1061 results about "Blood pressure" patented technology

The invention relates to the technical field of diagnosis, in particular to a diagnosis and treatment auxiliary system and method for the obstetrics and gynecology department, and the system comprises a parameter collection module, a feature offset recognition module, a feature reconstruction module, a collaborative trend recognition module and a diagnosis and treatment suggestion generation module. According to the system and the method, the body temperature, the heart rate, the pulse, the blood pressure and the image edge density are synchronously acquired and the timestamps are bound, so that a structured diagnosis and treatment data unit is formed, the time sequence comparison capability of multi-source information is effectively improved, and potential risk points can be positioned and feature tags can be constructed based on a numerical value offset identification and synchronous index combined judgment mechanism; according to the method, physical signs, images and laboratory data are normalized and fused into three-dimensional vectors, cross-dimensional feature linkage expression is achieved, the dynamic insight ability to pathological state changes is improved by screening features with large variation amplitude and long duration time and judging trend consistency, and the accurate response to the fetal risk state is enhanced by combining a specific trend combination matching rule.

The invention relates to an intelligent blood pressure measuring method and system based on deflation oscillography, and belongs to the technical field of medical detection.The measuring method comprises the steps that an air pump is controlled to inflate air into a cuff of the wrist or the upper arm of a testee till a preset initial air pressure value is reached; controlling an electromagnetic valve to release gas in the cuff at a preset rate, and receiving air pressure data and oscillatory wave signals, which are collected by a pressure sensor in real time, in the cuff; identifying the oscillatory wave signal based on a characteristic value method and extracting key characteristics to obtain oscillatory wave characteristic parameters; based on a pre-established proportionality coefficient model, a preliminary blood pressure value is calculated according to the air pressure data and the oscillatory wave characteristic parameters; and inputting the oscillatory wave signal, the oscillatory wave characteristic parameter and the initial blood pressure value into a pre-trained blood pressure value prediction model with a momentum item to obtain a final blood pressure value, and sending the final blood pressure value to a display module for output and display. The precision and stability of blood pressure measurement are improved.

A device and algorithm for controlling an autonomic function in an individual. A controller device that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure. A control interface and algorithm for controlling an autonomic function in a subject. For instance, an algorithm that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure.

The invention discloses a sea cucumber protein heptapeptide with functions of reducing blood pressure and blood sugar and application of the sea cucumber protein heptapeptide, and belongs to the technical field of bioactive peptide biology. The amino acid sequence of the sea cucumber protein heptapeptide is LPPGPFP. The sea cucumber protein heptapeptide can significantly inhibit the activity of ACE through a competitive inhibition mode, tolerates the gastrointestinal tract digestion environment, also has DPP-IV inhibition activity, can relieve hypertension and type 2 diabetes mellitus at the same time, and has an application value in preparation of products with the efficacy of reducing blood pressure and blood sugar due to multiple functions of the sea cucumber protein heptapeptide. The sea cucumber protein heptapeptide provided by the invention can significantly inhibit the activity of ACE through a competitive inhibition mode, has DPP-IV inhibition activity, has the characteristics of simple structure, safety, strong activity and the like, and has a wide application prospect.

The invention relates to the technical field of cardiovascular medicine, in particular to an automatic alarm system for cardiovascular medicine, which comprises a biomarker analysis module, a physiological parameter analysis module, a cardiovascular risk assessment module, a cardiovascular early warning adjustment module and an alarm trigger notification module. According to the invention, by integrating real-time monitoring of blood biomarkers and cardiovascular physiological parameters, the early recognition capability of cardiovascular disease risks is improved, key biomarkers are dynamically measured and compared with historical marker data, and subtle physiological changes can be captured at the early stage of asymptomatic conditions, so that potential cardiovascular events are warned; through correlation analysis of electrocardiogram, blood pressure and pulse waveforms, the system can accurately draw a comprehensive image of cardiovascular functions, so that more targeted monitoring and intervention are implemented, timeliness and accuracy of medical response are ensured, doctors can formulate targeted monitoring schemes according to real-time data, and the monitoring efficiency is improved. Therefore, deterioration or occurrence of cardiovascular events of patients can be effectively prevented.

