Intelligent fetal heart monitoring method and system for obstetrical department

Abstract

The invention discloses an intelligent fetal heart monitoring method and system for the obstetrical department, and relates to the technical field of medical monitoring. A multi-modal sensing monitoring unit, an intelligent data processing technology, a remote data analysis platform and an intelligent equipment application program are integrated. According to the system, fetal heart data are comprehensively collected through fetal heart sound, vibration, temperature and other multi-dimensional sensors, the data are cleaned, compressed, encrypted and processed through an intelligent algorithm, and the accuracy and safety of the data are ensured. And the remote data analysis platform analyzes the fetal heart data in real time and provides personalized medical suggestions. The intelligent device application program provides convenient user interaction and supports custom monitoring plan and data cloud synchronization. On the whole, comprehensiveness, accuracy and real-time performance of fetal heart monitoring are achieved, efficiency and safety of maternal and infant health monitoring are improved, and a powerful health guarantee tool is provided for medical staff and pregnant women.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical monitoring, and in particular relates to an intelligent fetal heart monitoring method and system for obstetrics. Background Art

[0002] In existing obstetric medical practice, fetal heart monitoring is one of the important means to assess the health status of the fetus. Traditional fetal heart monitoring methods mainly rely on doctors to manually operate stethoscopes or fetal heart monitors. This method has problems such as low monitoring frequency, insufficient data accuracy, and inability to provide real-time feedback. In addition, although some existing fetal heart monitoring devices have achieved automated monitoring, they often only use a single sensor, which makes it difficult to fully capture fetal heart information, and the data processing and transmission methods are relatively simple. Traditional fetal heart monitoring equipment mostly uses wired connections, which limits the range of activities of pregnant women, and is easily disturbed during data transmission, resulting in poor real-time data and unable to meet the needs of modern obstetric medical care for efficient, accurate, and personalized monitoring.

[0003] In addition, in recent years, with the rapid development of the Internet of Things, big data and artificial intelligence technologies, smart medical monitoring equipment has gradually entered the market. However, most of the fetal heart monitoring equipment on the market currently has the following shortcomings: First, the sensor types are single and the monitoring data is not comprehensive enough; second, the data processing technology is not advanced enough, and it is difficult to effectively remove noise and abnormal values, resulting in inaccurate monitoring results; third, the data transmission and storage methods are not secure enough, and there is a risk of data leakage; fourth, there is a lack of personalized medical advice functions, which cannot meet the personalized needs of pregnant women. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent fetal heart monitoring method and system for obstetrics, which can realize comprehensive, real-time and accurate monitoring of fetal heart data of pregnant women and provide personalized medical advice by integrating a multimodal sensor monitoring unit, intelligent data processing technology and a remote data analysis platform.

[0005] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0006] The present invention is an intelligent fetal heart monitoring method for obstetrics, comprising the following steps:

[0007] S1: deploy and use a multimodal sensor monitoring unit to collect fetal heart rate data of pregnant women in real time;

[0008] S2: transmitting the collected fetal heart data to a smart phone or other smart device via wireless communication technology;

[0009] S3: Use an efficient data cleaning algorithm to remove noise and outliers, then use data compression technology to reduce the amount of data transmission, and use the AES-256 bit encryption algorithm to encrypt the data;

[0010] S4: The smart device transmits the processed fetal heart data to the remote data analysis platform through a stable network connection;

[0011] S5: The remote data analysis platform performs real-time analysis on the received fetal heart data, transmits the analysis results to the smart device, and generates an alarm message when an abnormality is found;

[0012] S6: The alarm information is notified to pregnant women and / or medical staff through smart devices, and real-time data, historical records and personalized medical advice of fetal heart monitoring are provided.

[0013] As a preferred technical solution of the present invention, the following measures are also included:

[0014] Adaptive calibration of the multimodal sensor monitoring unit to accommodate changes in the body shape and fetal heart position of different pregnant women;

[0015] Visualize fetal heart data in smart devices, including waveforms, heart rate values ​​and trend graphs, so that users can understand the monitoring results more intuitively;

[0016] The remote data analysis platform integrates machine learning algorithms that can self-optimize based on historical data and user feedback, improving the accuracy of analysis and the applicability of personalized recommendations;

[0017] Realize the remote control function of smart devices, allowing medical staff to remotely access monitoring data and adjust monitoring parameters.

[0018] As a preferred technical solution of the present invention, the smart phone or smart device has an application installed therein, and the application installed in the smart device has the following user interaction functions:

[0019] Customized monitoring plan, allowing users to set monitoring time, frequency and alarm threshold according to needs;

[0020] Data cloud synchronization, automatically upload monitoring data to the cloud, and support data synchronization between multiple devices;

[0021] Data analysis report: regularly generate fetal heart monitoring reports, including data analysis charts, health advice and trend forecasts;

[0022] The intuitive user interface displays real-time data, historical trend charts and abnormal alarms of fetal heart monitoring, and supports sliding, zooming and touch operations.

