194 results about "Fetal heart" patented technology

The invention relates to the technical field of model construction, in particular to an obstetric delivery decision model construction method based on a knowledge graph. The method comprises the following steps that multi-dimensional information collection is conducted on a pregnant woman to be delivered, individualized data are obtained, and the multi-dimensional information comprises a medical record text, a laboratory examination result, an ultrasonic image and fetal heart rate monitoring data; performing standardization and structural processing on the individualized data to generate a standardized multi-modal data set; performing entity identification and relation extraction processing on the standardized multi-modal data set according to a preset obstetrical domain ontology model to obtain an initial knowledge graph; and carrying out priori knowledge-based mapping expansion on the initial mapping knowledge domain to obtain a multi-modal mapping knowledge domain. Through an attention mechanism and a decision support interface, the interpretability of the model is enhanced, and doctors can understand and trust decision suggestions.

The invention relates to the technical field of medical health data intelligent processing, in particular to a gestational diabetes patient family doctor management method and system based on artificial intelligence, and the method comprises the steps: 1, collecting patient data through a dynamic glucometer, a fetal heart monitor and a hospital information system; 2, aligning the multi-source data according to timestamps to construct a time sequence data set; 3, generating a complication risk score containing a ketoacidosis risk and a giant child risk; 4, generating a personalized sugar control scheme based on the risk score and a pre-constructed medical knowledge graph; 5, integrating opinions of multiple parties to generate a final edition scheme; and step 6, updating deep learning model parameters based on feedback data. According to the mode, the treatment efficiency and accuracy are improved, the control scheme can be adjusted in real time, and the health and safety of the patient in the pregnancy period are ensured. In addition, a feedback mechanism can continuously optimize the system, a closed loop is formed, and the management effect is further improved.

The invention relates to the technical field of remote measurement, in particular to a remote monitoring system for gynaecology and obstetrics patients, which comprises a fetal heart rate data acquisition module for acquiring fetal heart rate signals, integrating signal timestamps and signal values, establishing a fetal heart rate time sequence data set, adjusting dynamic scale factors of the fetal heart rate time sequence data set, and acquiring the fetal heart rate data; and executing time sequence analysis to obtain a time sequence analysis result. According to the method, the data accuracy and the processing efficiency are effectively enhanced by establishing a time sequence data set and adjusting a dynamic scale factor, and the system improves the data analysis depth and enhances the periodic mode identification capability by executing multi-scale entropy calculation and performing periodic mode identification, which is crucial for early pregnancy problem identification. And the detection of the abnormal mode and the comparison of the historical health data further improve the sensitivity and preventability of monitoring, so that the abnormal condition can be found and processed in time.

The invention discloses a fetal heart uterine contraction automatic interpretation system based on network characterization, which comprises a network model, and the network model comprises a CV module, an AT module, an SW module and a TC module which are connected in sequence; the CV module encodes low-level spatio-temporal information in the CTG signal through three convolutional layers; the AT module comprises a plurality of self-attention layers; the TC module uses a time convolution network to extract advanced time features in a time sequence, and inputs the advanced time features into a full connection layer with a Sigmoid classifier. According to the method, a multi-representation and multi-model integration thought is adopted, related features beneficial to CTG interpretation are fully extracted, the problem that a manual feature extraction algorithm is insufficient in capturing a long-time-span dependency relationship is solved, subsequent various analysis and research on CTG signals are facilitated, and the method is suitable for popularization and application. More accurate and reliable diagnosis information is provided for doctors and applied to the field of medical signal processing, and a more accurate and reliable auxiliary diagnosis tool is provided for clinicians.

The invention discloses an end-edge-cloud collaborative pregnancy risk assessment system, and relates to the field of medicine. The system comprises three modules which are fetal heart and pregnant woman heart rate monitoring equipment of end equipment, a pregnant woman user mobile phone APP of edge equipment and a high-risk pregnancy risk degree evaluation system of a cloud platform. The monitoring device is composed of a fetal heart device and an ECG device which are used for collecting heartbeat data of a fetus and a pregnant woman in real time and calculating the heart rate. During detection, the monitoring device needs to be placed at a corresponding position of a pregnant woman, and the pregnant woman uses the mobile phone APP for control. By optimizing the cooperative work of the doctor management end, the mobile phone edge device and the monitoring device, the system not only can improve the working efficiency of doctors, but also can enhance the self health management ability of pregnant women.

