78 results about "High heart rate" patented technology

The invention discloses a sleep monitoring analysis method and system based on HRV, and relates to the technical field of sleep monitoring, and the method comprises the following steps: at the beginning of monitoring, continuously recording a continuous heartbeat time interval of a sleeper at a preset initial heartbeat interval acquisition frequency for evaluating the autonomic nervous system state of the sleeper at night; the respiration data of the sleeper is acquired in real time while the heart rate data is acquired. By combining real-time respiration data and an intelligent increment control algorithm, when irregular respiration is detected, the heartbeat interval acquisition frequency is dynamically adjusted, so that the sampling precision of heart rate change is improved, fine fluctuation of a sleeper when apnea or irregular respiration occurs can be captured, and the sleep quality of the sleeper can be improved. In addition, the detection accuracy of the apnea event can be improved under high sensitivity, potential health risks can be recognized in time, more reliable data support is provided for improvement of sleep quality and early intervention, and therefore health damage caused by missing detection is effectively avoided.

The invention relates to the technical field of heart rate detection, in particular to a wearable underwear heart rate detection method and system.The method comprises the following steps that motion information of a user is obtained, and specific body posture changes are recognized based on the motion information of the user; generating a physiological artifact signal related to the specific body posture change based on the specific body posture change; removing a physiological artifact signal from the original physiological signal to obtain a purified physiological signal; heart rate abnormity judgment is conducted on the purified physiological signals. According to the scheme, the physiological artifact signals can be effectively removed, and the accuracy of heart rate detection is improved.

The present invention relates to computer vision technology and RPG heart rate detection technology, and specifically to a heart rate detection method based on CardiA2Net. The present invention utilizes CardiA2Net to combine a self-attention convolutional hybrid network (ACmix) with an attention-based long short-term memory (ALSTM) network to perform enhanced feature extraction from raw data and improve time series learning with an integrated attention mechanism. The present invention also proposes a comprehensive set of preprocessing methods for facial video datasets, effectively reducing noise interference in facial videos and improving the accuracy of heart rate detection. The present invention calculates heart rate through facial video analysis and simultaneously processes noise in the video, effectively reducing the difficulty of contactless heart rate detection and improving the accuracy of contactless heart rate detection.

The invention provides a heart rate and breath prediction method, a program product, electronic equipment and a storage medium. The method comprises the following steps: acquiring an original signal sequence acquired from a human body through an ultra-wideband radar; determining a thoracic cavity displacement signal according to a mapping relation between the phase change and thoracic cavity displacement; performing multi-domain feature extraction on the thoracic cavity displacement signal to obtain multi-domain features; the multi-domain features comprise time domain features, frequency domain features and time-frequency domain features; on the basis of the multi-domain features, prediction values are obtained through a pre-trained prediction model, and the prediction values comprise the heart rate and the respiratory rate in the future time period. The robustness of the algorithm is enhanced through multi-dimensional feature fusion, high precision is still kept in an electromagnetic interference or multi-target scene, and the reliability of heart rate and respiratory rate prediction in a complex environment is improved. The physical signal advantage of the ultra-wideband radar is complementary with the environmental adaptability of the neural network, and the prediction accuracy of the heart rate and respiratory rate is improved.

The invention provides a vital sign detection method and device based on a millimeter wave radar, electronic equipment and a storage medium. The method comprises the following steps: obtaining a distance frequency domain signal based on a radar echo signal; performing spectral analysis on the distance frequency domain signal, positioning the position of the to-be-detected object, and extracting phase information at the position; filtering through a band-pass filter to obtain a breathing frequency band interval signal and an initial heartbeat frequency band interval signal; performing real-time respiration rate estimation based on the respiration frequency band interval signal to obtain a respiration frequency, and eliminating respiration harmonics in the initial heartbeat frequency band interval signal by using an adaptive wave trap based on the respiration frequency to obtain a heartbeat frequency band interval signal; and with the minimum fuzzy entropy as an optimization target, decomposing the heartbeat frequency band interval signal by using a variational mode decomposition algorithm to obtain a heartbeat signal, and carrying out real-time heart rate estimation based on the heartbeat signal to obtain a real-time heart rate. According to the method, the device, the electronic equipment and the storage medium provided by the invention, the accuracy of heart rate measurement can be improved.

