295 results about "Skin temperature" patented technology

The invention discloses a perioperative hypothermia prediction and prevention system based on multi-modal data and deep learning. The system integrates skin temperature, physiological parameters (such as heart rate, blood pressure and oxyhemoglobin saturation) and operating room environment data (temperature, humidity, airflow and the like), and adopts a deep learning method (CNN-LSTM model, Transformer model and multi-modal fusion model) to carry out data analysis and hypothermia prediction. The system comprises a data acquisition module, a data processing module, a deep learning prediction module and a personalized temperature control module, can realize real-time low body temperature early warning, and provides a personalized intraoperative temperature control strategy. Experimental results show that the system abandons complexity, invasiveness and hysteresis of traditional hypothermia monitoring, hypothermia occurrence can be predicted 20-30 minutes in advance, and the accuracy of intraoperative management is improved. The method can be widely applied to the fields of anesthesia monitoring, operating room intelligent management and perioperative patient body temperature optimization control.

The invention relates to a seat self-adaptive adjusting system and method based on multi-modal biological data, and the system comprises a multi-modal data collection module, a data processing and fusion module, a control decision module, and an execution mechanism. Physiological and posture information of a user is collected through a heart rate sensor, a myoelectricity sensor, a skin temperature sensor, a pressure distribution sensor, a three-dimensional posture sensor and other multi-mode sensors, a fatigue index and a posture deviation amount are calculated through feature extraction, normalization and weighted fusion, and the fatigue index and the posture deviation amount are compared with preset threshold values. The control decision module generates adjusting instructions of the backrest angle, the waist support height, the cushion inclination angle and the temperature control power based on fuzzy control and a prediction algorithm, and self-adaptive adjustment of the seat is completed through an execution mechanism. The method can achieve the precise recognition and active intervention of the fatigue and posture change of the user, is suitable for various scenes such as driving, working and rehabilitation, can remarkably improve the comfort, delays the muscle fatigue, and improves the posture health.

The invention relates to the field of medical instruments, and discloses an anesthesia injury monitoring evaluation and management system for pain monitoring and rehabilitation acceleration. Comprising a sensor module configured to collect acupuncture point skin temperature data in a percutaneous acupuncture point electrical stimulation process, current parameter data output by an electrical stimulation device and skin impedance change data in real time; the control module is used for inputting the temperature data, the current parameter data and the skin impedance data which are acquired in real time into a multi-parameter risk assessment model, calculating a real-time risk value and generating a parameter change curve containing a time sequence; when the real-time risk value exceeds a preset safety threshold value, or any single parameter in the parameter change curve reaches a temperature change rate threshold value, an accumulated electrical stimulation energy threshold value or a skin impedance abnormal fluctuation threshold value, triggering a multi-stage early warning signal; according to the early warning level of the early warning module, the output power, the pulse frequency or the action time of the electrical stimulation device is automatically adjusted, or electrical stimulation is forcibly terminated when early warning is performed at the highest level.

The invention discloses an acupuncture stimulation evaluation method based on multi-physiological signal fusion real-time monitoring, relates to the technical field of acupuncture medical treatment, and aims to accurately judge a phase locking state through correlation analysis of an absolute value of a myoelectricity attenuation slope and a skin temperature phase difference standard deviation, break through the limitation of a single signal dimension and improve the judgment accuracy to 90% or above. A linear prediction model is constructed based on clinical data, and dynamic correction is performed in combination with a compensation coefficient when a beta wave ratio exceeds a standard, so that personalized needle retaining time prediction is realized, and the prediction deviation rate is effectively reduced; when the accumulated phase locking time reaches a predicted value, a needle retaining adjustment instruction is triggered automatically, a'monitoring-prediction-execution 'closed loop is formed, invalid treatment time is shortened by about 15%, and acupuncture operation efficiency is improved; model parameters are corrected in real time through beta wave anomaly monitoring, curative effect deviation caused by muscle tension or nerve imbalance is inhibited, the system false alarm rate is reduced to 3% or below, and robustness is remarkably superior to that of a traditional method.