[0023] As a preferred technical solution of the present invention, the remote data analysis platform uses an artificial intelligence algorithm to build an intelligent analysis model to perform in-depth analysis of fetal heart data, evaluate the changing trend of fetal health status, and generate personalized medical advice. The artificial intelligence algorithm used is a wavelet analysis algorithm.

[0024] As a preferred technical solution of the present invention, the steps of building the intelligent analysis model include:

[0025] Signal acquisition: Real-time fetal heart Doppler signals are collected through wireless fetal heart monitoring sensors;

[0026] Signal preprocessing: Perform low-pass filtering, absolute value calculation and envelope extraction preprocessing on the collected multi-source signals to filter out high-frequency noise and interference;

[0027] Wavelet decomposition: Select appropriate wavelet basis and decomposition level to perform wavelet decomposition on the preprocessed signal;

[0028] Threshold processing: threshold quantization is performed on the decomposed high-frequency coefficients to suppress noise;

[0029] Wavelet reconstruction: wavelet reconstruction is performed based on the processed high-frequency coefficients and low-frequency coefficients to obtain the denoised fetal heart signal;

[0030] Fetal heart rate calculation: Calculate the fetal heartbeat cycle through low-frequency signals to obtain the fetal heart rate.

[0031] An intelligent fetal heart monitoring system for obstetrics used to implement the above method comprises:

[0032] Multimodal sensor monitoring unit: contains multiple wireless fetal heart monitoring sensors, which are used to collect fetal heart data of pregnant women in real time;

[0033] At least one smart device, as a relay station for data transmission, receives fetal heart data from a fetal heart monitoring sensor, performs preliminary processing on the data and sends it to a remote data analysis platform via a stable network connection, and provides a user interface for users to view the fetal heart monitoring information;

[0034] The remote data analysis platform is used to receive fetal heart data from smart devices, perform real-time analysis and processing, generate alarm information, and provide real-time data, historical records and personalized medical advice for fetal heart monitoring.

[0035] As a preferred technical solution of the present invention, the multimodal sensing monitoring unit includes:

[0036] Four main wireless fetal heart monitoring sensors are designed to fit different positions of the pregnant woman's abdomen, including sensors on the top, bottom and sides. Each sensor is integrated with a fetal heart sound collector, fetal heart vibration sensor and temperature sensor to capture fetal heart information in multiple dimensions.

[0037] A secondary wireless fetal heart monitoring sensor, designed as a lightweight belt, is equipped with a low-power fetal heart sound collector and vibration sensor for daily auxiliary monitoring. It also has an automatic wake-up function and can monitor according to preset time intervals or the activity status of the pregnant woman.

[0038] As a preferred technical solution of the present invention, the main wireless fetal heart monitoring sensor includes a suction cup in contact with the skin and a sensor body mounted on the suction cup, the suction cup is a flexible suction cup, and a medical-grade adhesive is provided on the circumference of the suction cup.

[0039] As a preferred technical solution of the present invention, the secondary wireless fetal heart monitoring sensor includes a waist belt and a sensor body mounted on the waist belt.

[0040] As a preferred technical solution of the present invention, a data security protection mechanism is also included to ensure the security of fetal heart monitoring data during transmission, storage and processing;

[0041] The data security protection mechanism adopts the following measures:

[0042] During the transmission of data between smart devices and remote data analysis platforms, TLS / SSL protocol is used for encryption to ensure the security of data transmission;

[0043] The remote data analysis platform uses firewalls, intrusion detection systems and data backup and recovery mechanisms to ensure the security of data storage and processing;

[0044] Users can set data access permissions through smart devices to control which data can be viewed or shared by which people.

[0045] The present invention has the following beneficial effects:

[0046] The present invention realizes comprehensive, accurate and real-time monitoring of fetal heart rate data of pregnant women through multimodal sensor monitoring, intelligent data processing and remote real-time analysis, and provides personalized medical advice. The system has the advantages of comprehensive, accurate, safe and personalized data, which can significantly improve the monitoring efficiency and accuracy, provide more timely and effective health information for medical staff and pregnant women, and help protect the health of mothers and babies.

