time; and the temperature control system simulates the heat distribution and heat loss rule of the human body by adjusting the temperature of each part of the thermal dummy. Multi-dimensional environmental parameters including pressure, temperature and humidity can be simulated through the high-pressure simulation cabin, so that the actual working state of the diving suit in the deep sea can be effectively represented, comprehensive test conditions are provided, the test result is close to the real use situation, and the reliability and safety of the diving suit in the extreme environment are ensured.

The invention discloses a physical training load regulation and control method and system based on self-adaptive physiological coupling, and the method comprises the steps: collecting an electrocardiosignal, a light volume pulse signal, a respiration signal, a surface electromyographic signal and a body surface temperature signal, and generating a multimode sequence with a time mark; self-adaptive time alignment is executed, a timestamp graph is constructed, clock drift estimation is carried out, segmented monotonic reversible time transformation is established, and a multimode sequence is mapped to a unified time axis; reconstructing the missing section and the artifact section, establishing a mask auto-encoder with physiological priori constraints, combining time domain consistency constraints and frequency domain consistency constraints, and outputting a continuous differentiable reconstructed sequence. According to the method, by introducing adaptive time alignment, cross-modal signal reconstruction and dual-time scale state modeling, coordinated recognition and dynamic load regulation and control of multi-source physiological signals are achieved, coupling analysis in the training process is more stable, and an individual model can be continuously and adaptively updated.

The invention is suitable for the technical field of air conditioner control, and provides an air conditioner control method and an air conditioner. The method comprises the steps that body surface temperature values of human bodies in different sub-areas in a target area are collected, and environment comfort data of the different sub-areas are determined according to the body surface temperature values; fitting the environmental comfort data of the different sub-areas to obtain a comfort distribution diagram of the target area, and finally determining an air outlet strategy of the air outlet according to the comfort condition of the air outlet matching area in the comfort distribution diagram. The air outlet strategy of each air outlet is matched with the comfort degree of the area, differentiated and precise control over the multiple air outlets is achieved, and air supply on demand for different user positions or activity areas is achieved.

The invention is suitable for the technical field of data identification, and provides a fat-reducing energy consumption estimation method and device, and the method comprises the steps: obtaining body basic data and environment temperature, and calculating basic metabolism parameters according to the body basic data and the environment temperature; acquiring a moving track point, a current heart rate and a body surface temperature, and matching the estimated motion state and the motion intensity in each preset time period according to the moving track point, the current heart rate and the body surface temperature; and calculating fat reduction energy consumption according to the basic metabolic parameters, the estimated motion state in each preset time period and the motion intensity in each preset time period. According to the scheme, multiple key variables and dynamic data are introduced, so that the accuracy, comprehensiveness and individuation level of energy consumption estimation are remarkably improved.

The embodiment of the invention discloses an ultrasonic image adaptive optimization method and device and electronic equipment, and relates to the technical field of ultrasonic images. And self-adaptive adjustment and optimization of imaging parameters can be realized conveniently, so that the acquisition quality of ultrasonic images is improved. The method comprises the following steps: acquiring pressure data, body surface temperature data and displacement data of an ultrasonic probe in a contact state with a human body; according to the pressure data, the body surface temperature data and the displacement data, hardware control parameters of the ultrasonic imaging system are dynamically adjusted based on a preset algorithm model; and according to the adjusted hardware control parameters, acquiring an ultrasonic image of the human tissue.

Provided in the present application is a wearable temperature control device, comprising a housing, a temperature control main body, and a loading component, wherein the housing is provided with an air outlet facing a human body and vents facing away from the human body; the temperature control main body is provided with cavities, and pipe sections made of an elastocaloric material and media used for conducting heat are provided in the cavities; and the loading component is connected to the pipe sections, such that when stress is applied to the pipe sections, the pipe sections are deformed to generate heat, and / or, when the stress is removed from the pipe sections, the pipe sections return to their original shape to generate cooling capacity. The present application further provides a wearable article and a temperature regulator on the basis of the wearable temperature control device, and further provides a body surface temperature regulation method on the basis of the temperature regulator. The wearable temperature control device, the wearable article, the temperature regulator, and the body surface temperature regulation method provided in the present application can regulate the surface temperature of a wearer in a timely manner, so as to ensure the comfort of a user; moreover, free detachment and use can be realized, thereby preventing the impact on the movements of the wearer, and preventing difficulties in terms of cleaning clothes.

