28 results about "Abnormal heart rate" patented technology

The present invention discloses a dynamic early warning system for cardiac arrest based on multimodal data fusion, belonging to the field of medical information technology. Specifically, it includes: a non-contact sensing module for continuously acquiring the physiological parameters of a user based on non-contact devices; an active wearing module for starting the acquisition of contact physiological parameters when the user actively triggers the wearing device; a scene adaptive module for constructing a physiological parameter baseline only based on non-contact sensing data when the wearing device is not triggered; when the user triggers the wearing device, cross-verifying the contact data and the non-contact data and correcting the calibration parameters of the non-contact data; a risk decision module for starting a forced verification process of contact data when the non-contact detection detects an abnormal heart rate; if the verification fails or there is no response, generating a corresponding risk level early warning based on the continuous abnormal duration and the fluctuation pattern; the present invention realizes dynamic early warning based on multimodal data.

A closed-loop percutaneous ear vagus nerve stimulation system acting on insomnia, the system comprising: an electrocardiogram monitor for monitoring the heart rate of a patient; the power supply module is used for supplying power to the electrocardiogram monitor; the heart rate variability sensor is used for sensing heart rate data, collecting the heart rate data and transmitting the heart rate data to the feedback controller; the feedback microcontroller is used for receiving and processing the heart rate data and identifying abnormal heart rate data generated before or during the attack of insomnia; the pulse generator is used for outputting electric pulses to the percutaneous auricular concha area vagus nerve stimulator; and the percutaneous auricular concha area vagus nerve stimulator is used for stimulating the auricular concha area vagus nerve by adopting a vagus nerve stimulating electrode.

The invention discloses a sudden cardiac arrest dynamic early warning system based on multi-modal data fusion, and belongs to the technical field of medical information, and the system specifically comprises a non-contact sensing module which is used for continuously obtaining physiological parameters of a user based on a non-contact device; the active wearing module is used for starting contact type physiological parameter acquisition when a user actively triggers the wearable equipment; the scene self-adaption module is used for constructing a physiological parameter base line only based on the non-contact sensing data when the wearable equipment is not triggered; when the user triggers the wearable device, performing cross validation on the contact data and the non-contact data, and correcting calibration parameters of the non-contact data; the risk decision module is used for starting a contact type data forced verification process when the heartbeat frequency is detected to be abnormal in a non-contact manner; if verification fails or no response is made, corresponding risk level early warning is generated based on the continuous abnormal duration and the fluctuation mode; according to the invention, dynamic early warning is realized based on multi-modal data.

The invention discloses a medical big data analysis blood pressure alarm system and device based on a block chain technology. The system comprises a data acquisition module, a block chain service unit, a central processing unit and a storage database; the data acquisition module is used for acquiring heart rate data and blood pressure data of a user and sending the acquired data to the block chain service unit; and the block chain service unit is used for sending the received heart rate data and blood pressure data to the central processing unit according to a block chain service node. The heart rate and blood pressure data of the elderly user in medical treatment are monitored based on the block chain technology, the monitored data are analyzed in real time, the blood pressure change condition of the elderly user is judged, when the heart rate and blood pressure abnormal condition occurs, the condition of the elderly user can be timely alarmed and reminded through a mobile phone APP and a short message, and the user experience is improved. Monitoring of old people with hypertension and timely treatment in case of conditions are effectively improved.

The application relates to an exposure method, a medical imaging system, an electronic device and a storage medium, wherein the exposure method comprises the following steps: acquiring heart rate data of an object to be exposed and an exposure period; selecting an exposure mode corresponding to the heart rate data according to the heart rate data; and exposing the object to be exposed according to the exposure mode and the exposure period. According to the application, the object to be scanned with abnormal heart rate and the object to be scanned with normal heart rate can be scanned, and the scanning accuracy is improved.

This invention discloses an abnormal heart rate diagnostic system based on a lightweight spiking neural network, comprising: a data denoising module for denoising the input electrocardiogram (ECG) signal; a data segmentation module for segmenting the denoised ECG signal; a network construction module for constructing a lightweight spiking neural network consisting of a feature extraction network and a classification network connected sequentially; wherein the feature extraction network includes multiple branches of feature extraction modules, each branch including several sequentially connected IFR modules; the classification network includes first and second layer SGRU modules connected sequentially; a network training module for training the constructed lightweight spiking neural network using the segmented ECG signal to obtain a trained lightweight spiking neural network; and a data diagnosis module for inputting the ECG signal to be diagnosed into the trained lightweight spiking neural network to obtain a diagnostic result. This invention improves the accuracy of ECG signal classification.