The invention discloses an ultra-high heart rate electrocardio acquisition system, which comprises a signal acquisition unit adopting an ADS131E08 chip and supporting 8 channels, a 24-bit delta-sigma ADC (Analog to Digital Converter) and programmable gain amplification; the dynamic sampling rate adjusting unit is used for dynamically adjusting the sampling rate between 1kSPS and 64kSPS according to the heart rate change, and the sampling rate is increased to be greater than or equal to 2kSPS when the heart rate exceeds 200 times per minute; a low-noise design circuit has a common-mode rejection ratio greater than or equal to 110dB, a dynamic range greater than or equal to 118dB and total harmonic distortion less than or equal to-90dB, and power frequency interference is suppressed; the morphological enhancement module is used for enhancing QRS wave group characteristics by using digital morphological filtering; the multi-lead fusion module is used for fusing multi-lead signals through time sequence alignment and R-wave phase difference analysis; and the anti-interference module is integrated with a hardware comparator, and is used for lead falling detection and dynamic digital notch filtering. The system is suitable for researches on myocardial ischemia, arrhythmia and drug cardiotoxicity. Compared with the prior art, the device has the advantages of being simple in structure, low in cost, high in precision, high in reliability and the like, and can effectively solve the problem of animal ultrahigh heart rate electrocardio collection.

The invention discloses a safety condition monitoring method and device for old people, and relates to the technical field of heart rate monitoring. Acquiring a face video and an infrared video of a target user to obtain a first final space-time diagram and a second final space-time diagram; respectively inputting the first final space-time diagram and the second final space-time diagram into a space-time feature extraction module for feature extraction to obtain RGB features and NIR features, and fusing the RGB features and the NIR features to obtain fused features; the heart rate of the target user is determined according to the fusion features, and state monitoring is conducted. Acquiring a face and an infrared video of a target user, and extracting spatio-temporal features of the face video according to a preset rule to obtain a first spatio-temporal diagram; the infrared video features are extracted and amplified frame by frame to obtain a second space-time diagram, RGB and NIR features are extracted through a space-time feature extraction module and fused into fused features, non-contact heart rate monitoring is achieved, the accuracy and efficiency of heart rate monitoring are improved, the heart rate is determined according to the fused features, and the health condition of a user is monitored and evaluated in real time.

The invention provides a multi-lead heart rate monitoring method and wearable device.The multi-lead wearable device collects signals and conducts band-pass filtering, then signal quality judgment is conducted on electrocardiosignals of each lead, segments meeting the signal quality are effective signal segments, and segments not meeting the signal quality are interference signal segments; selecting the effective signal sections in each lead, and combining the effective signal sections into a continuous standard electrocardiosignal by taking time as length; and finally, performing QRS wave group detection on the standard electrocardiosignal, and obtaining a heart rate value of the standard electrocardiosignal. According to the method, the heart rate monitoring accuracy and the calculation efficiency can be effectively improved, and the high-real-time electrocardiogram monitoring requirements of all scenes are met.

The utility model discloses an in-aorta balloon and an IAB catheter. The in-aorta balloon comprises a balloon body and a catheter which is located outside the balloon body and connected with the front end of the balloon body. A balloon catheter with the hardness larger than that of the balloon body is arranged in the balloon body. The balloon catheter extends from the front end of the balloon body to the tail end of the balloon body by a preset length; the tail end of the balloon catheter is closed and a plurality of through holes are formed in the surface of the balloon catheter; the inner cavity of the catheter is communicated with the inner cavity of the balloon catheter or the inner cavity of the catheter, the inner cavity of the balloon catheter and the inner cavity of the balloon body are communicated at the same time, and when the front end of the balloon body is sucked to be shrunken, the tail end of the balloon body is sucked to be shrunken through the through holes in the surface of the balloon catheter at the same time. The balloon catheter is arranged, so that rapid deflation of the balloon is achieved, the negative pressure requirements of the rear end driving device and the negative pressure tank are reduced, meanwhile, deflation of the balloon can be accelerated, and the rapid response capacity when the heart rate is high or the heart rate is not stable is facilitated.