The invention discloses a noninvasive blood pressure prediction method of a Conformer-LSTM model based on multi-scale feature fusion, and the method comprises the steps: synchronously collecting a PPG signal and an ABP signal of a user, and carrying out the preprocessing of the collected PPG signal; the preprocessed PPG signals and the preprocessed ABP signals are input into a Conformer-LSTM blood pressure prediction model; the input PPG signal is subjected to Conforeemer model extraction and fusion of features of multiple scales, the features are transmitted to the LSTM network, the LSTM network carries out modeling on a time sequence through the extracted features of multiple scales, and finally a predicted ABP waveform is output through a full connection layer; and calculating systolic pressure and diastolic pressure through the predicted ABP waveform. According to the method, the Conformer-LSTM model is adopted, the features of different scales of the PPG signals can be extracted, the features of multiple scales are effectively fused, the key information of the current task can be rapidly extracted from the complex waveform features through the algorithm, the problem that the manually extracted features are unstable due to the diversity of crowds is avoided, and the accuracy of the algorithm is improved. And the applicability of the model to different waveforms is improved.

The invention discloses an ear-nose-throat department symptom monitoring method and system based on multi-modal data fusion, and relates to the technical field of medical monitoring. Comprising the steps of monitoring physiological data in real time, calling historical medical record data, collecting environment data, and preprocessing the monitored, called and collected data; carrying out feature fusion on the preprocessed data, extracting potential associated features, and carrying out multilevel and sequential feature learning; on the basis of the extracted features, an improved long-short-term memory network is used for conducting symptom prediction, in combination with historical trends of the blood sugar and the blood pressure of the patient, correlation between the symptoms and ear-nose-throat symptoms is evaluated in real time, and personalized symptom early warning is output; and sending a health prompt to the patient through the intelligent equipment or the mobile terminal application in real time. According to the invention, conventional symptom early warning can be carried out, and personalized health intervention measures can be provided according to individual health conditions.

The invention provides a small-capacity air bag blood pressure detection system and a precise pressure control method thereof. A micro air pump is communicated with an air inlet of a small-capacity air bag through a pipeline, and a linear proportional valve is arranged on an air release opening of the small-capacity air bag and used for controlling the opening, closing and flow of the air release opening of the small-capacity air bag; the miniature air pump is normally opened and provides stable-flow input air flow for the small-capacity air bag, the valve opening degree of the linear proportional valve is changed by executing a self-adaptive differential constant-pressure control algorithm, then the air release speed of an air release opening of the small-capacity air bag is changed, and pressure adjustment of the small-capacity air bag is achieved by changing the difference between the inflation speed and the deflation speed. According to the invention, rapid pressure stabilization can be realized, and pressure overshoot is hardly generated after the pressure is stabilized; the pressure control precision of 1mmHg at any pressure regulation step length is realized; the problem that the traditional single-parameter closed-loop control cannot meet the precise control of each pressure interval is solved; the production cost is further reduced, and the out-of-hospital scene adaptability and the popularization degree of the equipment are improved.

The invention relates to the technical field of medical data processing, in particular to an internal medicine emergency treatment data processing method and system based on cloud computing, and the method comprises the following steps: monitoring the data of an emergency treatment patient, carrying out the dynamic interval correction of the systolic pressure, diastolic pressure and blood oxygen critical values of the patient through the analysis of the age, gender and weight, and generating an index threshold interval. According to the method, the abnormal physiological parameter detection threshold value is adjusted, the actual health condition of the patient is accurately reflected, the correlation and fluctuation trend of multiple physiological data are analyzed, the emergency degree of the emergency patient is effectively evaluated, the data transmission priority is optimized, key information is ensured to be transmitted in time, and encryption in the data transmission process is combined; according to the method, the integrity and the reliability of data are guaranteed, the storage position and the access priority are dynamically adjusted according to the access frequency and the activeness of the data, the data retrieval efficiency is improved, the utilization of storage resources is optimized, the response speed and the processing capacity are improved, and reliable real-time support is provided for medical staff.