The utility model discloses an intelligent monitoring bed for a prison, which belongs to the technical field of prison equipment and comprises a bed frame with bed legs, a bed board is laid at the upper end of the bed frame, the intelligent monitoring bed further comprises a monitor used for monitoring heart rate and respiratory rate, and an embedding opening used for embedding the monitor is arranged on the surface of the bed board. A bearing frame used for bearing the monitor is fixedly arranged at the lower end of the bed frame, and a connecting assembly is fixedly arranged at the lower end of the monitor. The monitor is arranged to monitor the heart rate and the respiratory rate in real time, the physiological health condition of a supervised person is effectively mastered, early warning can be conducted in time once the heart rate is abnormal or the respiratory rate is disordered, a worker can rapidly take corresponding measures, safety risks caused by sudden health problems are greatly reduced, and the life safety of the supervised person is guaranteed.

This invention discloses a traditional Chinese medicine composition for assisting in the improvement of hand-foot-mouth disease in infants and young children, belonging to the field of traditional Chinese medicine technology. The composition consists of eight medicinal herbs: lotus leaf, coix seed, angelica dahurica, kudzu root, platycodon root, agastache rugosa, cimicifuga rhizome, and dandelion, with a defined optimal medicinal ratio. Based on the seasonal differences in the pathogenesis of hand-foot-mouth disease, this invention targets the core pathologies of winter (cold congestion of microvessels, water and sodium retention, and internal heat generation) and spring and summer (hypothalamic sympathetic activation, increased heart rate, and visceral heat overload). It also addresses the technical deficiencies of clinical Western medicine, cold-natured traditional Chinese medicine, calamine lotion, and diuretics, such as vasoconstriction, kidney damage, central nervous system disorders, increased skin exudation, and rebound water retention. This invention employs a combination of warming and cooling herbs, regulating the ascending and descending functions, and promoting diuresis and protecting the body's vital energy. The synergistic effects of these herbs can dilate spasmodic microvessels, improve renal perfusion, stabilize abnormal heart rates, stabilize the hypothalamic center, and assist in antagonizing enteroviruses. By targeting and reducing abnormal permeability of skin capillaries with Angelica dahurica and Platycodon grandiflorus, it reduces blood extravasation and inhibits the formation and exudation of herpes from the root cause. This invention has mild medicinal properties, is suitable for all seasons, and has high safety. It can effectively improve symptoms of hand-foot-mouth disease such as fever, herpes, irritability, and cold extremities, reduce the risk of severe illness, antagonize the toxic side effects of commonly used clinical drugs, and is suitable for the delicate constitution of infants and young children, possessing good prospects for clinical application and promotion.

The invention relates to the technical field of disease risk prediction, and discloses a heart rate calculation method and system for a wearable acquisition device.The heart rate calculation method for the wearable acquisition device.The heart rate calculation method for the wearable acquisition device.The heart rate calculation method for the wearable acquisition device.The heart rate calculation method for the wearable acquisition device comprises the steps that PPG signals acquired by the wearable device are analyzed on multiple time scales, and morphological characteristics of the multiple time scales are extracted; processing the multi-scale morphological features by using a multi-head attention neural network; adaptively adjusting the importance weight of each feature in the attention network according to the user features; on the basis of the adjusted attention network output, detecting heart rate abnormity by comparing current waveform features with templates in a self-learning normal waveform library, continuously optimizing individualized feature distribution through an incremental learning mode, and continuously optimizing the individualized feature distribution through incremental learning; according to the method, the detection accuracy of abnormal heart rhythms of different user groups can be effectively improved.

A multifunctional sleep monitoring method based on a millimeter wave radar comprises the following steps: carrying out recombination, frame division and clutter removal on collected original ADC data, obtaining a target distance spectrum through one-dimensional FFT and inter-frame difference, and determining a target distance unit by adopting non-coherent accumulation. Extracting the phase information of the unit signal, unwrapping and differentiating to obtain a vital sign signal, separating breathing and heartbeat components by utilizing multi-mode decomposition and reconstruction, and obtaining the breathing frequency and the heart rate through Fourier transform; performing two-dimensional FFT and DBSCAN clustering on the data after inter-frame difference, generating three-dimensional point cloud data in combination with angle FFT, and inputting the three-dimensional point cloud data into a DGCNN and Transform cascade network to realize sleeping posture recognition; the system can analyze the vital signs and the sleeping posture state in real time, and when it is detected that apnea, abnormal heart rate or dangerous sleeping postures continuously exceed preset time, alarm information is automatically output. The method has the advantages of non-contact, high precision and real-time performance.