The present application relates to a PPG sensor module, electronic device, wearable device and physiological information detection method. The PPG sensor module includes: at least three light-emitting components for emitting light signals; a light detection module for generating multiple detection signals based on the light signals emitted by each light-emitting component; each light sensor and at least two light-emitting components respectively form a first measurement channel, and the light sensor also forms a second measurement channel with at least one light-emitting component other than the first measurement channel; the length of the first measurement channel is less than the length of the second measurement channel; a controller for obtaining each detection signal and determining the heart rate information of the detection object based on the detection signal obtained from each first measurement channel, and the controller is also used to determine blood oxygen information based on the detection signal obtained from each first measurement channel and the detection signal generated based on each second measurement channel. The PPG module can simultaneously improve the accuracy of heart rate and blood oxygen detection.

The invention relates to a driver heart rate monitoring method, a driving risk early warning method, a medium, a controller and a vehicle. The method comprises the steps that a face video of a vehicle driver is collected; based on the face video, determining a face region of interest for heart rate calculation; and processing the facial region of interest through a deep learning network to obtain a heart rate value of the driver. By collecting the face video of the driver and applying the face video to follow-up determination of the heart rate value, compared with the heart rate value measured through hardware equipment connected with the driver in the related technology, direct contact with the driver can be avoided, and then the driving process of the driver can be prevented from being limited. And the face region of interest is processed through the deep learning network to obtain the heart rate value of the driver, so that the accuracy of the heart rate value can be improved.

The invention discloses a non-contact intelligent health monitoring method and equipment based on a physiological signal, and relates to the technical field of non-contact health monitoring, and the non-contact intelligent health monitoring method based on the physiological signal mainly comprises the steps: carrying out the division according to a face video image, and obtaining a region of interest; obtaining an aligned region of interest by utilizing a facial feature point tracking and alignment technology, and fusing and inputting an improved rPPG technology into the region to obtain an actual heart rate value; according to the original audio signal, performing framing and discrete Fourier transform by using a Hamming window to obtain a spectrogram of each audio clip; mel feature extraction is carried out by using a librosa library to obtain MFCC features, and the three features are fused to obtain a predicted emotion type of the voice. By means of the non-contact intelligent health monitoring method and device based on the physiological signals, the robustness and precision of heart rate monitoring can be improved, the accuracy and robustness of emotion recognition are improved, and combined monitoring of the emotion and the heart rate is achieved.

The invention discloses a heart rate measurement method and system based on time-frequency fusion and dynamic gating attention, and the method comprises the steps: firstly carrying out the preprocessing of an acquired face video sequence, and obtaining a stable input image sequence; thirdly, extracting a three-dimensional feature map and time sequence features which change along with time through a time-frequency convolutional network; a time-frequency fusion module is constructed, complementary time-frequency features are obtained through time-domain convolution and frequency-domain wavelet decomposition, and feature adaptive fusion is realized by using a dynamic gating mechanism; and the local time relevance of the features is enhanced through a local sliding window attention module. And inputting the three-dimensional convolution features into a prediction module, performing regression to generate a remote photoelectric volume pulse wave signal, and performing frequency domain analysis on the signal to estimate the heart rate. According to the method, pulse related signals can be stably extracted under the conditions of illumination variation and slight head movement, and the method has high heart rate estimation precision and environment robustness and can be used for non-contact vital sign monitoring application.

The present invention relates to the technical field of information processing, and in particular to a heart rate and respiration monitoring method based on a millimeter-wave radar. The method includes determining whether the driver is speaking; acquiring a first reflected wave signal; analyzing the first reflected wave signal; determining whether monitoring is abnormal; determining a second heart rate and a second respiration rate; determining whether the driver is abnormal; and correcting a standard distance range. By combining head image recognition and mouth feature analysis, the present invention ensures that heart rate and respiration monitoring is only performed in a target stationary state, significantly improving the efficiency of heart rate and respiration monitoring. By dynamically adjusting the duration of the transmitted wave and the monitoring strategy according to the actual distance between the driver and the transmitter, it effectively adapts to changes in the target position, avoids monitoring errors, and improves the accuracy and effectiveness of monitoring. When a wrong judgment occurs, the standard distance range is automatically corrected according to the feedback, continuously optimizing the monitoring parameters, improving the monitoring accuracy, and providing a more reliable guarantee for driving safety.