This biological data measurement device is provided with a substrate disposed at a position separated from a body surface (BS) by a predetermined distance via a support member made of a heat insulating material so as to generate an air layer between the substrate and the body surface of a living being to be measured. A thermometer including a radiation thermometer for measuring the body surface temperature and a substrate thermometer for measuring the substrate temperature of the substrate is provided on the substrate, so that the deep body temperature can be accurately measured.

The invention relates to the technical field of intelligent seats, and particularly discloses an intelligent seat health intervention method and system based on multi-modal physiological signal fusion, and the method comprises the steps: obtaining a physiological signal, driving time, body surface temperature and sweat amount data of a driver; on the basis of the physiological signal, the driving time and the body surface temperature data, preprocessing detection data are obtained, and to-be-detected pressure data and first preprocessing pressure data are obtained according to the sweating amount data; determining an error influence factor according to the historical characteristic data, and determining a friction force error value according to the error influence factor; determining a pressure error predicted value based on the friction force error value; and performing error compensation on the to-be-detected pressure data according to the pressure error prediction value to obtain second pre-processed pressure data, performing fatigue prediction based on the first pre-processed pressure data, the second pre-processed pressure data and the pre-processed detection data to obtain a fatigue grade result, and outputting a health intervention regulation result. And real-time health intervention on the intelligent seat is realized.

The invention relates to the technical field of child body temperature detection, and discloses an automatic child body temperature detection data processing system. The system comprises a multi-channel infrared temperature sensor array, a sliding window feature extraction module and a physical sign state decision module. The multi-channel infrared temperature sensor array is used for collecting body surface temperature time sequence data of a target child in real time; the sliding window feature extraction module performs multi-scale time domain feature analysis on the body surface temperature time sequence data to generate a basic sign feature set containing an instantaneous temperature change rate, a local temperature extreme value and a periodic fluctuation amplitude; the physical sign state decision-making module constructs a hierarchical detection state machine framework according to the basic physical sign feature set, the framework comprises a common detection state set, a high-heat early warning state set and an emergency treatment state set, and each state set is associated with different physical sign data analysis strategies. The system can realize real-time continuous monitoring of child body temperature, deeply extract body temperature characteristics, and provide an intelligent solution for child body temperature monitoring.

The application discloses a kind of determination methods, device, wearable equipment and medium of calorie consumption, applicable to wearable equipment technical field.Ear temperature value of ear cavity collected by earphone is acquired, wherein the earphone has temperature sensing probe for being built into ear cavity;Attitude value collected by attitude sensor is acquired;Calorie consumption is determined according to attitude value and temperature value.The temperature value of ear cavity collected by earphone, so that it will not directly contact with external environment, while also can avoid contact with sweat, less affected by external environment and sweat, and then determine calorie consumption according to temperature value and attitude value, avoid the existing only through attitude value to obtain inaccurate calorie consumption, or through attitude value and body surface temperature value due to the problem that body surface temperature value is greatly affected by external environment or sweat when collecting, improve the accuracy of calorie consumption of wearable equipment, further improve the experience of user.

This invention relates to the field of air conditioning and discloses an energy-saving fresh air system and fresh air treatment method. The system includes collecting and registering age group information and historical physical condition information; constructing a human body heat demand benchmark model by combining it with preset human body heat demand parameter mapping rules; collecting historical movement trajectory data and current location information to generate high-probability activity areas; collecting indoor and outdoor ambient temperature data and current body surface temperature information at corresponding spatial nodes to construct an environmental and human body joint state dataset; generating candidate temperature range evolution paths based on the human body heat demand benchmark model, high-probability activity areas, and the environmental and human body joint state dataset, forming temperature range evolution path information; and generating a multi-node temperature collaborative control scheme by combining the mapping relationship of high-probability activity areas in spatial nodes. This invention has the advantages of improving temperature control accuracy and overall energy efficiency.

The utility model provides a quilt, and relates to the technical field of smart home. The plurality of temperature sensors are arranged at a plurality of preset positions of the quilt core at intervals, and the plurality of temperature sensors are used for monitoring temperature signals of a plurality of body parts of a human body respectively; and the output interface is electrically connected with the plurality of temperature sensors, and the output interface is used for outputting the plurality of temperature signals. The multiple temperature sensors are arranged at the multiple preset positions of the quilt core at intervals so as to monitor the temperature signals of the multiple body parts of the human body, the output interface is arranged, the output interface is electrically connected with the multiple temperature sensors so as to output the multiple temperature signals, and therefore the temperature of the human body can be monitored. Real-time collection of the body surface temperature distribution characteristics of the user can be achieved in a non-contact temperature monitoring mode, and therefore the accuracy and privacy safety of sleep behavior monitoring are improved.

