31 results about "Target heart rate" patented technology

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.

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 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.

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 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.

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 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.

The invention provides a dual-heart health early warning system and method based on millimeter wave radar and electronic equipment, and relates to the technical field of non-contact physiological signal processing, the system comprises a signal acquisition and processing module used for extracting a target respiration signal and a target heartbeat signal in an original echo signal; the multi-parameter adaptive classification module is used for carrying out heart function parameter extraction processing to obtain a target respiratory rate, a target heart rate, target heart rate variability and target cardiopulmonary coupling; the psychological and emotion evaluation module is used for obtaining a target psychological state evaluation result and a target emotion state evaluation result; and the fusion decision module is used for inputting the target respiratory rate, the target heart rate, the target heart rate variability, the target cardiopulmonary coupling, the target psychological state evaluation result and the target emotional state evaluation result into the double-heart linkage early warning model to obtain a physiological parameter early warning result. According to the method, physiological signals with higher precision are extracted, and effective early warning of psychological and heart parameters is realized.

This invention discloses a method and system for accurately reproducing non-invasive blood pressure oscillation waveforms, relating to the field of vital sign data monitoring technology. It constructs and superimposes a target pressure sequence by separately generating a target baseline pressure curve and a target oscillation pressure curve. The actual pressure signal is then separated into an actual baseline pressure curve and an actual oscillation pressure curve. This allows the baseline pressure error and oscillation pressure error to correspond to the baseline pressure control quantity and oscillation injection control quantity, respectively, avoiding the problem of unclear error sources when correcting composite pressure as a whole. When reproducing the same target systolic pressure, target diastolic pressure, target mean pressure, and target heart rate multiple times, it can reduce pressure overshoot, pressure drop rate fluctuations, oscillation pressure amplitude distortion, and oscillation envelope peak position offset. This makes the corrected non-invasive blood pressure oscillation waveform closer to the target pressure sequence, improving the consistency of the error verification results and repeatability evaluation results of the non-invasive blood pressure module under test.

A motion index calculation system suitable for obtaining a motion index that matches the physical characteristics of a subject is provided. [Solution] An exercise index calculation device 100 inputs a subject's age and resting heart rate, calculates a target heart rate using the Karvonen method calculation formula based on the subject's age, resting heart rate, and intensity (%), and calculates a baseline NSM using the CLS theory calculation formula based on the calculated target heart rate.The subject then exercises with a target NSM set based on the calculated baseline NSM, reads out measurement data measuring the NSM and heart rate at that time, and calculates an adapted NSM using an individualization formula based on the calculated target heart rate and the read out measurement data.The device also determines parameters of the individualization formula based on the measurement data, and classifies the subject's physical characteristics based on the determined parameters.

The invention discloses a heart rate determination method, electronic equipment and a computer readable storage medium, and relates to the technical field of wearable equipment, the heart rate determination method comprises the following steps: acquiring heart rate data detected by a plurality of wearable equipment worn by a user at the same moment; calculating a difference value between the heart rate data of any two wearable devices; based on a comparison result of the difference value and a preset consensus threshold value, whether any two wearable devices reach a consensus or not is determined, and the wearable devices reaching the consensus form a consensus group; based on the formation result of the consensus group, dynamically adjusting the equipment credit value of each wearable equipment; and based on the adjusted equipment credit value of each wearable equipment, carrying out fusion calculation or selection on the heart rate data of all the wearable equipment, and outputting to obtain a final target heart rate value. According to the method, the unified and dynamically-adjusted equipment credit value is introduced to replace the confidence coefficient, and a dynamic credit adjustment mechanism based on the consensus group enables a multi-equipment heart rate data fusion result to be more accurate and reliable.

The application relates to the technical field of air conditioners, and discloses a method for obtaining calories, which comprises the following steps: obtaining current heart rate information and a breathing frequency of a target user; determining a compensation strategy of heart rate information according to the continuous state of the current heart rate information and the breathing frequency, and obtaining target heart rate information according to the compensation strategy; and determining the calories of the target user according to a calorie estimation model corresponding to the heart rate information. The method can improve the accuracy of calorie consumption value calculation. The application further discloses a device for obtaining calories, an air conditioner and a storage medium.