The invention relates to the technical field of lifesaving equipment, in particular to a drowning prevention lifesaving bracelet capable of sensing heart rate abnormity and automatically inflating, which comprises a bracelet shell, an operation panel, a central control chip, an air bin, an air bag and a pop-up assembly, the pop-up assembly comprises a pop-up plate, a plurality of pop-up springs, a plurality of rollers, a mini abutting plate and two torsion springs, the bracelet shell is annular, and the operation panel is arranged on the bracelet shell. The bracelet shell is provided with a wearing groove and a storage bin, the two torsional springs drive the mini abutting plate to rotate and be opened, meanwhile, the pop-up spring drives the pop-up plate to move, the air bag in the storage bin is popped up, and then the air bin starts to inflate the air bag, so that a user floats upwards; therefore, the resistance of water flow can be reduced through the mini abutting plate, meanwhile, the opening of the mini abutting plate can be accelerated and the popping speed of the air bag can be increased through the cooperation of the torsional spring and the popping spring, and the air bag is separated from components in the bracelet shell by virtue of the independently arranged storage bin, so that the damage to the whole bracelet and the components in the bracelet during rapid popping is avoided.

The present invention relates to the technical field of disease risk prediction, and discloses a heart rate calculation method and system for wearable data acquisition devices, wherein a heart rate calculation method for a wearable data acquisition device comprises: analyzing PPG signals collected by the wearable device at multiple time scales, and extracting morphological features at multiple time scales; applying a multi-head attention neural network to process the multi-scale morphological features; adaptively adjusting the importance weight of each feature in the attention network according to user characteristics; based on the adjusted attention network output, detecting abnormal heart rate by comparing the current waveform features with templates in a self-learning normal waveform library, and continuously optimizing the individualized feature distribution through incremental learning; and continuously optimizing the individualized feature distribution through incremental learning; the method can effectively improve the detection accuracy of abnormal heart rhythm for different user groups.

The present invention relates to a children's bed, and in particular to an intelligent children's bed with a sleep monitoring function. The present invention provides an intelligent children's bed with a sleep monitoring function that can detect a child's heart rate in real time to ensure safety. An intelligent children's bed with a sleep monitoring function comprises a base plate, a support base, a mattress and a pillow. The top of the base plate is clamped with a support base, the bottom surface of the support base is arc-shaped, a mattress is installed on the top of the support base, a pillow is placed on one side of the top of the mattress, and support rods are symmetrically fixed on the opposite sides of the support base. The child's situation on the mattress can be monitored in real time by a monitor, which is convenient for family members to understand, and the heart rate detector can detect the child's heart rate. When the child has an abnormal heart rate, it can send a signal to the parent's mobile phone in time, so that the parent can deal with the situation in time and improve the child's safety.

The application discloses a heart rate anomaly reminding method, a mobile terminal and a computer readable storage medium. The heart rate anomaly reminding method is executed by a first mobile terminal, and the reminding method comprises the following steps: receiving abnormal heart rate information from an earphone end, wherein the abnormal heart rate information is sent by the earphone end when it is detected that the heart rate of a user is abnormal; in response to the received abnormal heart rate information, acquiring video and audio information related to the user; and sending the abnormal heart rate information and the video and audio information to a second mobile terminal. The technical scheme of the application enables the relatives and friends of the user to timely grasp the physical condition of the user even if they are not around the user, and provides safety protection for the user.

The invention relates to the technical field of patient vital sign monitoring, in particular to an emergency ICU patient vital sign rapid monitoring device. The invention provides a quick monitoring device for vital signs of an emergency ICU (Intensive Care Unit) patient, which can give an alarm and call in time when detecting abnormal heart rate and body temperature of the patient and discomfort of the patient, and is convenient for taking timely and effective medical intervention. An emergency ICU patient vital sign rapid monitoring device comprises a detector, wrist straps and the like, and the left portion and the right portion of the detector are both rotationally connected with the wrist straps. When the heart rate or the body temperature of a patient is abnormal, the vibrator generates vibration prompt, the alarm gives an alarm to prompt medical staff, and when the patient is awake, the patient can press a call button to call the medical staff to check in time. And the effects of timely alarming and calling when the abnormal heart rate and body temperature of the patient and the discomfort of the patient can be detected, and timely and effective medical intervention can be conveniently adopted are achieved.

