79 results about "Target heart rate" patented technology

The invention relates to a non-contact multi-target heart rate variability (HRV) detection method based on adaptive variational mode decomposition (VMD). The method comprises the following steps: firstly, performing multi-target detection on human body targets in a detected scene by using a radar technology so as to determine an accurate distance window of each target; then, a signal phase is extracted from the distance window through a differential and cross multiplication algorithm, and then the thoracic cavity displacement signal of each person to be detected is obtained. According to the method, an improved GOA algorithm is adopted to optimize VMD parameters, a new adaptive function HIE (combining permutation entropy, mutual information amount and energy loss rate) is provided to serve as a target function of GOA, and complete self-adaptive VMD decomposition of chest displacement signals of each to-be-tested person is achieved. Through the decomposition, the heartbeat signals and the breathing signals are extracted respectively, so that the heart rate variation characteristic of each person to be detected can be accurately detected. The method provides a high-precision and non-contact HRV detection means, and is suitable for a multi-target scene.

The invention provides a heart rate continuous detection method and device, electronic equipment and a storage medium. According to the method, a cache queue is set for the latest M data points in a reference PPG signal, a reference heart rate value is determined according to the latest data points in the cache queue at set intervals, and an initial heart rate value is determined until it is detected that the reference heart rate value is relatively stable; further taking the initial heart rate value as a current heart rate value, determining candidate frequency values possibly corresponding to the updated target heart rate value according to the current heart rate value and a preset heart rate resolution after a second time interval, and fitting each candidate frequency value and data points stored in a current cache queue based on a preset fitting curve to obtain a target heart rate value; and determining the heart rate value corresponding to the candidate frequency value corresponding to the maximum fitting result as the target heart rate value, thereby reducing the frequency resolution under the condition of not influencing the time domain resolution so as to obtain a more accurate heart rate value.

The embodiment of the invention provides an object behavior analysis method and device, equipment and a storage medium, and belongs to the technical field of animal behavior analysis. The method comprises the following steps: acquiring depth video data, an original neuron calcium signal sequence and an original heart rate signal sequence of a target object; performing behavior prediction on the target object according to the depth video data to obtain an object behavior sequence; the object behavior sequence represents the behavior mode change of the target object. Preprocessing the object behavior sequence to obtain a target behavior sequence, preprocessing the original neuron calcium signal sequence to obtain a target neuron calcium signal sequence, and preprocessing the original heart rate signal sequence to obtain a target heart rate signal sequence. According to the target behavior sequence, the target neuron calcium signal sequence and the target heart rate signal sequence, behavior analysis is conducted on the target object, and behavior analysis information is obtained. The problem that behavior analysis is carried out only through information expressed by a single object spontaneous behavior, and the analysis result is inaccurate is solved.

The present application provides a heart rate detection method and electronic device, which relate to the field of communication technology. Through this solution, when it is detected that a user wearing a smart wearable device is performing a first exercise, a PPG signal is collected by a PPG sensor in the smart wearable device; based on the PPG signal and the first deep sequence neural network model, the first heart rate data is obtained; based on the PPG signal and the first frequency tracking algorithm model, the second heart rate data is obtained; based on the first heart rate data and the second heart rate data, data fusion is performed to obtain the user's target heart rate value during the first exercise. Since the frequency tracking algorithm can quickly track changes in heart rate, it can compensate for scenarios where the deep sequence neural network cannot track in time when the heart rate suddenly changes. Therefore, the present application solution can improve the accuracy of heart rate prediction by fusing heart rate data obtained by different models.

The embodiment of the invention discloses a blood glucose index evaluation method, electronic equipment and a storage medium, and the method comprises the steps: obtaining the corresponding heart rate data of a target user in an evaluation time period, carrying out the feature extraction processing of the heart rate data, obtaining the corresponding target heart rate feature of the target user in the evaluation time period, and obtaining the target heart rate feature of the target user in the evaluation time period; inputting the target heart rate feature and a target calibration parameter corresponding to the target user into a blood glucose evaluation model, and predicting blood glucose control index data corresponding to the target user in the evaluation time period through the blood glucose evaluation model. The target heart rate features and the target calibration parameters are used as input of a blood glucose evaluation model, and the blood glucose management and control index data of the target user in the evaluation time period are predicted through the blood glucose evaluation model, so that it is ensured that the obtained heart rate data corresponding to the target user in the evaluation time period are utilized; and the accuracy of the blood glucose management and control index data corresponding to the target user in the evaluation time period is determined, and meanwhile, the cost of blood glucose monitoring is greatly reduced.