The invention relates to the technical field of human body temperature prediction, and provides a human body skin temperature prediction method and system fusing an informer and STGCN. The method comprises the following steps: according to a topological structure among a plurality of measurement points of acquired skin temperature data of a target object, based on a space-time diagram convolutional network, extracting space time sequence characteristics of the measurement points, and based on a first informer module of a self-attention mechanism, respectively according to a data matrix of the skin temperature data and a data matrix of acquired environmental parameter data; respectively extracting temperature time sequence characteristics and environment time sequence characteristics of the measurement points; and then, fusing the space time sequence characteristics, the temperature time sequence characteristics and the environment time sequence characteristics of the measurement points in a second informer module based on a self-attention mechanism according to a time sequence, inputting an obtained characteristic matrix into a full-connection neural network, and predicting the skin temperature of a target measurement point.

The invention relates to the technical field of intelligent health monitoring, in particular to a physiological signal driven diabetes mellitus metabolism risk modeling analysis system which comprises a variable sorting module, an electrocardio shearing module, a distribution edge forming module, a risk modeling module and a regulation and control deconstruction module. According to the method, the fluctuation response time difference between the skin temperature and the blood oxygen signal is obtained, distribution density analysis is conducted on the time difference, the samples are divided into response difference groups, and layered recognition of the signal time dynamic characteristics is achieved; a peak-valley amplitude sequence in the electrocardiogram periodic signal is further extracted, an amplitude withdrawing ratio is calculated, a key turning point is identified according to a threshold value, and the corresponding periodic signal is divided into different electrocardiogram segments, so that the micro electrocardiogram fluctuation response is effectively positioned; on the basis, according to the time index, the asynchronous distribution section of the skin temperature and the blood oxygen is backtracked, a cross boundary graph between the asynchronous signals is constructed, and the asymmetric response mode of skin temperature and blood oxygen changes can be analyzed in a refined mode.

This document describes systems, methods, devices, and other techniques used for improving a sleeper's body thermoregulation during sleep. One aspect is a system, comprising a bed with a heating element and a cooling element and a controller configured to receive a current sleep state of a sleep stage sequence for a user in the bed, when the current sleep state is a non-rapid eye movement (NREM) state, activating the heating element to increase a skin temperature of the user, and when the current sleep state is a rapid eye movement (REM) state, activating the cooling element to decrease the skin temperature of the user.

The present disclosure relates to devices and methods for cosmetic treatment of a skin of a subject with RF energy. Examples of the present disclosure include movable electrodes and / or movable skin temperatures sensors.

The invention discloses an intelligent moxibustion control method and system, and belongs to the technical field of medical care, and the method comprises the steps: obtaining skin image data and moxibustion interference data of a current moxibustion part, and generating a skin health index; according to the skin health index, whether the skin of the current moxibustion part is abnormal or not is judged; if the skin of the current moxibustion part is abnormal, state data of a moxa stick and the moxibustion environment temperature are obtained, and a moxa stick distance adjustment value is generated; adjusting the distance between the moxa stick and the skin of the moxibustion object according to the moxa stick distance adjustment value; according to the method, the skin temperature, color distribution and scratching behavior data are collected in real time, the environment temperature and the moxa stick combustion state are combined, the skin health index model and the distance adjustment analysis model are constructed, dynamic closed-loop control over the moxibustion distance is achieved, meanwhile, the method adapts to different scenes through environment sensitive factor optimization, the user experience is enhanced, and the user experience is improved. The accuracy and safety of moxibustion treatment are remarkably improved, and the risk of skin burn or redness and swelling is effectively avoided.