The invention provides intelligent equipment for assisting heart rate detection. The intelligent equipment comprises a main body structure, a direct-current power supply voltage line and a processor, and the direct-current power supply voltage line is arranged at a preset position on the main body structure; the processor is electrically connected with the direct-current power supply voltage line; the processor is used for periodically sampling the voltage of the direct-current power supply voltage line, responding to the condition that the ripple of the voltage meets a preset condition, and obtaining the heart rate of a user based on the ripple; wherein the ripples are caused by mechanical vibration generated when a user acts on the main body structure. No sensor needs to be added, the voltage of the direct-current power supply voltage line is monitored, mechanical vibration caused by heartbeat when the human body makes contact with the intelligent device can cause the voltage to generate ripples, the heart rate is in positive correlation with the ripples, and the higher the heart rate is, the larger the ripples are; the higher the heart rate is, the denser the crests and troughs of the ripples are; the heart rate of the user is calculated based on the ripples, heart rate abnormity can be found in an auxiliary mode, the user is prompted in time, and the hardware cost of a sensor is not increased.

The invention discloses an elevator emergency rescue method and an elevator integrated with an AED device, and relates to the technical field of elevators, the elevator emergency rescue method comprises the steps that AI images and sign information of passengers in a lift car are collected, the AI images comprise body discomfort information, and the sign information comprises breathing information and heart rate information; according to the A I image, whether a passenger in the car has an abnormal behavior of body discomfort or not is recognized, and a posture analysis result is generated; according to the physical sign information, whether the passengers in the lift car have dyspnea or abnormal heart rate or not is recognized, and a physical sign analysis result is generated; and judging whether an emergency rescue program needs to be started and implemented or not according to the posture analysis result and the physical sign analysis result. By the adoption of the method, whether a person has sudden cardiac arrest in the elevator car or not can be monitored in real time, and linkage of the monitoring result and the emergency rescue program of the elevator is achieved.

The invention provides a heart rate anomaly detection method and system, computer equipment and a storage medium, and belongs to the field of health monitoring, and the method comprises the following steps: in different environments, collecting piezoelectric signals and heart rate data of different healthy people in different postures; mapping the piezoelectric signals to a plurality of random representation spaces by using a convolutional neural network, and extracting depth representation features of the piezoelectric signals; on each random representation space, recursive axis parallel partitioning is carried out by randomly selecting feature dimensions and segmentation threshold values, a plurality of isolated trees are constructed, and a deep isolated forest is formed through the plurality of isolated trees; the depth representation features and the heart rate data of the testee are input into a depth isolated forest, and the abnormal score of the heart rate data is calculated by counting the average path length of each piece of heart rate data in all isolated trees; and marking the heart rate data with the abnormal score higher than a threshold value as an abnormal heart rate event. According to the method, the abnormal heart rate event can be quickly recognized on the premise that a large number of abnormal samples do not need to participate in training.

The invention discloses an integrated blood transfusion apparatus, and belongs to the technical field of medical treatment. An integrated blood transfusion device comprises a pair of puncture outfits, a filter is arranged between the two puncture outfits, an injection needle connected through a second transmission tube is arranged at the lower end of the filter, and a flow speed regulator with a roller is arranged outside the second transmission tube. The problems that in the transfusion process of an existing blood transfusion and transfusion integrated device, the heart rate of a patient cannot be continuously detected in the transfusion process, medical workers cannot be called under the condition that the heart rate is abnormal, and the workload of the medical workers is increased are solved. The rolling wheel longitudinally slides along the movable rail so that the flowing speed of the liquid in the second conveying pipe can be actively adjusted, the speed adjustment is conducted after the fingertip oximeter detects that the heart rate of the patient continuously rises, and meanwhile a buzzer reminds medical staff.