The invention discloses a heart rate determination method and system based on a millimeter wave radar and a neural network, and relates to the technical field of heart rate detection.The heart rate determination method comprises the steps that original radar echo data and original electrocardiosignals are synchronously collected, a plurality of initial instantaneous heart rates are generated according to target electrocardiosignals determined by the original electrocardiosignals through an initial sliding window, and the initial instantaneous heart rates are obtained; performing data rejection according to the high-frequency body movement time, outputting target radar echo data and target instantaneous heart rates, and constructing an initial radar complex data matrix corresponding to each target instantaneous heart rate based on the target radar echo data through an initial sliding window; and performing data equalization according to the initial radar complex data matrix to which the plurality of preset heart rate intervals belong, determining a training radar complex data matrix and a real instantaneous heart rate, determining a trained heart rate prediction network based on the training radar complex data matrix and the real instantaneous heart rate, and predicting the actually measured instantaneous heart rate of the actually measured radar echo data. The scheme is beneficial to improving the heart rate determination accuracy.

The invention provides a sequential balloon pulsation blood pump, system and method for an artificial uterus, and relates to the technical field of medical instruments. The blood pump comprises a pump body which is arranged in a blood flowing loop of an artificial placenta and comprises a first pump cavity and a second pump cavity; the first pump cavity and the second pump cavity are connected in parallel through a catheter, the two ends of the catheter are a blood inlet end and a blood outlet end respectively, the inlet end is communicated with the umbilical artery of a fetus, and the outlet end is communicated with the umbilical vein of the fetus through an oxygenator; the controller is in communication connection with the first air bag assembly and the second air bag assembly; and the heart acquisition unit is arranged on the outer surface of the artificial uterus and is in communication connection with the controller. The device has the advantages that pulsatile blood flow can be generated, the device can adapt to high heart rate of a fetus, the afterload balance of the heart of the fetus is not affected, and umbilical vessel intubation spasm is avoided.

The utility model discloses a heart rate band which comprises an electrode slice unit, a control unit, a binding unit and a conduction unit. The control unit is used for collecting electric signals of the electrode plate unit; the binding unit is used for bearing the electrode plate unit and pressing the electrode plate unit on a human body; the conduction unit comprises a first clamping part, a second clamping part and a sealing part, the first clamping part and the second clamping part are clamped, the first clamping part is electrically connected with the electrode plate unit, the second clamping part is electrically connected with the control unit, the sealing part is arranged outside the first clamping part and the second clamping part in a sleeving mode, and the sealing part is electrically connected with the first clamping part and the second clamping part. The sealing part is used for preventing water between the binding unit and the first clamping part and between the binding unit and the second clamping part. The utility model provides a heart rate band which can reduce the influence of sweat on the heart rate detection accuracy of the heart rate band and improve the heart rate detection accuracy.

A system for testing medications for cardiac activity at elevated heart rates utilizes an array of electrodes connected to a computer and cardiomyocyte samples on the electrodes. Software implements an electrical stimulation protocol in a method of delivering an electrical signal at a baseline frequency to stimulate respective cardiomyocyte samples and calculating a functional refractory period (mISI) for the respective cardiomyocytes at the baseline frequency along with increased respectively applied frequencies of consecutive electrical signals.

The application provides a heart rate detection module and an electronic device; wherein the heart rate detection module comprises a light emitting element, a light receiving element and a Fresnel film; the light emitting element and the light receiving element are arranged in optical isolation, the Fresnel film is located on the same side of the light emitting element and the light receiving element, and the light emitting surface of the light emitting element faces the Fresnel film; the Fresnel film has a light absorbing medium therein, and the light absorbing medium is located between the light emitting element and the light receiving element in the direction perpendicular to the Fresnel film. According to the heart rate detection module and the electronic device provided by the application, the crosstalk phenomenon of the detection light emitted by the light emitting element in the Fresnel film can be reduced / attenuated, that is, the light leakage in the Fresnel film can be effectively inhibited to weaken the light noise of the heart rate measurement, and the signal-to-noise ratio of the heart rate detection module can be improved.