The application discloses a heart rate detection method and device, a wearable device and a medium, and belongs to the electronic information field. The wearable device comprises a microphone and a target sensor. The heart rate detection method comprises the following steps: acquiring a first sound signal through the microphone and a second interference signal through the target sensor in the case that a user wears the wearable device; and obtaining a target heart rate parameter of the user according to the first sound signal and the second interference signal. In the case that the user wears the wearable device, the microphone and the ear canal of the user form a closed cavity.

The invention discloses a heart rate monitoring method and device based on wearable equipment, equipment and a medium, and relates to the technical field of heart rate monitoring, and the method comprises the steps that PPG data of a target object is collected through the wearable equipment, and a target heart rate measured value and a target heart rate variability index are obtained based on the PPG data; extracting target HIS data of a target object from an HIS system of a hospital, and inputting the target HIS data, the target heart rate measured value and the target heart rate variability index into a pre-training heart rate grading model, so that the pre-training heart rate grading model is matched with a corresponding target heart rate variability index abnormal range threshold table based on the target HIS data, and determining and outputting a heart rate alarm level corresponding to the target heart rate measured value according to the target heart rate variability index abnormal range threshold table. Compared with a mode of judging abnormal heart rate according to single heart rate data or simple standards, the method fully considers the influence of individual disease characteristics of the patient on the heart rate.

The application discloses a kind of based on radar vital sign detection method, equipment and storage medium, the detection method includes target detection to radar echo, obtain real target and its distance gate and respiratory rate at;The phase signal of the distance gate where real target is and the phase signal of the adjacent distance gate of the distance gate where real target is are normalized superimposed and unwound, and the vital sign signal of real target is obtained;Heartbeat band of vital sign signal is Chrip-Z development and maximum peak frequency search is carried out, and target heart rate is obtained.The phase signal of multiple distance gates is normalized fusion in the application, the signal-to-noise ratio of respiration and heartbeat signal is improved, and vital sign information carried by radar echo is fully utilized;High-resolution spectrum analysis in heartbeat band is realized by Chrip-Z development, heartbeat signal spectrum is refined, and the detection precision of vital sign parameter is improved.

The application discloses a heart rate detection method and device, a storage medium and an electronic device. A pulse wave signal and an acceleration signal of a user are acquired, and a current state of the user is determined. When the user is in a static state, time domain analysis is performed based on the pulse wave signal to obtain at least one first static heart rate value, and frequency domain analysis is performed based on the pulse wave signal to obtain a plurality of second static heart rate values. When the user is in a motion state, frequency domain analysis is performed based on the pulse wave signal to obtain a plurality of first motion heart rate values, and deep learning analysis is performed based on the pulse wave signal and the acceleration signal to obtain a second motion heart rate value. A target heart rate value of the user is determined according to the first static heart rate value and the second static heart rate value, or the target heart rate value of the user is determined according to the first motion heart rate value and the second motion heart rate value. In the static state, the time domain and the frequency domain are combined, the accurate heart rate value is obtained, and the energy consumption is reduced. In the motion state, the frequency domain and the deep learning are combined, and the more accurate heart rate value is obtained.

SMART TARGET HEART RATE MEDICAL DEVICE

The invention discloses a heart rate calculation method and device, intelligent wearable equipment and a storage medium, and relates to the technical field of signal processing.The method comprises the steps that after a pulse wave signal collected by the intelligent wearable equipment is subjected to frequency spectrum transformation and motion noise suppression processing, a pulse wave frequency spectrum signal is obtained; determining a preset number of frequency spectrum peak values from the pulse wave frequency spectrum signal, and taking the frequency corresponding to each frequency spectrum peak value as a candidate heart rate frequency; the comprehensive weight value of each candidate heart rate frequency is calculated according to the frequency spectrum peak value, the reference heart rate frequency and a rhythm stability factor, and the rhythm stability factor is a parameter for quantifying heartbeat cycle stability; and performing weighted average calculation on each candidate heart rate frequency based on the comprehensive weight value to obtain a target heart rate frequency. The problem that the heart rate monitoring result is inaccurate due to motion interference can be solved.