The invention provides a health management method with a health data analysis function. The health management method with the health data analysis function comprises the following steps: S1, collecting health data information of a user body through existing equipment, and establishing a personal health record according to the data information, wherein the body data information comprises but is not limited to blood pressure, heart rhythm and blood sugar; s2, the collected health data need to be cleaned, sorted and preprocessed before a personal health record is established, so that subsequent data analysis is facilitated; and S3, according to the health data of the user, performing health risk assessment by using a machine learning model and a deep learning model algorithm, and predicting possible health risks, including but not limited to cardiovascular diseases and diabetes, of the user. The health management method with the health data analysis function provided by the invention has the advantages that the accuracy and individuation level of health management can be improved, and the requirements of people on health are met.

The invention provides ACE (Angiotensin Converting Enzyme) inhibitory peptide, middle-aged and elderly formula goat milk powder and a preparation method thereof, goat milk is taken as a raw material, the goat milk is sterilized and cooled, compound protease consisting of three proteases is inoculated for constant-temperature enzymolysis, and the ACE inhibitory peptide is obtained through ultrafiltration, preparative chromatographic separation and freeze drying. And uniformly mixing the active peptide with a nutrition enhancer and goat milk powder required by the middle-aged and elderly people to obtain the active peptide goat milk powder for the middle-aged and elderly people. Or after the goat milk is subjected to enzymolysis by compound protease, directly adding a nutrition enhancer required by the middle-aged and elderly people, and then concentrating and spray-drying to obtain the formula goat milk powder for the middle-aged and elderly people. The ACE inhibitory peptide prepared by the invention can be used as a food functional factor, and the prepared formula goat milk powder for middle-aged and elderly people contains the ACE inhibitory peptide and has the function of assisting in lowering blood pressure.

The invention provides a blood pressure measurement system and method based on multi-airbag cooperative control and oscillatory wave analysis, and relates to the technical field of medical instruments. Comprising an integrated cuff cover body, an inflator pump, an electromagnetic valve, a pressure balancing device and a microprocessor, a first air bag, a second air bag and a third air bag are arranged in the integrated cuff cover body, firstly, an inflation pump is started, the multiple air bags are synchronously inflated to preset initial pressure, then a first air bag electromagnetic valve and a third air bag electromagnetic valve are closed, a pressure balance device dynamically adjusts a miniature deflation valve, and the pressure in the first air bag and the pressure in the third air bag are kept constant; the inflator pump continues to inflate until the pressure in the second airbag is higher than the systolic pressure level; the measuring method specifically comprises a multi-air-bag pressure measuring mode and a double-air-bag pressure measuring mode. The multi-air-bag pressure measuring mode is that three air bags are used for measuring pressure at the same time, and the double-air-bag pressure measuring mode is that only the second air bag and the third air bag are pressurized, so that blood pressure measurement is achieved.

The invention provides a sudden cardiac death high-risk group multi-modal data intelligent analysis and prediction method and system, and relates to the technical field of medical health monitoring, and the method comprises the steps: collecting multi-modal data, projecting an electrocardiogram to a three-dimensional coordinate system, extracting potential trajectory features, and calculating a space-time discrete index; performing dynamic response analysis on the blood pressure data, and matching with a space-time discrete index to calculate a cardiovascular coupling coefficient; and performing segmented correction according to the motion state data, monitoring a coupling coefficient deviation condition in real time, calculating a risk degree and generating an early warning. According to the method, heart abnormity can be found in advance, and sudden cardiac death can be effectively prevented.