A heart rate detection method based on joint attention and multi-scale fusion constructs a multi-scale image sequence to ensure the integrity of the scale, then extracts signal features from multiple scales, performs multi-scale feature fusion through an inter-layer attention mechanism, and finally sends the fused features into the rPPG signal extraction network. The designed rPPG signal extraction network consists of channel-time joint attention (CTJA) and spatio-temporal joint attention (STJA) to extract signals in terms of time, space, and channels. The present invention can effectively improve the accuracy of heart rate detection.

The invention relates to the technical field of physiological signal processing, in particular to a device and method for monitoring vital signs during sleep, and the device comprises a signal collection module which is used for collecting physiological signals of a user in a non-contact manner and sending the collected physiological signals Sraw (t) to a noise filtering module; the noise filtering module is used for de-noising the physiological signal Sraw (t) and outputting a de-noised signal Scanan (t); the signal enhancement module is used for carrying out time sequence feature extraction and signal enhancement on the de-noised signal Scanan (t) so as to improve the stability and detectability of the heart rate signal, and outputting an enhanced signal Senhanced (t); the signal classification module is used for classifying the enhanced signal Senhanced (t) and outputting heart rate HR (t), respiratory rate RR (t) and body movement information M (t); the data analysis module is used for extracting characteristic parameters from the output data of the signal classification module, identifying abnormal events and outputting an analysis result; and the display and alarm module is used for displaying the analysis result in real time and giving an alarm when an abnormal condition is detected.

The present application relates to the technical field of heart rate detection, and particularly relates to a wearable underwear heart rate detection method and system, the method comprising the following steps: acquiring motion information of a user, identifying a specific body posture change based on the motion information of the user; generating a physiological artifact signal related to the specific body posture change based on the specific body posture change; removing the physiological artifact signal from an original physiological signal to obtain a purified physiological signal; and performing heart rate anomaly judgment on the purified physiological signal. Through the above scheme, the physiological artifact signal can be effectively removed, and the accuracy of heart rate detection is improved.

The present application relates to the technical field of wearable devices, in particular to a method for calibrating earphone heart rate error based on a sports knowledge graph and related devices. The method comprises the following steps: obtaining multi-modal physiological data of a user wearing an earphone during sports, the multi-modal physiological data including photoplethysmographic wave signals collected by an optical heart rate sensor and the like. The present application structures the complex mapping relationship between different sports state types, sports intensity levels and heart rate error characteristics by constructing a sports knowledge graph, thereby achieving explicit modeling of the correlation between sports artifacts and heart rate signals. Compared with traditional heart rate calibration methods based on statistical filtering or a single deep learning model, the present application uses the topological structure information of the knowledge graph to better capture the deep semantic correlation between sports states and heart rate errors, thereby achieving higher heart rate monitoring accuracy in various sports scenarios.

A computer game as presented from spectator side may use clusters of marginally high heart rate to infer something interesting occurring on platform, which may be used in turn for video bookmarking highlights, other uses on the platform.

The invention discloses an ultrahigh heart rate anomaly detection method based on real-time signal processing, and relates to the technical field of pet health monitoring. According to the ultrahigh heart rate anomaly detection method, local low-delay processing is achieved by fusing multi-modal physiological signals and utilizing edge calculation, signal preprocessing is conducted through band-pass filtering, self-adaptive Kalman filtering and the like, and the abnormal heart rate is obtained. Multi-time scale feature extraction is combined with pet state vectors to dynamically adjust feature weights, an improved attention mechanism neural network and support vector machine secondary classification and a posterior probability fusion algorithm are used to improve classification precision, and a dynamic threshold mechanism and a grading early warning mechanism are used to match response intensity according to abnormal duration, so that the classification accuracy is improved. According to the invention, accurate and real-time monitoring of the abnormal ultrahigh heart rate of the pet is realized, an efficient and reliable detection process is provided for health management of the pet, and the method has important significance for early detection of potential diseases of the pet.