The invention discloses a health detection method and device, wearable equipment, an earphone and a storage medium, and relates to the technical field of wearable equipment, the method is applied to the wearable equipment, and the wearable equipment comprises a microphone, a temperature detection module and a heart rate detection module; the method comprises the following steps: acquiring a target sound signal and a target heart rate signal of a wearer through a microphone; acquiring target body temperature data of a wearer through a temperature detection module; preprocessing the target sound signal, the target heart rate signal and the target body temperature data to obtain a target sound feature, a target heart rate feature and a target body temperature feature; and obtaining a health detection result of the wearer based on the target sound feature, the target heart rate feature and the target body temperature feature. According to the method, the health state of the wearer is comprehensively analyzed by adopting the three parameters of the sound, the heart rate and the body temperature, and the health state of the wearer can be accurately and comprehensively reflected.

The invention discloses an abnormity alarm method, device and equipment in competition sports and a storage medium, and the method comprises the steps: determining the positioning information, sports data and heart rate parameters of a contestant, and determining the type of a racing road section where the contestant is located according to the positioning information, determining current motion reference information of the competitors according to the road section type and the motion data; determining a target heart rate threshold value corresponding to the current motion reference information according to the current motion reference information and a preset historical motion reference information and heart rate threshold value comparison table; under the condition that the parameter value of the heart rate parameter is larger than the target heart rate threshold value, the abnormal alarm information is generated based on the heart rate parameter, the purpose of determining the corresponding alarm threshold value according to the actual exercise intensity of the competitor can be achieved, the accuracy of the abnormal alarm result in the competition exercise is improved, and the timeliness of abnormal event processing is guaranteed.

The application relates to a self-provided filtering constant-flow escape breathing method, device, medium and electronic equipment, and relates to the technical field of escape breathing, wherein the method comprises the following steps: acquiring an actual heart rate and an actual oxygen supply rate of a target escape person; determining a target image of the target escape person, and determining whether the actual oxygen supply rate needs to be adjusted based on the actual heart rate, the actual oxygen supply rate, a target oxygen supply rate interval in which a historical escape person corresponding to the target image is prone to be when an adverse symptom occurs and at least one target heart rate range corresponding to the target oxygen supply rate interval; if yes, determining a suitable oxygen supply rate for the target escape person, and adjusting the actual oxygen supply rate to the suitable oxygen supply rate. The application has the effect of avoiding safety hazards in the escape process of the escape person.

The invention relates to the technical field of data processing, in particular to a heterogeneous health data fusion analysis method and device and a storage medium, and the method comprises the steps: collecting target physiological data, environment data and body movement data; dividing a target sleep stage based on the target breathing waveform and the target heart rate variability in the monitoring period; determining an environment interference factor according to the environment noise, the environment temperature and the illumination intensity in the monitoring period, and triggering an environment abnormity mark according to the environment interference factor; determining a target body moving frequency distribution entropy according to the target body moving frequency in the sleep cycle, determining body moving features based on the target body moving frequency distribution entropy, and constructing body moving feature factors; judging target sleep quality according to the target sleep stage of each monitoring cycle in the sleep cycle, the triggering result of the environment abnormity mark and the body movement characteristic factor, and updating the target sleep quality according to the target blood oxygen saturation in the sleep cycle. The sleep quality evaluation accuracy is effectively improved.

The invention discloses a treadmill heart rate self-adaptive control method and system. The treadmill heart rate self-adaptive control method comprises the steps that S1, a target heart rate value is set; s2, acquiring a treadmill speed instruction and the actual heart rate of the user in real time according to a preset period; s3, on the basis of the obtained historical data sequence, discrete time model parameters used for describing the speed-heart rate dynamic relation of the current user are identified and updated on line through a recursive least square method with a forgetting factor; s4, according to the discrete time model parameters, calculating adaptive controller parameters based on an internal model control principle; s5, a new treadmill speed instruction is determined according to the deviation between the target heart rate value and the actual heart rate of the user and the parameters of the self-adaptive controller; and S6, adjusting the target speed by using a new treadmill speed instruction, and returning to the step S2 for circulation. The intelligent heart rate control system has the advantages that high-precision and high-stability full-automatic heart rate control is achieved, personalized adaptation in the real sense is achieved, and the intelligent adaptive capacity for responding to dynamic changes of user states is achieved.