The invention relates to the technical field of general control systems, in particular to an intelligent rehabilitation pectoral girdle regulation and control method based on real-time data acquisition, which comprises the following steps: determining a heart rate abnormity time period, and determining the heart rate abnormity time period according to the dissimilarity between the respiration abnormity change and the pressure change of the heart rate in the heart rate abnormity time period; screening out a plurality of suspected wound influence sensors from the pressure sensors, and screening out a plurality of wound influence sensors from the suspected wound influence sensors according to the distance between the suspected wound influence sensors and the similarity between the pressure sequential sequences corresponding to the adjacent suspected wound influence sensors; a wound sensor is screened out from the wound surface influence sensors, a trend value is determined, and therefore tightness adjustment is conducted on the adjusting structures corresponding to the wound surface influence sensors. The rehabilitation pectoral girdle at the wound is adjusted in a self-adaptive mode, unnecessary compression on the wound surface is avoided, and therefore recovery of the wound is better promoted.

The invention belongs to the technical field of tunnel construction, and particularly relates to tunnel operator health monitoring equipment and an intelligent scheduling method.The tunnel operator health monitoring equipment comprises a smoke exhaust pipeline, air exhaust mechanisms are arranged on the outer surface of a supporting column pipeline at the lower end of the smoke exhaust pipeline in an array mode, and an electric sliding rail is fixedly connected to the outer surface of the upper end of a smoke exhaust pipeline network; a conductor rail is arranged on one side of the electric sliding rail, and the upper end of the conductor rail is fixedly connected with the outer surface of the upper end of the smoke exhaust pipeline. According to the monitoring equipment, the gas sensor and the temperature sensor are arranged at the upper end of the mounting block, and the health monitoring ring worn by an operator is arranged, so that synchronous acquisition of tunnel environment data and personnel physiological data is realized. The controller data processing module analyzes and compares data in real time, risks such as excessive harmful gas, abnormal temperature or abnormal heart rate and blood oxygen of people are warned in advance, safety accidents caused by environmental deterioration or non-timely discovery of potential health hazards are avoided, and a dual safety defense line is built for tunnel operation.

This invention discloses a method and system for detecting atrial fibrillation (AF) on electrocardiograms based on the fusion of time-series and waterfall plot models, belonging to the fields of biomedical signal processing and deep learning technology. This method simultaneously constructs two complementary data representations of the same electrocardiogram signal: a fixed-duration one-dimensional time-series segment and a two-dimensional heartbeat stacked grayscale waterfall plot aligned with the R-wave. These are respectively input into independently trained one-dimensional and two-dimensional convolutional residual networks for classification. Finally, the outputs of the two models are aligned at the heartbeat time granularity, and the final AF detection result is obtained through a configurable fusion strategy (intersection, union, or weighted voting). The time-series model excels at capturing abnormal heart rate rhythms, while the waterfall plot model excels at identifying abnormal waveform morphology; the two are significantly complementary in boundary cases. In 2,433,594 heartbeat tests with balanced distribution of AF and NAF samples (AF accounting for 43.7%), the false alarm rate decreased from 4.30% to 1.30% and the missed alarm rate decreased from 1.07% to 0.59% after adopting the intersection fusion strategy. The prediction conflict rate between the two models was only 2.43%, which proves that the two-dimensional fusion has a significant complementary gain effect under neutral distribution conditions.

The invention provides a heart rate recognition and abnormal heart rate detection method based on PPG and BP signals. The heart rate recognition and abnormal heart rate detection method comprises the steps that 1, a blood pressure waveform, SV, an electrocardiogram and a photoplethysmography signal are obtained; 2, preprocessing the data acquired in the step 1; step 3, performing feature extraction on each preprocessed signal; and 4, performing comprehensive analysis based on the extracted features, and identifying whether the heart rate of the patient is normal or not. According to the method, the robustness and accuracy of heart rate recognition are enhanced through the multi-signal fusion technology, meanwhile, the reliable monitoring capacity of the heart rate is improved through machine learning and a signal processing algorithm, and compared with independent electrocardiogram detection, the method can obviously improve the patient monitoring accuracy and reduce the false alarm rate.

The invention discloses an indoor and outdoor positioning bracelet for real-time heart rate abnormity warning, which comprises a body and a quick-release clamping needle type wrist strap, and the quick-release clamping needle type wrist strap is mounted on the body. A main control board is arranged in the body, and the main control board is provided with a health monitoring system, an intelligent positioning system, a dynamic strategy adjusting system, an SOS one-key alarm system and an offline voice broadcast system. The invention discloses an indoor and outdoor positioning bracelet for real-time heart rate abnormity alarm, and aims to solve the problems of single function, insufficient positioning precision, inaccurate health monitoring, lack of safety function, low data reliability, high power consumption and the like of the conventional bracelet.