The invention discloses a heart rehabilitation training monitoring and management system, relates to the technical field of intelligent medical treatment, and solves the problems that in the prior art, an evaluation mode excessively depends on artificial experience, the requirements of modern heart rehabilitation for data objectivity and timeliness are difficult to meet, and the scientificity and effectiveness of rehabilitation training are limited. By means of the data acquisition unit and the monitoring analysis unit, real-time monitoring and accurate analysis of the heart rate of the patient are achieved. Compared with a traditional heart rehabilitation evaluation mode, the system can automatically calculate the target heart rate interval and output an objective rehabilitation training evaluation result according to the difference between the real-time heart rate and the target heart rate. According to the automatic evaluation mode, the dependence on artificial experience is reduced, errors caused by subjective judgment are avoided, and the objectivity and timeliness of an evaluation result are ensured. Meanwhile, the system can help related personnel to dynamically adjust the training intensity according to real-time data, and the safety and effectiveness of rehabilitation training are further improved.

The invention provides an intelligent multi-modal control rehabilitation method based on heart multi-dimensional indexes. The method comprises the steps that personal basic information and medical record information of a patient are acquired; based on the personal basic information of the patient and the medical record information, calculating a patient targeted heart rate index; generating a rehabilitation training scheme suitable for the patient based on the targeted heart rate index of the patient; according to the rehabilitation training scheme suitable for the patient, rehabilitation training equipment is started for rehabilitation training, and heart multi-dimensional indexes of the patient are monitored; according to the rehabilitation training scheme and the heart multi-dimensional indexes of the patient, the power of rehabilitation training equipment is adjusted. According to the method, the patient can conduct rehabilitation training under the appropriate exercise intensity, then the power of rehabilitation training equipment is adjusted by monitoring the multi-dimensional indexes of the heart of the patient in the subsequent rehabilitation training process, the examination items of the heart indexes can be reduced, and the rehabilitation training efficiency is improved; and the patient can perform rehabilitation training in a safer state.

The invention provides a cardiopulmonary function training method and device, a computer readable storage medium, a computer program product and terminal equipment. The cardiopulmonary function training method comprises the steps that a target motion mode is determined according to physiological information of a user and first motion information, and the target motion mode is matched with a corresponding target heart rate interval; acquiring second motion information, wherein the second motion information comprises physiological feature data of the user and acceleration data of equipment used by the user; determining a suggested stride frequency according to the second motion information, wherein the heart rate of the user under the suggested stride frequency is close to the target heart rate interval or is within the target heart rate interval. The invention provides a scheme for flexibly carrying out stride frequency training and improving the cardiopulmonary function training effect.

The invention discloses a sleep scene-oriented robust millimeter wave radar heart rate estimation method, which comprises the following steps of: acquiring data of a detected object through a radar, and processing pulses acquired by the radar to obtain a phase sequence; performing band-pass filtering on the phase sequence to obtain a heart rate signal; performing Fourier transform on the heart rate signal to obtain a heart rate spectrum; evaluating the confidence coefficient of the heart rate spectrum to obtain the confidence coefficient; and estimating the target heart rate based on the confidence coefficient. According to the method, original data are collected through a radar, distance dimension imaging, target phase extraction, spectrum confidence judgment and heart rate estimation are carried out, and different heart rate estimations are adopted according to different signal spectrum qualities. By means of the method, the signal at the target true value position can be effectively obtained, the influence of poor signal quality on the output result is avoided, and therefore the robust heart rate measurement result is obtained.