The invention discloses a fetal heart rate signal data enhancement method based on a conditional diffusion model, and the method comprises the steps: firstly obtaining and preprocessing a fetal heart rate signal, and obtaining a fetal heart rate signal containing noise; then, a noise prediction model based on conditional diffusion is constructed, the noise prediction model based on conditional diffusion comprises a conditional auxiliary information coding module and a noise prediction network module, and the fetal heart rate signal data containing noise are used for training the noise prediction model based on conditional diffusion; and finally, denoising the fetal heart rate signal by using the trained noise prediction model based on conditional diffusion. According to the method, the defects of a traditional generation model in the aspects of training stability, mode diversity and signal quality are effectively overcome, high-quality and high-fidelity data support is provided for fetus health condition evaluation, and a referable mode is provided for a data generation task of a time sequence signal.

The invention relates to the technical field of medical ultrasonic image processing, in particular to a fetal heart standard section detection method based on multiple tasks, which comprises the following steps: acquiring a to-be-detected fetal heart section image, inputting a target detection model, outputting types, quantity and positions of anatomical structures in the to-be-detected fetal heart section image, and classifying the to-be-detected fetal heart section image based on a classification algorithm. And obtaining a judgment and classification result of the fetal heart section image to be detected. On the basis of a target detection model path fusion feature pyramid, a self-adaptive spatial feature fusion module containing sampling operation and small-size feature map fusion branches and an interleaving path are added, and a path interleaving pyramid network based on the self-adaptive spatial feature fusion module is constructed as a neck network of a target detection model. And meanwhile, a detail fusion enhancement module introducing an optimized feature fusion strategy is utilized, so that the recognition precision of a key anatomical structure in the fetal heart ultrasonic image and the accuracy of section judgment and classification results are improved.

The invention provides a fetal heart region image segmentation method and system, electronic equipment and a storage medium, and the method comprises the steps: segmenting a current frame image of fetal heart body data through employing an inference network and a Canny edge detection algorithm; the fetal heart segmentation area of the current frame image is determined according to the obtained first fetal heart segmentation area and the second fetal heart segmentation area, and the inference network carries out inference based on the two-dimensional features and the three-dimensional features of the current frame image to obtain the first fetal heart segmentation area. The invention aims to combine two-dimensional information and three-dimensional information of an image so as to effectively solve the problems of non-fitting edges and poor reasoning effect of some frames in 3D segmentation, and a segmentation result of a Canny edge detection algorithm is used as a reference to help to judge and correct segmentation output generated by a reasoning network so as to improve the efficiency of 3D segmentation. By combining the advantages of the multi-source features and the Canny edge detection algorithm, the precision of complex heart structure segmentation is improved, and a more reliable segmentation result can be obtained.

The invention discloses a fetal heart analysis method, device and equipment and a storage medium. The method comprises the steps that fetal heart data and user basic information uploaded by a user are acquired; the fetal heart data and the basic information of the user are input into a preset fetal heart analysis model, a fetal heart analysis result is obtained, and the preset fetal heart analysis model comprises a position coding module, a bidirectional gating circulation unit, a channel attention mechanism, a multi-scale feature extraction module and a feature fusion module; and distributing the fetal heart data, the basic information of the user and the fetal heart analysis result to doctors of different grades according to the fetal heart analysis result. The fetal heart data and the basic information of the user are input into the preset fetal heart analysis model to obtain the fetal heart analysis result, and the preset fetal heart analysis model comprises the position coding module, the bidirectional gating circulation unit, the channel attention mechanism, the multi-scale feature extraction module and the feature fusion module. According to the invention, the accuracy of fetal heart analysis is improved.