The invention discloses ACE (Angiotensin Converting Enzyme) inhibitory octapeptide YI8 derived from bovine cheese protein hydrolysate and application, and relates to the technical field of bioactive peptides, and the technical scheme is characterized in that the ACE inhibitory octapeptide YI8 comprises an amino acid sequence of YKVPQLEI. The ACE inhibitory octapeptide YI8 derived from the cattle cheese protein hydrolysate is obtained by screening from the cattle cheese protein hydrolysate, and is an octapeptide YI8 with ACE inhibitory activity, the in-vitro ACE inhibition rate of the ACE inhibitory octapeptide YI8 derived from the cattle cheese protein hydrolysate is tested to be 70.86% under the condition of the concentration of 1mg / ml, and the ACE inhibitory octapeptide YI8 is suitable for functional food for assisting in lowering blood pressure.

The present application provides a soybean antihypertensive peptide and its screening method and application, which belongs to the field of polypeptides. The soybean antihypertensive peptide provided in the present application includes one or more of soybean antihypertensive peptide I with a molecular weight of less than 1000Da, soybean antihypertensive peptide II with a molecular weight of less than 1000Da, and soybean antihypertensive peptide III with a molecular weight of less than 1000Da; wherein, the soybean antihypertensive peptide I with a molecular weight of less than 1000Da is prepared by nattokinase enzymatic hydrolysis of soybean protein isolate, the soybean antihypertensive peptide III with a molecular weight of less than 1000Da is prepared by Bacillus subtilis liquid fermentation of soybean protein hydrolysate, and the soybean antihypertensive peptide III with a molecular weight of less than 1000Da is prepared by Bacillus subtilis solid fermentation of soybeans. The soybean antihypertensive peptide of the present application is a plant-derived antihypertensive peptide with high angiotensin converting enzyme inhibition rate and good antihypertensive effect. And it has been verified by animal experiments that the soybean antihypertensive peptide of the present application can significantly reduce the heart rate, diastolic blood pressure and systolic blood pressure of rats, and has less toxic and side effects.

The invention provides a blood pressure measurement system and method based on oscillatory wave dynamic characteristics and regression modeling, and relates to the technical field of wearable medical health monitoring. A signal processing method serves as a main body, oscillatory wave key features are extracted through time domain, frequency domain, time frequency and a statistical method, traditional features are finely adjusted through a lightweight deep learning model, and finally the mapping relation between feature wave band changes and blood pressure values is established through machine learning. Not only can the complete oscillation wave waveform be predicted through the characteristic change of part of oscillation waves to realize low-pressure comfortable measurement, but also personalized blood pressure measurement can be realized by identifying the characteristic mutation point of the oscillation waves. According to the method, the interpretability and the stability of a traditional method are guaranteed, the feature recognition precision and the individual adaptive capacity are improved through lightweight deep learning fine adjustment, edge calculation can be achieved, and therefore the measurement time is shortened, and the user comfort level, the measurement accuracy and the system practicability are improved.

The invention belongs to the technical field of computer vision, and discloses a human face video blood pressure prediction method based on multi-scale attention constraint, which comprises the following steps: step 1, extracting a remote photoplethysmography (rPPG) signal; firstly, a face is detected in a video through an MTCNN face detection algorithm, a region of interest (ROI) is divided, an effective face region is extracted, then an rPPG signal carrying noise is preliminarily extracted in combination with optical flow estimation and median filtering, in a blood pressure prediction part, baseline drift removal, secondary filtering and other processing are carried out on the rPPG signal to obtain a relatively clean signal, and then the effective face region is extracted. Performing window segmentation on the rPPG signal; and 2, designing an EBP-Net model, and inputting the rPPG signal into the EBP-Net model to predict systolic pressure and diastolic pressure. According to the invention, the types of signals required by blood pressure measurement are simplified, only rPPG signals are required, the measurement error is minimum, and the cost of signal acquisition is reduced.