To monitor whether an exercise prescription presented from a doctor (e.g., prescription regarding exercise amount, exercise strength, and exercise frequency) are properly observed outside a hospital as well, and assist doing exercise.SOLUTION: A server 1 is designed to assist rehabilitation of patients, and comprises a patient information acquisition unit 51 and a patient information presentation unit 53. The patient information acquisition unit 51 acquires the first index (pedometer, etc.) value of an exercise amount and the second index (hear rate, etc.) value of an exercise amount regarding a prescribed exercise imposed on a patient for rehabilitation of a given disease. The patient information presentation unit 53 presents the target heart rate-pedometer achievement of the patient, including a combination of the acquired pedometer and heart rate (e.g., pedometer from walking at heart rate of 100 bpm or greater) as assistance information for assisting rehabilitation of the disease.SELECTED DRAWING: Figure 4

Disclosed are example embodiments of an exercise system and methods for providing a personalized workout session. An example method for providing a personalized workout session includes collecting heart rate data of a user during a calibration workout session. The example method for providing a personalized workout session also includes determining a plurality of personalized heart rate zones for the user based on the collected heart rate data. Additionally, the example method for providing a personalized workout session includes providing, to an exercise equipment, a workout session having a plurality of workout segments, wherein each workout segment has a target heart rate zone that is associated with one of the plurality of personalized heart rate zones.

A fatigue measurement method includes obtaining a face video of a target object, processing the facial video to obtain a plurality of quasi-heart rates and a plurality of quasi-vibration frequencies, selecting a target heart rate from the plurality of quasi-heart rates and a target vibration frequency from the plurality of quasi-vibration frequencies, detecting the target heart rate and the target vibration frequency, and determining, according to the detection result, that the target object is in a fatigue state. The quasi-heart is obtained through one or more of a region of interest (ROI) between eyebrows and an ROI of chin, and the quasi-vibration frequency obtained through one or more of an ROI of eyes and an ROI of mouth.

Embodiments of the present application provide a heart rate determination method and device, electronic equipment and storage medium. The method comprises: obtaining a heartbeat signal corresponding to a heart impact signal of a target to be measured; processing the heartbeat signal to obtain a heartbeat difference signal corresponding to the heartbeat signal and a target probability density curve; determining a plurality of consecutive target heartbeats in the heartbeat signal based on the heartbeat difference signal, the similarity between any two target heartbeats in the plurality of target heartbeats being greater than a preset similarity threshold; determining a plurality of predicted heart rates according to the target probability density curve, the plurality of target heartbeats and the sampling rate of the heart impact signal; and determining a target heart rate of the target to be measured based on the plurality of predicted heart rates. Based on the method, errors in heart rate calculation caused by interference signals in the heart impact signal can be avoided, and the accuracy of heart rate determination is improved.

The invention discloses an AI accompanying toy and method based on an emotional acoustic wave algorithm, and relates to the technical field of man-machine interaction, a core processing layer establishes an independent virtual heart rate system for each AI role, and generates a personalized basic heart rate and an emotional intimacy initial value according to role attributes; dialogue content and AI emotional state are analyzed in real time based on data acquired by the input layer, and emotion type and intensity are identified; calculating a target heart rate and a spectrum modulation parameter according to the emotional state; dynamically adjusting parameters according to the interaction time, the dialogue depth and the emotion intimacy; the heart rate rhythm and spectrum modulation are applied to AI voice in real time; and the output layer presents the fused information of the emotional sound wave and the emotional state in a graph or color mode. Therefore, personification and life feeling of the AI role are greatly enhanced, man-machine interaction is upgraded from simple information exchange to accompanying experience with emotional depth and physiological resonance, and interaction naturalness and emotional attachment of the user are remarkably improved.

The present application relates to a kind of non-contact multi-target heart rate variability (HRV) detection method based on adaptive variational mode decomposition (VMD).The method first uses radar technology to detect the human target in the measured scene to determine the accurate distance window of each target.Then, the signal phase is extracted from the distance window by the differential and cross-multiplication algorithm, and then the thoracic displacement signal of each person to be tested is obtained.The present application optimizes the VMD parameters using the improved GOA algorithm, proposes a new adaptive function HIE (combining permutation entropy, mutual information and energy loss rate) as the objective function of GOA, and realizes the complete adaptive VMD decomposition of the thoracic displacement signal of each person to be tested.Through this decomposition, the heartbeat signal and the breathing signal are extracted, so that the heart rate variability characteristics of each person to be tested can be accurately detected.The present method provides a high-precision, non-contact HRV detection method, which is suitable for multi-target scene.