The invention discloses an AI-driven dynamic body temperature monitoring system and aims to solve the problem that existing body temperature detection equipment is difficult to adapt to individual differences and environment dynamic changes. The system comprises a temperature sensing unit, an environment acquisition unit and a heart rate sensing unit which are respectively used for acquiring skin temperature, environment parameters and heart rate variation characteristics; the system constructs a body temperature and environment incidence matrix, extracts a nonlinear coupling region, and fuses heart rate features to generate a three-mode state tensor; abnormal sensitivity is evaluated through an attention mechanism and a graph neural network model, and an individualized fever judgment threshold is dynamically generated in combination with a historical stable state, so that an accurate health response decision is realized; and the system further outputs behavior suggestions based on the decision result, such as water replenishing or medical treatment prompting, so that the intelligence and practicability of body temperature monitoring are improved.

According to the invention, the ultrasonic device for skin treatment comprises an external part which is composed of a device body, the middle part of the device body is provided with an indicating lamp for indicating the operation state of the device, a switch for turning on and turning off the device and a mechanism part, and the mechanism part is composed of energy connected to a circuit control panel. The circuit control panel comprises a short circuit detection circuit, a Bluetooth and / or Wi-Fi receiver and transmitter and a skin temperature monitoring circuit. The circuit control panel transmits current to the electromagnetic electrode and the electrical stimulation muscle electrode ultrasonic transducer, and the ultrasonic transducer is composed of a deeper-focal-length ultrasonic transducer and a shallow-focal-length ultrasonic transducer. Two transducers, each consisting of electrodes, are connected to a piezoelectric material for transmitting electrical energy to the piezoelectric material, and a solid or semi-solid material that can transmit ultrasonic waves for strengthening the ultrasonic waves to a desired skin layer.

The invention relates to the technical field of medical instruments, in particular to an electromagnetic focusing extracorporeal shock wave pancreatic lithotripsy device and method.The electromagnetic focusing extracorporeal shock wave pancreatic lithotripsy device comprises a device body, a bed body is installed on one side of the device body through a supporting frame, and a lithotripsy notch is formed in the side, close to the device body, of the bed body; a large C-shaped arm and a small C-shaped arm installed on the inner side of the large C-shaped arm are installed at the position of the notch of the device body, an X camera imager is installed at the upper end of the large C-shaped arm, and a shock wave generator and an ultrasonic probe installed on one side of the shock wave generator are installed on the small C-shaped arm. An energy adjusting module used for controlling the shock wave generator and a safety detection module used for detecting the skin temperature are arranged in the device body, and a displayer and a human-computer interaction interface are arranged on one side of the device body. The technical scheme in the prior art has limitations on shock wave generation, positioning precision, energy regulation and control and treatment strategies.

This invention provides a thermal comfort evaluation method based on infrared thermal imaging technology, comprising: real-time acquisition of infrared thermal imaging data of a target object; determination of skin temperature data of the region of interest on the target object's face based on the infrared thermal imaging data; calculation of the thermal sensation level using the skin temperature data and a thermal sensation evaluation model; and adjustment of the temperature setting of the target device according to the thermal sensation level. This invention uses only the skin temperature of a single area (e.g., facial skin temperature) to evaluate thermal sensation, which is simple, convenient, and highly accurate; it does not require the user to wear a smart device to collect skin temperature, directly acquiring the user's facial skin temperature in a non-contact manner.

The invention discloses a tumor radiotherapy prognosis prediction simulation method and system based on big data and a medium, and relates to the technical field of tumor radiotherapy prognosis, and the method comprises the following steps: collecting basic physiological information of a tumor patient, and collecting a color image and a temperature image of skin of a radiotherapy part of the tumor patient; skin color feature extraction and skin temperature feature extraction are carried out to obtain skin color feature data and skin temperature feature data; a radiodermatitis prediction model is constructed; performing prediction simulation on the skin of the radiotherapy part of the tumor patient based on the radiodermatitis prediction model, and performing prediction simulation correction to obtain a radiodermatitis prediction result of the tumor patient; the method is used for solving the problem that when an existing tumor radiotherapy prognosis technology is used for predicting and simulating disease development, the risk and time of radiodermatitis of a tumor patient cannot be objectively and accurately predicted and simulated according to physiological characteristics of skin of the tumor patient after radiotherapy.