The invention relates to the technical field of obstetrical fetal heart monitoring, in particular to an obstetrical fetal heart intelligent monitoring method and system, and the method comprises the following steps: S1, data collection: collecting fetal heart signals through wearable equipment; s2, data preprocessing: acquiring fetal heart monitoring parameters; s3, self-adaptive adjustment of the personalized physiological state: dynamically adjusting fetal heart monitoring parameters by applying a self-adaptive algorithm; s4, data analysis and prediction, wherein the adjusted fetal heart monitoring parameters are analyzed, and the health problem of the fetus is predicted; s5, dynamic multi-mode signal interaction analysis: identifying relevance among multi-mode signals, performing abnormal mode detection, and performing comprehensive evaluation; and S6, visualization and user interaction: developing a user interface based on Web and mobile applications. According to the invention, the relevance among various signals can be comprehensively captured and analyzed, the abnormal mode can be accurately identified, and the accuracy and reliability of fetal health monitoring can be improved.

Techniques for real-time doppler ultrasound signal processing techniques for fetal heart rate (FHR) detection with supervisory error control are provided. In an example, a method comprises receiving, by a system comprising a processor, signal data as the signal data is captured via an ultrasound transducer during a fetal monitoring session using doppler-based ultrasound technology. The method further comprises determining, by the system using a first process, first FHR values for a fetal heart targeted by the ultrasound transducer based on the signal data as the signal data is received, and determining using a second process in parallel with the first process, second FHR values for the fetal heart based on the signal data as the signal data is received. The method further comprises determining, by the system, whether the first FHR values are associated with an error based on differences between the first FHR values and the second FHR values.

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

The invention relates to the technical field of medical image artificial intelligence, in particular to a multi-prototype cross-modal contrast learning fetal heart ultrasound image intelligent diagnosis system which comprises the steps that a to-be-detected fetal heart ultrasound image is obtained through an obtaining module, and a processing module inputs the to-be-detected fetal heart ultrasound image into a pre-trained image diagnosis model; the method comprises the following steps: performing feature extraction on a to-be-detected fetal heart ultrasound image, performing cross-modal multi-prototype comparison according to a feature extraction result to obtain a diagnosis category and a most matched image-text prototype pair, outputting the diagnosis category and the most matched image-text prototype pair by an output module, and finally performing CHD classification and screening according to the diagnosis category and the most matched image-text prototype pair. The problem that the model generalization ability is insufficient due to the fact that a single prototype center is mainly relied on to represent each category and the significant difference of the same category under different conditions is neglected is solved, and multi-category CHD intelligent screening is achieved by utilizing unlabeled images and a small amount of text priori on the premise that a large number of graph-text pairs are not needed.

A method of treating a mother intrapartum. The method includes obtaining fetal heart rate (FHR) and uterine activity data, including contraction data, from a pregnant mother intrapartum. Contraction data for a plurality of time periods is determined. The FHR data and contraction data is analyzed, within each of the plurality of time periods, to determine occurrence of a marker selected from the markers consisting of Fetal Evaluation, Fetal Intervention, Fetal Operation, and Fetal Morbidity. A recommended intervention is provided based on the occurrence of the marker. The recommendation may be, for example, shown on a display.

A method and apparatus of examining fetal hearts includes obtaining ultrasound data of a fetal heart to generate fetal heart images, displaying different marked sample images of a fetal heart and at respective cardiac phases, each marking a different feature of a fetal heart at a respective marked location, and sequentially presenting one of the different marked sample images to a user along with one of the fetal heart images that is a similar view. As each of the different marked sample images is sequentially presented, a user is prompted to mark the different feature in a respective fetal heart image based on its marked location to create a plurality of marked fetal heart images, and a geometric model of the heart is generated based on the marked fetal heart images, from which fetal echocardiography views can be extracted. The fetal echocardiography views of the fetal heart are displayed.

The utility model discloses an FD-600 low-noise fetus-voice meter filter circuit. The FD-600 low-noise fetus-voice meter filter circuit comprises a passive band-pass filter circuit, three groups of active low-pass filter circuits, a logarithmic amplifier circuit, two groups of proportional amplifier circuits and an audio signal amplifying and shaping circuit. According to the utility model, the input audio signal is filtered and amplified for many times, so that clutter interference in the audio signal is filtered, and the signal is amplified between the filter circuits, so that the condition that the filtered signal is weak and difficult to capture and further causes distortion is avoided, noise is effectively reduced, and meanwhile, the noise is reduced. The clarity of fetal heart audio signals is improved, and medical staff can conveniently recognize and judge the audio signals detected by the fetal heart meter.