The invention discloses a non-contact blood pressure prediction method based on multi-modal fusion. The method comprises the following steps: firstly, carrying out preprocessing such as space-time alignment and face region cutting on visible light video and infrared video sequences; then, obtaining multi-scale and multi-channel depth feature representations from the visible light image and the infrared light image through an independent feature extraction module, and generating adaptive weights for two modals in a space-channel dimension by using a dynamic weighted fusion mechanism based on L1 / L2 mixed norm evaluation and Softmax normalization combination; fusing into a uniform feature vector according to a complementary principle; finally, fitting and reconstruction of rPPG signals are carried out based on the fusion features, the reconstructed pulse wave signals are input into a blood pressure prediction network at the tail end, and high-precision non-contact estimation of systolic pressure and diastolic pressure is achieved. According to the method, visible light and infrared light videos are cooperatively analyzed, and the problem that an existing face-based video method is sensitive to illumination conditions is successfully solved.

The invention discloses an automatic positive pressure tube sealing device and a tube washing device in the technical field of medical auxiliary instruments. The automatic positive pressure pipe sealing device comprises a liquid supply mechanism, the liquid supply mechanism comprises a liquid storage pipe and a pushing assembly, and the pushing assembly is arranged in a containing cavity of the liquid storage pipe. The pushing assembly comprises a piston and a pushing rod, the piston is arranged in the containing cavity, an elastic piece is arranged between the pushing rod and the piston, mechanical energy generated when the pushing rod moves is converted into stable elastic potential energy, the elastic piece is used for slowly releasing the elastic potential energy, and the piston can apply pressure to liquid in the liquid storage pipe for a long time; the liquid in the liquid storage tube is in a positive pressure state for a long time and can be in a positive pressure state relative to the blood pressure of a human body for a long time, and blood is prevented from flowing back to the venous catheter. After the push rod moves towards the piston by a certain distance, the push rod and the liquid storage pipe can be kept relatively fixed, the elastic piece can release elastic potential energy in the direction close to the piston, the elastic potential energy of the elastic piece completely acts on the piston, and automatic pipe sealing operation is achieved.

The invention discloses a blood pressure measuring method, a user interface and a related device.According to the method, after blood pressure measuring operation is detected, whether a user has a heartbeat irregular symptom or not is judged based on historically-collected first data and / or second data collected after the blood pressure measuring operation is detected; and determining the blood pressure value of the user on the basis of the blood pressure values measured for multiple times under the condition of determining that the user has the symptom of irregular heartbeat. In this way, the user does not need to actively inform the device of the symptom of irregular heartbeat, the trouble of user operation is reduced, the device can automatically recognize the physical condition of the user, the blood pressure is measured in a targeted measurement mode according to the physical condition of the user, and accurate measurement of the blood pressure is achieved.

The invention provides a blood pressure measuring device. The blood pressure measuring apparatus includes a main body and a balloon. Wherein the air bag is provided with an air cavity and is fixed at one end part of the main body. The main body is provided with a cavity defined by a plurality of side walls, and an air supply and exhaust device and a first air pressure sensor can be arranged in the cavity of the main body but not limited to the cavity. The air supply and exhaust device comprises an air inlet path and an air outlet path, and the air supply and exhaust device communicates with the air cavity of the air bag through the first air path. The first air pressure sensor comprises a first air hole and a second air hole, and a pressure film is arranged between the first air hole and the second air hole. In addition, a first air hole is formed in the side wall of the main body, the first air hole can be communicated with the air cavity of the air bag through a second air path, and the second air hole can be communicated with the first air hole through a third air path. The air pressures on the two sides of the pressure film of the first air pressure sensor are the air pressure in the air bag and the external atmospheric pressure respectively and are not affected by the air pressure in the cavity, so that the blood pressure measurement precision of the blood pressure measurement equipment is high.