The embodiments of the present application provide a data processing method, system, server and readable storage medium, and relate to the field of computer technology. The embodiments of the present application can collect the user's target heartbeat data during the display and / or playback of the target multimedia file, and adjust the association relationship between the target user identifier and the target multimedia file according to the target heart rate parameters determined based on the target heartbeat data. Furthermore, the embodiments of the present application can recommend corresponding content to the user based on the association relationship. Therefore, the embodiments of the present application can judge the user's preference for the target multimedia file based at least on the user's target heartbeat data, and can obtain the user's preferences without relying on the user's operation of the terminal device, thereby improving the accuracy of data recommendation.

The invention discloses a tactile feedback guiding method and system for heart rehabilitation, and relates to the technical field of medical rehabilitation, and the method comprises the steps: obtaining physiological monitoring data and motion state data of a heart rehabilitation patient; a current heart rate interval state is determined according to the physiological monitoring data, a current exercise metabolism equivalent value is determined according to the exercise state data, and the current heart rate interval state is divided based on a preset rehabilitation target heart rate range; generating a tactile feedback mode corresponding to the current heart rate interval state and the current exercise metabolism equivalent value; and executing a tactile feedback mode to realize rehabilitation guidance, and adjusting the tactile feedback mode according to the change trend of the physiological monitoring data. According to the invention, real-time tactile feedback adjustment based on the change trend of the physiological data is realized, accurate non-intrusive motion guidance is provided for heart rehabilitation patients, and the safety and effectiveness of rehabilitation training are improved.

A brain function improvement facilitating device includes: a storage; a display screen; a timer; a heart rate measurement unit; a target exercise intensity calculator; a setting unit; a first determiner that determines whether a heart rate of a user is greater than or equal to a target heart rate set by the setting unit; a duration time measurement controller that performs control to measure a duration time in which the heart rate of the user is greater than or equal to the target heart rate if the heart rate of the user is determined to be greater than or equal to the target heart rate; a second determiner that determines whether a total of the duration time measured within a predetermined time limit has reached the target time set by the setting unit; a storage controller that controls the storage to store information indicating that the duration time has reached the target time if it is determined that the total of the duration time has reached the target time; a display data generator that generates display data to be displayed on a display screen based on reaching the target time if it is determined that the duration time has reached the target time; and a display controller that controls the display screen to display at least one of the calculated target heart rate, actual related data and time, or the display data.

The invention discloses a melatonin secretion moment detection method, device and equipment, a medium and a program product, and relates to the technical field of physiological rhythm monitoring, and the melatonin secretion moment detection method comprises the steps of obtaining original heart rate data of a user at a first moment; performing first filtering processing based on a circadian rhythm period on the original heart rate data to obtain first heart rate data; determining second heart rate data according to the original heart rate data and the first heart rate data; performing second filtering processing on the second heart rate data based on an over-daily rhythm period to obtain third heart rate data; fusing the first heart rate data and the third heart rate data to obtain target heart rate data; according to the target heart rate data at the first moment and the target heart rate data at the at least one second moment, the melatonin secretion moment of the user is determined, and the detection accuracy of the melatonin secretion moment is improved.

A computer-implemented method is disclosed. The method includes determining a maximum target heart rate for a user using an electromechanical machine to perform a treatment plan, wherein the electromechanical machine is configured to be manipulated by the user while the user is performing the treatment plan. The method includes receiving, via an interface, an input pertaining to a perceived exertion level of the user, wherein the interface comprises a display configured to present information pertaining to the treatment plan. Based on the perceived exertion level and the maximum target heart rate, the method includes determining an amount of resistance for the electromechanical machine to provide via one or more pedals physically or communicatively coupled to the electromechanical machine. While the user performs the treatment plan, the method includes causing the electromechanical machine to provide the amount of resistance.