The disclosure provides a fetal congenital heart disease auxiliary judgment method and system, which comprises the following steps: collecting clinical fetal heart ultrasound standard section image construction dataset; constructing a multi-task model containing section segmentation, single-section diagnosis and section fusion evaluation, training the multi-task model based on the dataset; wherein the section fusion evaluation in the multi-task model obtains global fusion features by splicing or attention weighted fusion of the backbone network deep features of each section of the same case, and outputs the case category based on the global fusion features, each section diagnosis result, diagnosis consistency score and diagnosis complementarity judgment; collecting fetal heart ultrasound images and judging fetal congenital heart disease through the trained multi-task model. The scheme of the disclosure can improve the accuracy and reliability of fetal congenital heart disease judgment by verifying the consistency and analyzing the complementarity of the diagnosis results of different sections.

The application discloses a kind of fetal heart three-dimensional ultrasound reconstruction methods based on radio frequency identification signal, the device used includes a medical two-dimensional color ultrasound machine, two RFID passive tags, an RFID signal reader connected with three receiving antennas, and PC for RFID signal data processing and three-dimensional color ultrasound reconstruction;RFID reader transmits radio frequency signal and receives RFID passive tag reflection signal, after correcting the phase deviation of receiving signal, the distance between phase determination antenna and RFID passive tag is used, the position and elevation of RFID passive tag are estimated, the moving track of ultrasonic probe is determined, finally the position and angle information extracted by two-dimensional ultrasonic probe are input into three-dimensional ultrasound reconstruction model together with the obtained two-dimensional ultrasonic image, and accurate fetal heart three-dimensional ultrasound is obtained.The application can realize lower cost and higher accuracy, and is especially suitable for fetal heart detection.

1. The name of this design product: Fetal heart rate probe. 2. Purpose of the product of this design: The fetal heart probe is used to form a fetal Doppler with other components of the fetal Doppler to detect the fetal heart rate. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The invention provides a fetal heart rate signal classification method based on a space-time diagram convolutional network. The method comprises the following steps: acquiring and preprocessing a fetal heart rate signal; node feature attributes are extracted from the fetal heart rate signals, and an initial static graph is generated; constructing a dynamic graph based on the initial static graph and the self-adaptive adjacency matrix, updating information propagation of nodes in the dynamic graph on each time step, and generating an updated dynamic graph; and constructing an optimized space-time diagram convolutional network model, inputting the updated dynamic diagram into the optimized space-time diagram convolutional network model, and outputting a classification result of the fetal heart rate signals. According to the method, a dynamic graph mechanism is introduced, a traditional space-time graph convolutional network is optimized, space dependence and time dependence between nodes are effectively captured, cross-time-dimension information transmission is achieved, the pathological causality of FHR data is deduced, and the accuracy of FHR signal classification is improved.

The invention provides a fetal hypoxia early warning method and device combining health conditions and fetal heart rates, and is applied to the technical field of data processing. The method comprises the following steps: preprocessing a fetal heart rate signal of a target fetus to generate target fetal heart rate signal sequence information; the target fetal heart rate signal sequence information is processed on the basis of a Gaussian second wavelet function, a target wavelet transformation diagram is generated, and the target wavelet transformation diagram is used for representing time-frequency information of the fetal heart rate signal of the target fetus; processing the physiological parameter information of the pregnant woman and the PH value information of the target fetus based on a target fetal hypoxia diagnosis model to generate a target physiological state feature; processing the target wavelet transform diagram based on the target fetal hypoxia diagnosis model to generate target image features; and processing the target physiological status features and the target image features based on the target fetal hypoxia diagnosis model to generate fetal hypoxia information.