The invention discloses a blood pressure measurement atrial fibrillation detection method and device based on dynamic deflation and a medium. The method comprises the steps that in the pressure reduction process of blood pressure measurement, a pulse sequence corresponding to target pressure is obtained, when the maximum amplitude appears, if the number of current amplitude sequences is smaller than a preset threshold value, the deflation speed is adjusted, the pulse sequence continues to be detected according to the new deflation speed, and after the amplitude sequences with the enough number are obtained, atrial fibrillation judgment is conducted; the device comprises a main control unit, a display unit, a pressurization part, a decompression part, a pressure pulse detection unit and an atrial fibrillation judgment unit. According to the scheme, enough amplitude sequence data can be obtained in the decompression process of single-time blood pressure measurement to judge whether atrial fibrillation exists or not, and the use experience of related applicable people is greatly improved.

The invention provides a blood pressure detection and classification system and method based on a neural network, a medium and a terminal. Mel-frequency cepstral coefficient feature extraction, first heart sound time domain feature extraction and second heart sound time domain feature extraction are performed on acquired heart sound signal real-time data; the extracted Mel frequency cepstral coefficient feature data, the first heart sound time domain feature data and the second heart sound time domain feature data are used as model features to be input, time domain features and frequency domain features are included, and comprehensive coverage of time domain information and frequency domain information is achieved. The multi-input time domain convolutional neural network model is used for processing the three feature inputs and fusing the three feature inputs, the current blood pressure state of the user can be accurately detected, convenience and rapidness are achieved, and the result is accurate. The algorithm for extracting the frame where the heart sound peak point is located based on the MFCC0 is achieved, the influence of noise can be effectively avoided, the algorithm is simpler and more accurate, meanwhile, higher fault tolerance is achieved, and the first heart sound and the second heart sound can be accurately distinguished.

A system and method for authenticating identity during a financial transaction based, in part, on dynamic biometric factors such as body temperature, heart rhythm, blood pressure, blood sugar, vein pattern, skin pore pattern, and voice recognition. The biometric values are captured, aggregated, and patterned over time to create a unique biometric profile. When a transaction is initiated, current biometric values are captured and compared to the biometric patterns, and a biometric authentication determination is made based on the results. An overall identity authentication score is generated based on a combination of the biometric authentication determination and other identity authentication determinations such as a purchase pattern authentication determination or a location authentication determination. An identity authentication determination is made based on the overall identity authentication score and communicated to the merchant. Further, the transaction may be rejected when the overall identity authentication score violates a pre-established fraud threshold value.

The invention provides a blood pressure measurement model training method and a pulse blood pressure measurement system, a pulse wave measurement module obtains a pulse wave signal, and pulse waves of the wrist of a user act on pressure of a pressurization module to obtain a pressure change signal; the signal denoising module is used for denoising the pulse wave signals and the pressure change signals and transmitting the signals to the blood pressure measurement module, and the blood pressure measurement module executes a blood pressure measurement model training method; an initial neural network comprising a time sequence prediction network, a feature extraction network and a decoding network is trained through a pulse wave signal data set and a pressure change signal data set, the time sequence prediction network and the feature extraction network output personal blood vessel features and high-dimensional pulse features respectively, and a blood pressure data prediction result is output through the decoding network. And minimizing the deviation between a blood pressure data prediction result and an actual result, performing parameter iteration updating on the initial neural network model to obtain a blood pressure measurement model, and obtaining blood pressure data through the blood pressure measurement model to realize continuous measurement of blood pressure.