The invention discloses a massage effect evaluation method and system, and the method comprises the following steps: S1, data collection: obtaining a plurality of physiological parameters; s2, data preprocessing: carrying out filtering, normalization and feature extraction processing on the physiological parameters; s3, effect evaluation: inputting the data after feature extraction into an effect evaluation model, and adaptively outputting an evaluation result by the effect evaluation model according to the massage manipulation; and S4, optimization iteration: optimizing the effect evaluation model by adopting a gradient descent method so as to improve the evaluation effect. The massage effect is evaluated by fusing the EMG feature, the skin temperature feature, the pressure distribution feature, the HRV feature and other parameter data, and the evaluation effect is more accurate.

The invention provides a patch type thrombus monitoring and NO release closed-loop system for treating venous thrombosis, which comprises a flexible patch substrate on which a sensor module is integrated, and the sensor module comprises a blood flow velocity sensor, a biological impedance sensor, an acceleration sensor and a temperature sensor, the acquisition units are respectively used for acquiring blood flow velocity v at a target vein, related parameters of vascular resistance R, limb movement states and skin temperature of a patch area; the NO release module is used for releasing NO to act on the venous thrombosis part; the control module comprises a signal processing unit and a control unit and is used for receiving the signal output by the sensor module and operating a closed-loop control algorithm to generate an NO release control instruction; and the power supply module provides electric energy for the sensor module, the control module and the NO release module. The invention provides a patch type closed-loop system which integrates thrombus multi-mode monitoring, decision making, NO release assisting and treatment mode self-adaptive switching.

An approach is provided for multiple-device wearability-aware heat orchestration. The approach involves, for example, determining a predicted skin temperature at a skin contact point of a wearable device. The approach also involves determining a wear status of the wearable device. The approach further involves determining a wearable temperature threshold of the wearable device based on the wear status. The approach further involves delegating at least one portion of a computational workload of the wearable device to at least one other device based on determining that the predicted skin temperature is greater than the wearable temperature threshold.

The invention belongs to the field of human body detection devices, and provides a wearable system for evaluating pain, which comprises wearable equipment in communication connection with a cloud system. The wearable device is used for continuously collecting physiological signals when a patient wears the wearable device. The cloud system is provided with a hierarchical evaluation module, a correction module and an intervention control module, the hierarchical evaluation module extracts physiological features in a long-term time window, extracts skin electroreaction mutation, a myoelectricity activity peak value and skin temperature rapid change in a short-term time window, and deduces an acute pain level in combination with instant self-evaluation information of a patient; the correction module is used for correcting the acute score based on the mapping relation between the long-term stability characteristic and the acute pain level and an individualized threshold value; the intervention control module generates individualized electrical stimulation control parameters according to the correction result and issues the individualized electrical stimulation control parameters to the wearable device, and the electrical stimulation execution unit outputs a stimulation signal through the percutaneous electrode to relieve pain of the patient and uploads a feedback signal to the cloud end to form a closed loop.

The invention relates to the technical field of medical detection, and particularly discloses a human body microcirculation change monitoring method and device.The human body microcirculation change monitoring method comprises the steps that the body surface skin temperature of a specific limb of a patient and the intracavity temperature of the patient are monitored; when the first difference value between the intracavity temperature and the body surface skin temperature is larger than a third threshold value, it is judged that microcirculation insufficiency occurs at the specific limbs of the patient. Monitoring the change condition of the first difference value in a third preset time period; when the first difference value is gradually reduced in a third preset time period, judging that the microcirculation blood flow of the patient enters a recovery state; and when the first difference value is gradually increased in a third preset time period, judging that the microcirculation blood flow of the patient enters a deterioration state. The microcirculation change of the patient is evaluated based on the body surface skin temperature, the intracavity temperature and other information of the specific limbs of the patient, non-invasive monitoring on the microcirculation change of the patient can be achieved, and then early warning analysis on the illness state of the patient can be achieved according to the microcirculation change condition of the patient.