The utility model provides a parturient delivery skirt which comprises an upper garment and a skirt body, a first zipper is sewn in the middle of the front face of the upper garment, second zippers are sewn on the two sides of the upper garment, a plurality of button holes are formed in the bottom of the upper garment, buttons are sewn on the inner top of the skirt body, the skirt body is connected with the upper garment through the buttons and the button holes, and an opening is formed in the position, located at the chest, of the front face of the upper garment. The first zipper is a two-way zipper, so that the first zipper is pulled upwards to facilitate fetal heart detection of a pregnant woman, the first zipper is pulled downwards to facilitate contact between a newborn and a mother in the early stage, the newborn can be directly fed by the pregnant woman through the formed opening, and the opening can be blocked by the blocking piece, so that the pregnant woman feels comfortable. By means of the second zipper, the pregnant woman can be anesthetized without taking off the delivery clothes, during delivery, the pregnant woman can pull up the first zipper upwards or directly lift up the skirt body for delivery, the pregnant woman does not need to take off the delivery skirt, and the risk that the pregnant woman gets frozen and gets ill due to clothes taking off is reduced.

The application provides an inductive fetal heart monitor, which comprises a fetal heart monitor body and a probe, wherein the fetal heart monitor body comprises a power module, a main control module, a signal source switching module, a grounding signal module and a fetal heart output module; the main control module is connected with the signal source switching module; the grounding signal module and the fetal heart output module are both connected with the signal source switching module; the probe comprises a probe body, a sensor one and a sensor two; the probe body is connected with the signal source switching module; the sensor one and the sensor two are arranged on the probe body; and the sensor one and the sensor two are both connected with the main control module. The two sensors and the signal source switching circuit are added to the probe, the signal source switching circuit is controlled by an MCU, the two signal sources of the signal source switching circuit, i.e. the fetal heart signal or the grounding signal, are switched and output, and the two sensors are used to solve the problems of reading and loud noise during the fetal heart searching process when the fetal heart monitor is not used correctly.

The invention discloses a double-fetal monitoring method based on abdominal electric signal state dynamic conversion analysis, which comprises the following steps of: acquiring abdominal electric signal data of a double-fetal pregnant woman containing all age groups and physical conditions in a clinical environment, and constructing a double-fetal monitoring reference data set through preprocessing and signal separation; and designing an abdominal electric signal state dynamic conversion analysis algorithm suitable for double-fetal monitoring. And constructing a state dynamic conversion template of the source signal in state dynamic conversion analysis, and generating a double-tire position marking data set. And obtaining state labeling time sequence data of state dynamic conversion based on the state dynamic conversion template, constructing a double-fetal electrocardiosignal extraction scheme, and calculating the fetal heart rate. And visualizing a state dynamic conversion time sequence chart and marking real-time fetal heart rate and mother heart rate to realize dynamic monitoring of the state of the double fetuses. According to the invention, the limitation that the fetal heart signals are confused and the independent electrocardiosignals of the two fetuses are difficult to accurately extract during the existing monitoring of the two fetuses is solved, and the real-time performance and the reliability of the clinical monitoring of the two fetuses are improved.

A mechanism for automatically generating and ranking M-mode lines for generating or defining M-mode data usable to assess fetal heart activity, e.g. determine a fetal heart rate. A region of interest, containing a fetal heart, in a sequence of ultrasound images is identified. The region of interest is used to define the position of each of a plurality of M-mode lines, e.g. anatomical M-mode lines. A quality measure of each M-mode line is determined based on M-mode data generated for each M-mode line, and the quality measures are then used to rank the M-mode lines.

The invention relates to the technical field of fetal heart detection, and particularly discloses an antenatal fetal heart detection method and system for simulation teaching. The method comprises the following steps of: establishing a movement track model comprising a plurality of nodes through a preset standard curve, discretizing student operation into simulated fetal heart searching nodes, and jumping walking to generate a first weight through a node matching detection step; secondly, when a preset frequency signal is detected, recording timestamps of a simulation capture area and a final detection point, judging the positioning efficiency through duration analysis, and if the positioning efficiency exceeds a preset range, generating a second weight; and finally, combining the basic proficiency score and the dual weight to comprehensively calculate a detection result. According to the method, visual tracking of operation steps is achieved through node discretization, a step integrity and operation timeliness dual verification mechanism (identifying leapfrogging violation and positioning time consumption abnormity) is utilized, operation normalization is quantitatively evaluated in combination with timestamp data, and the operation proficiency of a user can be comprehensively, objectively and accurately evaluated.