The application provides a monitoring system, a monitoring device and an atrial fibrillation presentation method. The atrial fibrillation comprehensive view is displayed by obtaining the heart rate analysis result and the atrial fibrillation analysis result according to the heart rate analysis result and the atrial fibrillation analysis result. The atrial fibrillation comprehensive view includes the heart rate information and the target heart rate identifier in the preset atrial fibrillation monitoring period, and the atrial fibrillation information in the preset atrial fibrillation monitoring period. The atrial fibrillation information includes at least one of the atrial fibrillation load, the atrial fibrillation occurrence frequency and the atrial fibrillation duration. The target heart rate identifier is used for identifying the preset target heart rate. Through the joint presentation of the atrial fibrillation and the heart rate, the quantitative analysis result of the atrial fibrillation event and the heart rate can be comprehensively and intuitively presented to the medical staff in a graphical manner, which helps the medical staff to understand the achievement of the heart rate control target of the atrial fibrillation patient and improves the atrial fibrillation management efficiency.

The present application provides a data acquisition method and an electronic device. The method includes: obtaining first heart rate information of a target user corresponding to a first scenario within a recent first time period, where the first heart rate information is collected when the signal quality of a photoplethysmogram (PPG) signal meets a first condition, and the first heart rate information includes a step frequency value and a heart rate value; constructing a first heart rate map corresponding to the target user in the first scenario according to the first heart rate information; receiving a target step frequency value of the target user in the first scenario, where the target step frequency value is collected when the signal quality of the PPG signal does not meet the first condition; and determining a target heart rate value corresponding to the target step frequency value according to the first heart rate map. In this way, by generating a heart rate map using the user's historical heart rate information and determining the heart rate value when the PPG signal quality is poor according to the heart rate map, the abnormal value output of heart rate monitoring can be reduced, thereby improving the reliability of heart rate monitoring and enhancing the user experience.

The invention relates to the technical field of biomedical engineering. The invention discloses a physiological parameter detection method and device based on RGB-NIR combination, a terminal and a storage medium. The accuracy of physiological parameter detection can be improved. The physiological parameter detection method based on RGB-NIR combination comprises the following steps: acquiring a target RGB signal and a first target NIR signal corresponding to the face of a target object; performing correction processing on the first target NIR signal by adopting a first preset algorithm to obtain a second target NIR signal; performing fusion processing on the target RGB signal and the second target NIR signal to obtain a fusion signal; heart rate feature extraction processing is conducted on the fusion signal, and the target heart rate of the target object is obtained.

The present invention discloses a spinning bike with a motion feedback intervention system, which belongs to the field of bio-information feedback intervention for virtual reality depression disorders. The spinning bike collects the user's heart rate variability and electroencephalogram through a heart rate belt detection module and an electroencephalogram detection module, and the photoelectric speed measurement module monitors the rotation of the driving wheel in real time to obtain a speed pulse signal. The single-chip computer module obtains the target speed by combining the real-time heart rate variability, the real-time electroencephalogram with the target heart rate variability and the target electroencephalogram through a PID neural network decoupling control algorithm based on sparrow search, and reduces the system error through a nonlinear fault-tolerant control law based on an adaptive neural network to ensure the stable operation of the system, and finally transmits the real-time speed value and the target speed value to the VR glasses worn by the user in real time, and the user can adjust the speed of the spinning bike in time according to the target speed value and the real-time speed value, control the exercise intensity, enhance the user's emotional regulation ability, and improve the emotional regulation effect.

The invention discloses a method for calculating a target heart rate of exercise, which comprises the following steps of: 1, obtaining the consensus of the relation among age, resting heart rate and target heart rate in the biomedical field and the sports science field at present by looking up academic literatures; 2, designing a research scheme, and determining a method and a tool for collecting data; 3, collecting data on site to obtain 324 samples; 4, through statistical analysis, carrying out multivariate stepwise regression analysis by taking the heart rate after exercise as a dependent variable and taking age and resting heart rate as independent variables, so as to obtain a double-drop target heart rate model; 5, establishing and calculating target heart rate matrix data, determining the age range to be 20-70 years old, determining the resting heart rate range to be 55-95 times per minute, and calculating the matrix data of the target heart rate lower limit value; the problem of correctly calculating the bull's-eye rate according with the medical physiology principle is solved.