The invention relates to the technical field of data analysis, and discloses a blood glucose monitoring control system and a control method, which realize accurate dynamic monitoring of a blood glucose state through acquisition, alignment and fusion of multi-source physiological signals. The system firstly collects blood glucose, skin temperature, acceleration and skin electric signals, and performs time compensation and filtering processing to ensure data synchronization. Inertia correction is calculated according to changes of blood glucose and skin temperature, delay and physiological inertia influences are eliminated, and abnormal jumps are recognized. The interference intensity is calculated in combination with movement and galvanic skin change, and the blood glucose value is corrected. The stability of the system is dynamically adjusted by analyzing the mean value and variance of recent blood glucose data. Short-term trend prediction is generated by combining the blood glucose change rate and the acceleration, and dynamic correction is performed when the change is severe. The individual risk is evaluated according to the predicted deviation from the current blood sugar, and early warning or intervention prompt is automatically sent out when the high-low blood sugar risk occurs.

The invention provides a cardiovascular postoperative gradient pressure reduction type hemostasis device, and relates to the technical field of medical instruments, the cardiovascular postoperative gradient pressure reduction type hemostasis device comprises a controller, a pressing assembly and fixing assemblies, the pressing assembly and the fixing assemblies are electrically connected with the controller, and the two fixing assemblies are symmetrically connected to the two sides of the pressing assembly; an initial pressure setting module and a gradient decompression curve generation module are configured in the controller; the pressing assembly comprises a positioning ring and a pressing column penetrating through the center of the positioning ring; the fixing assembly comprises a deformation claw and a flexible adsorption block connected to the deformation claw. By monitoring the biological impedance and the skin temperature in real time and combining the self-adaptive gradient decompression algorithm to dynamically adjust the pressure, personalized hemostasis is achieved, limitation of a traditional constant pressure mode is avoided, the risk of postoperative complications is reduced, and the comfort and safety of a patient are improved; the problem that in the prior art, the treatment effect is poor due to the fact that pressing hemostasis is conducted through experience or a device with fixed strength is used is solved.

A solar radiation protective band for a driver that includes a housing and an armband. The housing includes a front panel, a side panel, and a microcontroller. The front panel includes a front panel UV light sensor, a front panel IR phototransistor, and an LCD. The side panel includes a side panel UV light sensor, and a side panel IR phototransistor. A temperature sensor measures a skin temperature and generates a temperature signal. A skin color sensor detects a skin color of the driver and generates a skin color signal. The microcontroller requests an input of a SPF of a sunscreen used by the driver; calculates an exposure time threshold; generates a UV exposure warning when an exposure time exceeds the exposure time threshold; calculates an updated skin temperature; and generates an IR exposure warning when the updated skin temperature exceeds a maximum skin temperature threshold.

The invention discloses a non-invasive skin drug delivery control method and system based on big data analysis, and the method comprises the steps: collecting multi-dimensional data, such as skin thickness, metabolic capability, allergic constitution, electrical impedance value, skin temperature and humidity, through a physiological parameter sensor array, and carrying out the classification and recognition of individual physiological features through a clustering algorithm. When individual parameters exceed a preset penetration threshold value, a real-time monitoring module is automatically activated, the drug administration intensity adjustment direction is judged by analyzing electrical impedance value fluctuation characteristics, a penetration depth prediction model is constructed by fusing skin temperature data, and deviation feedback optimization of a prediction value and an actual monitoring value is achieved. Allergic physical characteristics are further extracted and combined with metabolic capacity data to construct a dynamic regulation and control sequence, personalized administration intensity parameters are generated to drive an actuator to adjust equipment output, continuous and accurate permeation rate control is achieved through loop iterative optimization, the contradiction between individual differential administration requirements and equipment standardized output is effectively solved, and the method is suitable for large-scale popularization and application. The safety and the effectiveness of noninvasive administration are obviously improved.