The invention relates to the technical field of data acquisition and management, in particular to a multi-modal data acquisition and management system and intelligent method for old people, and the system comprises a multi-modal data acquisition unit, an edge computing gateway, an acousto-optic voice alarm unit and a cloud analysis and decision unit. The multi-modal data acquisition unit comprises a physiological data acquisition module, an environment data acquisition module, a behavior activity data acquisition module and a video and audio data acquisition module; the physiological data acquisition module acquires heart rate and gait data through wearable equipment; the environment data acquisition module acquires indoor temperature and humidity and illumination data through an environment sensor; local real-time analysis and privacy protection are achieved, audio and video collection is triggered only under the emergency conditions such as suspected tumble and abnormal heart rate, the privacy risk of continuous monitoring is avoided, the personalized recognition requirement is met, and an active health monitoring and safety guarantee scheme with low cost and high reliability is provided for old people.

The invention relates to the technical field of health management, in particular to health management monitoring equipment which comprises a wearable shell, a circulation pipeline is arranged in the wearable shell, an upper water bag cavity and a lower water bag cavity are formed in the front side of the wearable shell, the circulation pipeline is communicated with the upper water bag cavity and the lower water bag cavity, and a control mechanism is arranged between the upper water bag cavity and the lower water bag cavity; a heart rate detector is further arranged on the front side of the wearable shell; an adjusting switch is arranged in the circulation pipeline on the rear side of the wearable shell, knocking reminding assemblies are arranged at the two ends of the upper side of the wearable shell, and the adjusting switch is connected with the knocking reminding assemblies. The wearable device further comprises a rotary adjusting assembly arranged on the front side of the wearable shell, and the rotary adjusting assembly is connected with the control mechanism and the heart rate detector. In combination with the influence of sitting postures on the heart rate, the effect of reminding and adjusting the sitting postures in three directions to improve the heart rate when the sitting postures are bad is achieved, when the heart rate of old people is too slow, the control mechanism is triggered to achieve heating so as to promote heart rate recovery, and the health problem caused by abnormal heart rate is solved.

1. The name of the design product: heart and lung monitoring graphical user interface for electronic device. 2. The use of the design product: running programs and displaying information. 3. The design points of the design product: the graphical user interface in the screen, the heart and lung radar is the existing design. 4. The picture or photo that best shows the design points: design 1 front view. 5. The product shape is a conventional design, and other views are omitted. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: the graphical interface of the product is the application interface of the heart and lung radar, which can display and interact with the heart and lung information of the personnel in the monitoring area. The interface of design 1 front view is the interface before entering normal working state after starting; when entering normal working state and monitoring normal heart and lung information of personnel, from design 1 front view to design 1 change state diagram 1; when monitoring abnormal heart rate or respiration of personnel, starting abnormal alarm function, from design 1 change state diagram 1 to design 1 change state diagram 2. The interface of design 2 front view is the interface before entering normal working state after starting; when entering normal working state and monitoring normal heart and lung information of personnel, from design 2 front view to design 2 change state diagram 1; when monitoring abnormal heart rate or respiration of personnel, starting abnormal alarm function, from design 2 change state diagram 1 to design 2 change state diagram 2.

The invention relates to the technical field of remote biomedical monitoring, in particular to a pet heart rate monitoring system based on cloud computing, which comprises a heart rate fluctuation recording module, a motion mode tracking module, an abnormal marking module, a grading evaluation module and an abnormal signal triggering module. According to the method, real-time mammalian pet heart rate data are collected and analyzed, so that the real-time performance and accuracy of pet health monitoring are remarkably improved, heart rate fluctuation is captured in real time, changes in a short time are recognized, the monitoring system can quickly respond to pet health changes, potential health problems are recognized in time, and the pet health monitoring efficiency is improved. The synchronous collection of data is accelerated to further enrich the recognition of motion modes, the change of stride frequency and motion direction is analyzed, more comprehensive understanding of pet motion modes is provided, the heart rate and motion data are synthesized, the recognition of abnormal states is more accurate, the correlation with motion states can be rapidly evaluated when the heart rate is abnormal, and the accuracy of the abnormal heart rate is improved. And the pet health risk can be predicted and identified more effectively.