The invention relates to the technical field of fitness equipment, in particular to a stair machine control method based on heart rate control and a stair machine. The specific control method of the heart rate mode comprises the following steps: starting heart rate mode training at an initial gear: acquiring a heart rate time curve of a user, comparing the heart rate time curve with a target heart rate, and if a heart rate value within continuous specified time is lower than a first specified amplitude of the target heart rate, automatically adjusting the resistance of a resistance regulator to be increased by one gear from the current gear, if the heart rate value in the continuous specified time is higher than the second specified amplitude of the target heart rate, the resistance of a resistance regulator is automatically adjusted to be reduced by one gear from the current gear; and if an exit signal is received in the process, entering a standby mode. The resistance gear of the stair machine is automatically adjusted according to the real-time heart rate data, speed adjustment is achieved, so that the heart rate of a user is kept within the target heart rate range, and it can be ensured that the exercise intensity is moderate, scientific and safe.

A computer-implemented method is disclosed. The method includes determining a maximum target heart rate for a user using an electromechanical machine to perform a treatment plan, wherein the electromechanical machine is configured to be manipulated by the user while the user is performing the treatment plan. The method includes receiving, via an interface, an input pertaining to a perceived exertion level of the user, wherein the interface comprises a display configured to present information pertaining to the treatment plan. Based on the perceived exertion level and the maximum target heart rate, the method includes determining an amount of resistance for the electromechanical machine to provide via one or more pedals physically or communicatively coupled to the electromechanical machine. While the user performs the treatment plan, the method includes causing the electromechanical machine to provide the amount of resistance.

The application provides a heart rate detection method and an electronic device. In the method, the electronic device obtains first data of a user, and determines a first heart rate value according to the first data. When the first heart rate value does not satisfy a preset condition, the electronic device obtains second data of the user, determines a second heart rate value according to the second data, and the second data is related to a heart rate detection scene. The electronic device performs fusion processing on the first heart rate value and the second heart rate value, and determines a target heart rate value. Through the scheme, when the electronic device detects the heart rate of the user, if the first heart rate value determined based on the first data is inaccurate, the electronic device can obtain the second data related to the heart rate detection scene, generate the second heart rate value based on the second data, and generate the target heart rate value according to the first heart rate value and the second heart rate value, so that the inaccurate heart rate value can be calibrated in combination with the heart rate detection scene, and the accuracy of heart rate detection is improved.

The present invention relates to the technical field of electronic digital data processing, and particularly relates to a method for eliminating motion artifacts in a heart rate signal for heat tolerance monitoring. During the heat tolerance monitoring process, temperature data, acceleration data, and the PPG heart rate signal of blood vessels of a monitored object are acquired. Different types of each action are determined based on the acceleration data, and the segments of the PPG heart rate signal corresponding to different types of each action are decomposed to determine each IMF component corresponding to each action. According to each IMF component corresponding to each action and the temperature data, the influence of each IMF component corresponding to each action on motion artifacts is determined. Signal reconstruction is performed based on the influence of each IMF component corresponding to each action on motion artifacts to obtain the target PPG heart rate signal with motion artifacts eliminated, avoiding the situation where the heart rate signal is distorted due to motion artifacts, and being beneficial to improving the accuracy of heart rate measurement.

The present application relates to the technical field of treadmills, and particularly relates to an intelligent treadmill based on heart rate and a training method, which comprises the following steps: S1, acquiring instantaneous heart rate data of a runner at the moment when a preset cardiopulmonary endurance test prescription is completed, and calculating maximum oxygen uptake by combining the instantaneous heart rate data and basic information of the runner; S2, obtaining an oxygen uptake percentage by comparing the maximum oxygen uptake with an oxygen uptake percentage table, and calculating a target heart rate interval by combining the oxygen uptake percentage, gender and age; S3, executing a movement prescription based on the target heart rate interval of step S2 and acquiring an actual heart rate during the movement, and adjusting the movement intensity to maintain the actual heart rate within the target heart rate interval when the actual heart rate deviates from the target heart rate interval. The present application can avoid excessive movement or insufficient movement intensity, obtain the best movement prescription suitable for the runner, and thus help to improve the user experience of the runner when using the treadmill.