The invention relates to the technical field of machine learning, in particular to a nursing physical examination data intelligent analysis and management method which comprises the following steps: extracting body temperature, blood pressure and heart rate from a physical examination data set, performing Gaussian kernel mapping processing, and mapping physical examination data into a high-dimensional feature space to obtain high-dimensional feature data; and training a support vector machine model by using the high-dimensional feature data. Through the Gaussian kernel mapping of the high-dimensional feature space and the application of the support vector machine model, the processing capability of the nursing physical examination data is improved, and abnormal and normal data points can be distinguished. And the nonlinear representation of the data is enhanced through mapping, so that the model can process a complex mode more effectively, and outlier and error data are effectively removed. Real-time classification ensures fast processing of data streams, allowing instant updates and responses. And by dynamically marking the severity of the data points and adjusting the processing strategy, the flexibility and individuation of data management are further enhanced.

The invention discloses a steady-state leakage and forward flow testing device for a heart valve, and relates to the technical field of medical instrument inspection. The device comprises a reservoir, a pipeline, and a driving device, a regulating valve, a front-end flow meter, a front-end valve mounting channel and a rear-end valve mounting channel which are sequentially mounted on the pipeline, and the two ends of the pipeline are communicated with the reservoir. The heating and temperature control system ensures that the liquid temperature meets the requirement of a new edition standard, the valve installation channel with the inner diameter of 70 mm is suitable for a large-size mitral valve, and differential pressure sensor interfaces are arranged in front of and behind the valve ring of the artificial heart valve, so that the requirement of the new standard for the position of a sensor is met; according to the device, flexible selection of pressure values under different blood pressure states is achieved by adjusting the rotating speed of a driving device (a magnetic pump), accurate measurement and automation of the leakage amount are achieved through a high-precision flow meter, and the whole design aims at improving the accuracy and repeatability of testing and ensuring the quality and safety of an artificial heart valve.

The invention provides a blood pressure detection method and device based on a frequency modulated continuous wave radar and electronic equipment, and can be applied to the technical field of signal processing. The method comprises the steps that a radar echo signal is acquired, and the radar echo signal is acquired at a preset height position away from a neck-chest area of a target object; performing beam focusing processing and phase demodulation processing on the radar echo signal to obtain pulse wave signals at different positions and angles in the neck-chest area; pulse wave time features and pulse wave clustering features of the pulse wave signals are extracted, the pulse wave time features represent phase information of pulse waves collected at different positions in the neck-chest area, and the pulse wave clustering features represent the similarity between the pulse waves collected at different angles in the neck-chest area; inputting the pulse wave time features and the pulse wave clustering features into a blood pressure detection network, and outputting a blood pressure detection result of the target object.

The invention provides a wearable equipment wearing detection method and wearable equipment, the wearable equipment comprises a main body, a wrist strap and a blood pressure detection assembly, the blood pressure detection assembly comprises an air bag and an air pump, and the method comprises the steps that when it is detected that preset conditions are met, the air bag is inflated with gas; detecting the volume expansion rate of the airbag; determining a wearing detection result of the wearable device according to the volume expansion rate; and displaying a first interface, wherein the first interface comprises the wearing detection result. In the embodiment of the invention, the wearable equipment can judge whether the wearable equipment is normally worn by detecting the volume expansion rate of the air bag, so that the accuracy of a physiological parameter measurement result is ensured, hardware does not need to be added, and extra cost is not increased.

The invention provides a blood pressure measuring method, wearable equipment and a storage medium. The method is applied to the wearable equipment, the wearable equipment comprises a blood pressure measuring device, and the blood pressure measuring device comprises an air bag. In the first time period, the wearable device inflates the air bag and obtains a first pulse wave signal, the air pressure in the air bag is gradually increased along with time in the first time period, and the first pulse wave signal is used for obtaining a first blood pressure measurement value; in a second time period, the wearable device inflates the air bag and obtains a second pulse wave signal, the air pressure in the air bag is kept unchanged or fluctuates in the first range in the second time period, and the second pulse wave signal is used for evaluating the cardiovascular risk; the wearable device outputs a first blood pressure measurement and cardiovascular risk. By means of the method, the wearable device can monitor the cardiovascular disease risk of the user while obtaining the peripheral arterial blood pressure value, and cardiovascular diseases are prevented.