The embodiment of the invention relates to a low-temperature treatment system, and the system comprises a treatment cap which comprises a protection layer, a cooling layer and a skin-attaching layer, the temperature control module is arranged between the cooling layer and the skin attaching layer; the heat exchange unit is arranged between the skin attaching layer and the temperature control module and is in contact with the temperature control module; the ice cap temperature sensor is arranged on the side, close to the cooling layer, of the skin attaching layer; a body surface temperature sensor; an anus temperature sensor; the display screen is configured to receive a target temperature control type and a target treatment type; and the controller is electrically connected with the temperature control module, the ice cap temperature sensor, the body surface temperature sensor, the anus temperature sensor and the display screen, and is configured to determine a target temperature control mode based on the target temperature control type and the target treatment type, and control the temperature control module based on the target temperature control mode. According to the low-temperature treatment system, the corresponding temperature control mode can be obtained according to the treatment type and the temperature control type of the patient, so that the temperature control module is adaptively controlled, and the accuracy of low-temperature treatment is ensured.

The application provides a human body wearing monitoring system based on traditional Chinese medicine pulse diagnosis and a use method thereof, and relates to the technical field of traditional Chinese medicine pulse diagnosis. The wearable monitoring device comprises a detection module, a data processing module and a transmission module. The application integrates three types of sensors, synchronously collects pulse waves, physiological electrical signals and body surface temperatures, monitors core physiological parameters in one station, meets daily monitoring and diagnosis data requirements, adopts differentiated ADC precision conversion for different signals, removes biological electrical noise through Kalman filtering, matches exclusive quantification or calibration formula, effectively suppresses power frequency and motion interference, and has high data precision and reliability.

The application provides a system and method for measuring core body temperature and multi-mode health parameters, and relates to the technical field of health parameter measurement of human body. The application comprises a thermoelectric device module, a multi-mode health parameter monitoring module, a measurement circuit module and a processing module. Firstly, the heat flux density and body surface temperature of the human body surface are collected by the thermoelectric device module, the heat transfer model of the human body is constructed by using the heat flux method, and the core body temperature is calculated, so that the test error is small, and the measurement accuracy of the system is improved. Secondly, the thermoelectric device module is wrapped with a thin copper sheet and a heat insulation plastic layer outside, so that the interference from the environment can be overcome, and the heat flow is guided to transfer along the thickness direction, thereby improving the anti-interference ability of the system. Finally, the multi-mode health parameter monitoring module is integrated, the sensitive and accurate monitoring of multiple health parameters is realized, the parameters are verified with each other, and the accuracy of the human health condition is ensured.

This invention relates to the field of competitive performance monitoring and prediction technology, and discloses a method and system for predicting competitive performance based on multimodal data fusion and machine learning. The system collects physiological data (such as heart rate, blood oxygen, HRV, body surface temperature, etc.), environmental data (such as temperature, humidity, air pressure), and behavioral data (such as steps, sleep structure, calorie consumption) in real time, performs feature weighted fusion using the entropy method, and evaluates competitive performance based on an LSTM-CNN hybrid neural network model. The system outputs fatigue index, stress index, recovery ability index, and exercise readiness index, enabling efficient early warning and in-depth analysis report generation, significantly improving the accuracy and real-time performance monitoring of individual athletic performance, and is applicable to sports training, health management, and competitive performance optimization.

The object of the present invention is to provide a temperature sensor unit and an internal thermometer that can be manufactured at low cost. The temperature sensor unit (1) is used to measure the deep body temperature Ti as the internal body temperature of the subject. The temperature sensor unit (1) has a first to a fourth temperature sensor (111 to 114) for measuring the body surface temperature of the subject on the measuring surface side facing the body surface of the subject. In the first and second temperature sensors (111, 112), a first thermal resistor (121) is provided only on the measuring surface side of the first temperature sensor (111). The first temperature sensor (111) and the second temperature sensor (112) are arranged close to each other so that the temperature T2' on the measuring surface side of the first thermal resistor (111) is approximately equal to the temperature T2 measured by the second temperature sensor (112).

The invention discloses a sheep epidemic disease control method and system based on thermal imaging, particularly relates to the technical field of body temperature monitoring in biomedical engineering, and aims to solve the problems that in the prior art, target loss and identity recognition interruption are likely to occur in sheep body temperature monitoring, and body temperature changes cannot be continuously tracked. The method comprises the following steps: collecting continuous thermal imaging sequence frames to extract body surface temperature distribution data, carrying out identity matching and tracking based on the body surface temperature distribution data in combination with behavior characteristics and spatial characteristics, constructing a time sequence body surface temperature change curve, identifying standard resting posture fragments, establishing a reference resting body temperature, and carrying out standardization processing. And comparing the standardized curve with an epidemic disease characteristic database, analyzing and identifying a temperature anomaly trend, introducing a fuzzy logic decision mechanism for grading evaluation, and judging epidemic disease risks in combination with historical data.