1. The name of the design product: physiological signal detector. 2. The use of the design product: for continuous acquisition of human motion, skin temperature, pulse, blood oxygen, electrocardiogram, electroencephalogram, ambient light, air pressure and other signals. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

1. The name of the design product: industrial infrared temperature measuring gun. 2. The use of the design product: for measuring human body temperature, skin temperature, object temperature, liquid temperature. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: front view.

The present invention comprises: a high-frequency oscillator that transmits high-frequency energy and includes a control unit; a high-frequency connecting line connected to the high-frequency oscillator; and a high-frequency transmission pad connected to the other end of the high-frequency connecting line and attached to the curve of facial skin in close contact with it, wherein the high-frequency transmission pad is configured such that an adhesive pad and a bipolar pad are integrated or separate. This invention relates to a non-invasive automatic facial lifting device using high-frequency energy that adheres closely to the curves of the face to be treated, thereby enabling uniform delivery of high-frequency energy to the skin, allowing for effective treatment without separate operation, minimizing the risk of excessive thermal damage to specific areas of the skin, resolving issues such as pain, scarring, and infection associated with existing invasive technologies, enhancing user convenience and safety through an automated control system and customized settings, and providing uniform treatment effects and reducing treatment time and fatigue by monitoring skin temperature in real time and delivering high-frequency energy according to set output, time, and patterns.

This invention relates to a method for synchronous prediction of human thermal injury based on a dynamically coupled physiological model. First, a refined, segmented, multi-layered human physiological thermal model is constructed. Based on this model, a set of coupled biological heat transfer equations is established, embedding an active thermoregulation mechanism mediated by the human central nervous system. This set of equations is solved by deeply and dynamically coupling skin temperature, core temperature, and physiological parameters such as blood perfusion rate, metabolic rate, and sweat evaporation. Subsequently, by setting the initial and boundary conditions of a fire scene operation, the coupled equations are solved in one go using numerical methods. During the same solution process, the system synchronously and in parallel performs segmented skin burn risk assessment and overall human heat stress risk assessment. This invention overcomes the limitations of traditional models in segmented prediction and coupled active thermoregulation, achieving effective synchronous early warning of skin burn risk and overall heat stress risk in various parts of the human body under extreme thermal environments.

The present application relates to the technical field of human body temperature prediction, and provides a human skin temperature prediction method and system that integrates Informer and STGCN. According to the topological structure among multiple measurement points of the skin temperature data of the target object obtained, based on the spatio-temporal graph convolutional network, the spatio-temporal features of the measurement points are extracted, and based on the first Informer module with self-attention mechanism, according to the data matrix of the skin temperature data and the data matrix of the obtained environmental parameter data respectively, the temperature time series features and environmental time series features of the measurement points are extracted respectively; then, the spatio-temporal features, temperature time series features, and environmental time series features of the measurement points are fused in the second Informer module with self-attention mechanism according to the time series, and the obtained feature matrix is input into the fully connected neural network to predict the skin temperature of the target measurement point.

An object of a system according to an embodiment is to enable a user to easily grasp his or her health condition and obtain appropriate advice.SOLUTION: A system includes a measurement unit including a bioimpedance sensor, a measurement unit including an infrared sensor, an analysis unit, and a provision unit. The measuring unit including the bioimpedance sensor measures the body fat percentage of the user. The measurement unit including an infrared sensor measures a skin temperature. The analysis unit analyzes the data measured by the measurement unit. The providing unit provides a comment and advice to the user on the basis of the analysis result obtained by the analysis unit.SELECTED DRAWING: Figure 1

The present disclosure may include: an electrode unit including at least one electrode; an energy supply unit that applies a high-frequency voltage to the at least one electrode; and a processor that obtains impedance in the skin on the basis of the applied high-frequency voltage, calculates the temperature of the skin on the basis of the obtained impedance, and controls the energy supply unit so as to apply a high-frequency voltage associated with the temperature of the skin to the at least one electrode.