An ergonomic heart rate tracking and bias detecting system and method is provided. The system is configured to determine if users exhibit biases by measuring their heartrates and / or recording audio via the smartwatch during simulated tests or real-world situations. The system is intended to help those supervisors of employees by requiring employees to wear the smartwatch and using the system track and record their behavior. The system is configured to transmit data from the smartwatch to the system application for analysis to measure the heartrate of users. A low or resting heartrate may denote a pass situation, where a high heartrate may denote a failure situation, meaning a potential bias is detected in the user. Audio recorded by the system is also analyzed for tone and language to further determine the presence of bias in the user. Supervisors may then decide whether to hire / fire / or retrain the user.

The application is suitable for the field of remote physiological parameter monitoring, and provides a heart rate determination method and device based on a region of interest and an electronic device, which comprises the following steps: acquiring a video stream comprising a face of a user to be measured; performing region of interest detection on the video stream by using at least two region of interest templates to obtain corresponding regions of interest; for each region of interest, determining a time sequence signal corresponding to the region of interest, performing blind source separation on the time sequence signal by using an independent component algorithm to obtain an independent component signal related to a heart rate, and calculating the heart rate according to the independent component signal to obtain a heart rate corresponding to the region of interest; determining a weight value of each region of interest; and determining a heart rate of the user to be measured according to the weight value and the heart rate corresponding to each region of interest. By using the above method, local abnormal disturbance can be inhibited, and the accuracy of the heart rate can be improved.

This application provides a method, program product, electronic device, and storage medium for predicting heart rate and respiratory rate. The method includes: acquiring the original signal sequence collected from the human body via ultra-wideband radar; determining the chest cavity displacement signal based on the mapping relationship between phase change and chest cavity displacement; extracting multi-domain features from the chest cavity displacement signal to obtain multi-domain features, including time-domain features, frequency-domain features, and time-frequency-domain features; and obtaining predicted values ​​based on the multi-domain features using a pre-trained prediction model, the predicted values ​​including heart rate and respiratory rate in the future time period. Multi-dimensional feature fusion enhances the robustness of the algorithm, maintaining high accuracy even under electromagnetic interference or multi-target scenarios, improving the reliability of heart rate and respiratory rate prediction in complex environments. The physical signal advantages of ultra-wideband radar complement the environmental adaptability of neural networks, improving the accuracy of heart rate and respiratory rate prediction.

The invention discloses a watch heart rate monitoring method and device based on TEC temperature control, and solves the problem of inaccurate heart rate monitoring caused by the fact that the influence of temperature on a photoelectric sensor is not considered when a smart watch photoelectric measurement method is used for measuring the heart rate in the prior art. Comprising the following steps: acquiring the surface temperature of LED lamp beads at the bottom of the watch or the ambient temperature in real time; according to the target temperature range and the current temperature value, the TEC working mode is adjusted based on a preset temperature control algorithm; continuously detecting the temperature of the LED lamp bead, and dynamically adjusting the working power of the TEC according to the temperature change trend; after the temperature of the watch is stabilized within the target temperature range, photoelectric signals are collected for heart rate monitoring. The light source temperature can be stabilized in the optimal working temperature interval, and the accuracy of heart rate measurement is improved.

The invention discloses a heart rate monitoring method, system and device based on millimeter wave radar and a storage medium. The method comprises the following steps: extracting a phase signal of a target monitoring object in a radar echo signal; performing second-order differential processing to obtain an acceleration signal segment set corresponding to the phase signal; positioning an acceleration signal segment most similar to the periodic heartbeat signal from the acceleration signal segment set; segmenting beat-by-beat heartbeat signals from the positioned acceleration signal segments, and calculating the heart rate according to the segmented beat-by-beat heartbeat signals. According to the method, the acceleration signal segment of the distance angle bin with the optimal heartbeat is positioned based on the periodicity of the heartbeat signals, and the beat-by-beat heartbeat signals are segmented based on the acceleration signal segment, so that the accurate heart rate value is calculated, the misjudgment problem of a spectrum peak value detection method under the coexistence of multiple persons and the interference of respiration harmonics and body movement is effectively solved, and the accuracy of the detection result is improved. And the heart rate calculation precision is improved.