The application discloses a parameter automatic optimization pacing frequency self-adaptive adjusting device and a cardiac pacing device, which comprises an acceleration signal acquisition module, a motion amount evaluation and statistics module, a target heart rate calculation and statistics module, a pacing frequency adjusting and statistics module and a parameter automatic optimization module; the target heart rate value is determined through the motion amount evaluation value, the pacing frequency value at the next moment is determined through the size relation between the target heart rate value and the actual heart rate value and the selection of the time-pacing frequency rising / falling curve, the pacing related parameters are automatically optimized and adjusted, so that the program control setting of the frequency self-adaptive adjusting function is simplified, the function always works in the best parameter state, and the daily life quality is improved; after the daily life state changes, the pacing related parameters are also automatically optimized and adjusted, so that the needs of different dynamic changes can be met; after the upper and lower limit motion amounts are automatically optimized, the motion amount-target heart rate curve can adopt multiple adjustment strategies, and the personalized needs of different patients can be met.

The invention relates to the technical field of health data processing, in particular to a body function state monitoring method and platform and electronic equipment, and the method comprises the steps: collecting target physiological parameters, environmental parameters and target activity parameters; modeling is carried out on the target physical energy load index, and target physical energy load grades are divided; a modeling process of updating a target body energy load index according to the environment temperature and the environment humidity collected in the monitoring period; judging a target emotional state based on the high-frequency component and the low-frequency component of the target heart rate variability in the monitoring period; evaluating the target sleep quality based on the target deep sleep ratio and the target awakening frequency of each sleep analysis cycle in the management cycle; according to the target physical energy load level and the target emotional state of each monitoring period in the management period and the target sleep quality in the management period, the target physical state is judged, and an early warning is given to the user. The body function state monitoring efficiency is effectively improved.

The invention belongs to the technical field of millimeter wave radar vital sign detection, and aims to solve the problems that existing detection is easily interfered in a multi-target scene, heartbeat components are difficult to accurately separate, and heart rate variability index estimation precision is low. The invention provides a multi-target heart rate variability detection method based on signal decomposition and deep learning. The multi-target heart rate variability detection method comprises the following steps that chest phase signals from multiple targets are obtained; processing the chest phase signals to obtain a continuous chest phase time sequence, and extracting target sub-signals containing heartbeat components from the continuous chest phase time sequence; inputting the target sub-signals into a verified deep learning heartbeat signal reconstruction network to obtain reconstructed heartbeat waveforms of a plurality of targets; carrying out heartbeat peak value detection according to the reconstructed heartbeat waveform to obtain a time interval sequence between adjacent heartbeat peak values; a heart rate variability indicator is calculated based on the sequence of time intervals. The reliability of heartbeat signal extraction and the accuracy of heart rate variability evaluation can be improved in a multi-target non-contact monitoring scene.

The application discloses an AI physical fitness evaluation and target heart rate generation method and system based on multi-modal data. The application collects physiological signs, cardiopulmonary timing, visual posture, and multi-modal data of traditional Chinese medicine constitution, and constructs a standardized physical fitness data set through preprocessing. According to physiological threshold, three types of people are divided, and the main constitution and combined constitution typing coding are completed in combination with the nine-body model of traditional Chinese medicine. Taking the basic heart rate as the benchmark, the personalized limit heart rate is obtained through the weighted fusion correction of six types of coefficients, the three-level target heart rate interval is divided, and the personalized exercise scheme is generated. The artificial review is started for the high-risk group. The heart rate interval is monitored and corrected in real time during exercise, and the early warning is triggered according to the adaptive rule. The application realizes the integration of traditional Chinese and western medicine and dynamic closed-loop regulation, solves the problems of single dimension, insufficient individualization and high safety risk of traditional heart rate measurement, improves the evaluation accuracy, exercise safety and effectiveness, and adapts to offline operation and large-scale popularization of various devices.

This application discloses a non-contact heart rate monitoring and cardiac screening method based on 1300nm shortwave infrared light, belonging to the field of image processing technology. It includes: acquiring multiple frames of target face images captured by a 1300nm infrared camera; sequentially arranging the multiple frames of target face images to obtain a time-series signal; sending the time-series signal to a face nose region recognition and data acquisition module, locating the nose region in the time-series signal based on the Dlib algorithm, and collecting the average grayscale value of the pixels in the nose region to obtain the heart rate signal to be processed; sending the heart rate signal to be processed to a feature signal extraction module, sequentially performing detrending, mean removal, wavelet transform, and Kalman filtering to obtain a feature signal representing the heart rate; inputting the feature signal representing the heart rate to a heart rate status judgment module, obtaining the target heart rate through Fourier transform, and judging the target heart rate based on a two-level comparison strategy to obtain the target heart rate status. This method improves the accuracy and efficiency of cardiac screening.