The utility model relates to the technical field of fetus-voice meters, in particular to a fetus-voice meter with a disinfection function, which comprises a fetus-voice meter main body, a support seat is fixedly connected to the bottom of the rear side of the fetus-voice meter main body, a disinfection tank is arranged on one side of the support seat, and a liquid storage bin is arranged on the other side of the support seat. A liquid supplementing opening is formed between the disinfection tank and the liquid storage bin, a connecting electric wire is fixedly connected to the top of the fetus-voice meter body, and a fetal heart probe is fixedly connected to one end of the connecting electric wire. The fetal heart probe disinfection device has the advantages that when a fetal heart probe needs to be disinfected, the fetal heart probe is inserted into the disinfection groove, the sealing plate is pressed downwards, the sealing plate and the liquid supplementing opening are staggered, disinfection alcohol enters the disinfection groove from the liquid storage bin to disinfect the end of the fetal heart probe, and therefore disinfection is completed; according to the disinfection structure, disinfection alcohol can be supplemented at any time according to needs, the flow of the disinfection alcohol can be controlled by controlling the pressing duration according to needs, and disinfection is more convenient and faster.

The invention provides a fetal heart monitoring probe detection device which comprises a base, stand columns are fixedly connected to the four ends of the upper portion of the base, a top plate is fixedly connected to the tops of the stand columns, a movable frame is movably connected to the stand columns, a rack is fixedly connected to one end of the outer side of the movable frame, and a fixed frame is fixedly connected to one end of the bottom of the base. The top of the fixing frame is fixedly connected with a third motor, and the output end of the third motor penetrates outwards and is fixedly connected with a third gear. The clamping assembly is arranged on the movable frame so that fetal heart monitoring probes of different sizes can be positioned and clamped, and follow-up detection work can be conveniently carried out; and a plurality of groups of detection assemblies are arranged at the outer end of the base and comprise sound wave detection, pressure detection and appearance detection, so that the fetal heart monitoring probe is detected from multiple aspects, and an authoritative, comprehensive and accurate detection result is achieved.

The utility model discloses an integrated fetal heart monitor which comprises a rod-shaped shell, a main board, a loudspeaker, an ultrasonic probe, a battery, a control key, a key cap and a display screen, wherein the main board, the loudspeaker, the ultrasonic probe and the battery are respectively arranged in the rod-shaped shell; the control key is arranged on the main board; the key cap and the display screen are arranged on the surface of the rod-shaped shell; the mainboard is electrically connected with the loudspeaker, the ultrasonic probe, the battery and the display screen respectively; the key cap is connected with the control key in an abutting mode. The rod-shaped shell comprises a probe shell, a surface shell and a bottom shell, the surface shell and the bottom shell are respectively connected with the probe shell, and the surface shell is connected with the bottom shell; the ultrasonic probe is arranged behind the probe shell, and the probe shell is arranged at one end of the rod-shaped shell. The main board, the loudspeaker, the ultrasonic probe, the battery and the display screen are integrated in the rod-shaped shell, so that the integrated fetal heart monitor is obtained, the fetal heart monitor is greatly convenient to carry, and a pregnant woman can conveniently monitor the fetal heart of a fetus at any time.

The invention provides a noise optimization processing method for fetal heart signals, which relates to the technical field of signal processing, and comprises the following steps: performing dual-channel acquisition on maternal electrocardiosignals and fetal electrocardiosignals to obtain a maternal electrocardiosignal sequence and a fetal electrocardiosignal sequence, and acquiring maternal feature information of a maternal; according to the multiple pieces of feature information, maternal electrocardio noise prediction is carried out, and multiple maternal electrocardio noise sequences are obtained; collecting a moving image sequence of a parent, and performing myoelectricity noise signal prediction according to the multiple pieces of feature information to obtain multiple parent myoelectricity noise sequences; noise optimization processing is conducted on the fetal electrocardiosignal sequence to obtain an optimal noise-filtered fetal electrocardiosignal sequence, random noise filtering is conducted on the fetal electrocardiosignal sequence, the similarity between the noise signal sequence and the multiple maternal electrocardio noise sequences and the similarity between the noise signal sequence and the multiple maternal electromyogram noise sequences are calculated, and optimization is conducted. The technical problem that in the prior art, the fetal heart signal noise processing effect is poor is solved.