The invention discloses an intraoperative body temperature real-time prediction and early warning system, which relates to the field of intelligent medical treatment and synchronously acquires multi-source data such as body surface temperature, heart rate, skin humidity and operating room environment temperature and humidity through flexible non-invasive wearable equipment. And constructing a time sequence characteristic matrix through data cleaning, normalization and characteristic engineering, and inputting the time sequence characteristic matrix into a three-layer LSTM body temperature prediction model to realize the real-time estimation of the core body temperature and the accurate prediction of the future 5-10 minutes. The system is provided with three levels of early warning threshold values, multi-mode early warning reminding is achieved through a buzzer, an LED indicator lamp and mobile terminal pushing, and medical workers are assisted to take intervention measures in advance. The system further comprises a process control module and a model adaptive calibration unit, and can automatically manage operation sessions, correct prediction deviation and generate an intraoperative body temperature monitoring report. According to the method, the risk and limitation of a traditional invasive temperature measurement mode are effectively overcome, and the accuracy, predictability and clinical application value of intraoperative body temperature monitoring are remarkably improved.

The invention discloses an air conditioner control method and a related device, relates to the technical field of air conditioners, and improves the thermal comfort service level of an air conditioner to a user. The method comprises the following steps: detecting body surface temperatures of different body parts of a user; calculating the thermal comfort of the user according to the body surface temperatures of the different body parts, the skin surface area proportions of the different body parts and the temperature tolerance weights of the different body parts; wherein the temperature latitude weights of the different body parts refer to the weights of the temperature latitude of the different body parts in thermal comfort calculation of the human body; and according to the deviation between the preset target thermal comfort and the thermal comfort obtained through current calculation, target operation parameters of the air conditioner are compensated.

There is provided a correction apparatus comprising: a calculation unit configured to acquire a body surface temperature of a first person who has stayed outdoors for a predetermined time or longer from a video image captured by a thermal camera and calculating, on the basis of a result of measurement of a body temperature of the first person, a correction value to be used for correcting the body surface temperature of the first person; and a correction unit configured to acquire a body surface temperature of a second person different from the first person from a video image captured by the thermal camera and correct a body surface temperature of the second person on the basis of the correction value.

The application discloses a kind of wearable sensor based on chaos fiber ring decay ring-down technology, including light source part, fiber ring and data processing device;Light source part is chaos fiber laser;Fiber ring decay ring-down ring includes optical coupler OC-2, optical coupler OC-3, optical isolator ISO and sensing unit;The light splitting ratio of two optical couplers is 95:5, and sensing unit is composed of polydimethylsiloxane packaged fiber bragg grating;The algorithm in data processing device PC includes solving the influence of body surface temperature on FBG stress sensing, the influence of temperature sensitization of PDMS, and the collected chaos signal is autocorrelated and fitted to obtain human motion related data.Carry out human motion detection, solve the influence of body surface temperature on FBG stress sensing.Using PDMS to package FBG, the sensing unit is protected and has the characteristics of skin-like stretchable, and the temperature sensitization of PDMS is easier to measure the body surface temperature.

The invention discloses a scapulohumeral periarthritis dynamic cold and hot compress regulation and control system and method based on body temperature feedback. The system comprises a user interaction terminal; the multi-modal physiological sensing end is used for collecting multi-source physiological data of shoulders, multi-source physiological data body surface temperature distribution, patient pain scores and local thermal metabolism data in real time; the intelligent central controller is used for carrying out fusion analysis on the collected multi-source physiological data, generating a treatment decision according to the real-time state of the patient and outputting a decision instruction; and the dynamic cold and hot compress execution end is used for executing independent and dynamic cold compress or hot compress treatment on different anatomical areas of the shoulder according to the decision instruction. Through real-time feedback of multi-modal physiological data, the system can automatically identify different pathological states such as inflammation and circulation, and dynamically adjust cold and hot compress parameters; the built-in safety monitoring module can detect temperature abnormity and equipment faults in real time, give an alarm in time and interrupt treatment, so that the risk of scalding or frostbite is avoided.

The invention relates to the technical field of vital signs, in particular to a cold radiation panel refrigeration control method based on vital signs, which comprises the following steps: acquiring heart rate skin conductivity shell temperature and combining with circadian rhythm segmentation to obtain rhythm grades, calculating heart rate variability indexes, inputting the heart rate variability indexes into an SVM (Support Vector Machine) model to judge a metabolic state, the method comprises the steps of analyzing the heat dissipation requirement by combining the change rate of the electric conductivity and the change direction of the body surface temperature, deriving the power requirement through cross logic operation, and predicting a rhythm inflection point to correct a refrigeration control instruction, and comprises the steps of optimizing processing links, improving the accuracy and adaptability of a scheme, combining the heart rate, the skin electric conductivity and the body surface temperature data, and improving the accuracy and adaptability of the scheme. The physiological state is divided by means of the circadian rhythm, the metabolism active state and the heat dissipation requirement are accurately judged, complex parameter dependence is reduced, the heat dissipation requirement judgment sensitivity and control precision are improved, the power requirement is accurately adjusted, and the refrigeration effect is optimized.

The application discloses a perioperative hypothermia management method and system, wherein the management method comprises the following steps: acquiring the surface temperature time series data of a target patient in a perioperative period in real time; converting the surface temperature time series data into core temperature change characteristics based on a pre-constructed body temperature conversion model, wherein the body temperature conversion model is constructed based on the correlation between the surface temperature time series data and the core temperature change characteristics; dynamically evaluating the hypothermia risk of the target patient based on the core temperature change characteristics to obtain a dynamic risk evaluation result; and automatically controlling a heating device based on the dynamic risk evaluation result. The surface temperature time series data is converted into core temperature change characteristics through the body temperature conversion model. The risk caused by invasive measurement is avoided, the accuracy of non-invasive body temperature monitoring is improved, and the patient's body temperature is dynamically adjusted by automatically controlling the heating device to automatically heat or stop heating in real time according to the dynamic risk evaluation result, so that automatic body temperature regulation is realized.

The invention relates to the technical field of biomedicine, in particular to a menstrual uterus-warming nursing device and an intelligent temperature control method thereof.In the process of conducting uterus-warming nursing on a user through the uterus-warming nursing device, body surface temperature data and blood flow data of the user within the coverage range of the uterus-warming nursing device at the current set temperature gear are obtained; analyzing the difference between the body surface temperature data and the standard temperature under the current set temperature gear, and determining the temperature achievement degree deviation at each monitoring moment; the change condition of the blood flow data is analyzed, and the thermal therapy effect at each monitoring moment is determined; and based on the change condition of the thermal therapy effect at each monitoring moment and the temperature achievement degree deviation at the current monitoring moment, determining whether to adjust a system target temperature in a temperature adjustment algorithm so as to realize self-adaptive control of the temperature in the uterus warming nursing process. According to the invention, temperature self-adaptive adjustment based on user physiological feedback can be realized.

The invention provides an infant body temperature real-time monitoring and early warning method and system, and relates to the technical field of infant guardianship, and the method comprises the steps: continuously collecting body surface temperature data and environment temperature data of an infant in real time, and preprocessing the body surface temperature data to obtain a preprocessed body surface temperature sequence; determining a dynamic body temperature baseline of the individual based on the body surface temperature sequence, and dynamically compensating the early warning threshold by combining the real-time environment temperature data to obtain an environment self-adaptive dynamic early warning threshold; based on the body surface temperature sequence and the dynamic early warning threshold, calculating a comprehensive early warning index reflecting the multi-dimensional characteristics of the body temperature change; and triggering corresponding graded early warning according to the value of the comprehensive early warning index, and dynamically adjusting monitoring parameters based on an early warning result. According to the invention, the problems of inaccurate early warning, untimely early warning and poor adaptability in the prior art can be integrally solved.

The application discloses a wearable pain relief device and a remote monitoring system thereof, which comprises a multi-modal physiological sensor array, a data fusion processing module, a control module, a transcutaneous electrical stimulation output module, a communication module and a remote monitoring system. The multi-modal sensor array collects pain-related physiological parameters such as electromyography, skin conductance, body surface temperature, heart rate and brain oxygen, the data fusion module generates a pain estimate value, the control module dynamically adjusts the stimulation intensity based on the PID+derivative compensation algorithm, and the transcutaneous electrical stimulation module outputs an electric current to intervene in pain. The communication module uploads data to the remote monitoring system, and medical staff can monitor and remotely adjust parameters in real time through the cloud platform. The application realizes real-time monitoring, intelligent control and remote intervention of pain, has the advantages of personalized treatment, data security and scalability, and is suitable for postoperative pain management, chronic neuropathic pain and the like.