[0047] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0049] Figure 1 It is a flow chart of an intelligent fetal heart monitoring method for obstetrics in the present invention;

[0050] Figure 2 The steps for building the intelligent analysis model in the present invention;

[0051] Figure 3 It is a schematic diagram of the monitoring system mentioned in the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Embodiment 1

[0054] like Figure 1 As shown: The present invention provides an intelligent fetal heart monitoring method for obstetrics, comprising the following steps: S1: deploying and using a multimodal sensor monitoring unit to collect fetal heart data of pregnant women in real time; S2: transmitting the collected fetal heart data to a smart phone or other smart devices through wireless communication technology; S3: using an efficient data cleaning algorithm to remove noise and outliers, then reducing the data transmission volume through data compression technology, and using an AES-256-bit encryption algorithm to encrypt the data; S4: the smart device transmits the processed fetal heart data to a remote data analysis platform through a stable network connection; S5: the remote data analysis platform performs real-time analysis on the received fetal heart data, transmits the analysis results to the smart device, and generates an alarm message when an abnormality is found; S6: notifying the pregnant woman and / or medical staff of the alarm message through the smart device, and providing real-time data, historical records and personalized medical advice for fetal heart monitoring.

[0055] This implementation provides a detailed description of the above method, which integrates modern sensor technology, wireless communication, data processing and encryption, and remote data analysis and feedback, aiming to provide efficient, safe, and real-time fetal heart monitoring services. The following is a further analysis of each step:

[0056] S1: deploy and use a multimodal sensor monitoring unit to collect fetal heart rate data of pregnant women in real time;

[0057] Multimodal sensor monitoring unit: This unit integrates multiple sensors to capture fetal heart signals comprehensively and accurately. These sensors collect fetal heart data in real time through non-invasive methods (such as placement on the abdomen of pregnant women). Real-time collection: ensures the freshness and accuracy of data, providing a reliable basis for subsequent monitoring and analysis.

[0058] S2: transmitting the collected fetal heart data to a smart phone or other smart device via wireless communication technology;

[0059] The wireless communication technology in this step is: using wireless communication technologies such as Bluetooth, Wi-Fi, LoRa, NB-I oT, etc. to achieve fast and stable transmission of fetal heart data from the monitoring unit to the smart device.

[0060] Smartphone or other smart device: As a terminal for data reception and preliminary processing, it is portable and easy to use, allowing pregnant women to monitor fetal heart rate anytime and anywhere.

[0061] S3: data processing and encryption;

[0062] Specific measures include the following: Data cleaning: Use efficient data cleaning algorithms, such as filtering, denoising, and outlier detection, to improve data accuracy and reliability. Data compression: Use data compression technology to reduce data transmission volume, reduce network bandwidth requirements, and improve transmission efficiency. Data encryption: Use the AES-256-bit encryption algorithm to encrypt data to ensure data security during transmission and storage, and prevent data leakage and illegal access.

[0063] S4: The smart device transmits the processed fetal heart data to the remote data analysis platform;

[0064] The specific implementation requirements are as follows: Stable network connection: ensure stable and reliable data transmission between smart devices and remote data analysis platform. Remote data analysis platform: possess powerful data processing and analysis capabilities, and be able to receive, process and analyze fetal heart data in real time.

[0065] S5: The remote data analysis platform performs real-time analysis of fetal heart data and generates alarm information

[0066] Real-time analysis: Use advanced algorithms and models to analyze fetal heart data in real time to identify abnormal fetal heart conditions. Alarm information: Once an abnormal fetal heart rate is detected, an alarm message is immediately generated to notify relevant personnel in a timely manner.

[0067] S6: The alarm information is notified to pregnant women and / or medical staff through smart devices, and real-time data, historical records and personalized medical advice of fetal heart monitoring are provided.

[0068] This step mainly involves: Notification mechanism: the smart device notifies the pregnant woman and / or medical staff of the alarm information through sound, vibration, screen display, etc.; Real-time data and historical records: providing real-time data and historical records of fetal heart monitoring to help pregnant women and medical staff fully understand the fetal heart condition; Personalized medical advice: providing personalized medical advice and guidance based on the fetal heart monitoring results and the pregnant woman's personal situation.

[0069] In summary, the intelligent fetal heart monitoring method for obstetrics provided in this embodiment realizes the intelligence, real-time and safety of fetal heart monitoring through the close cooperation of multimodal sensor monitoring, wireless transmission, data processing and encryption, remote analysis and feedback, etc., and provides convenient and efficient fetal heart monitoring services for pregnant women and medical staff.

[0070] Embodiment 2

[0071] Based on the first embodiment, the difference of this embodiment is that it also includes the following measures:

[0072] Adaptive calibration of the multimodal sensor monitoring unit to accommodate changes in the body shape and fetal heart position of different pregnant women;

[0073] Visualize fetal heart data in smart devices, including waveforms, heart rate values ​​and trend graphs, so that users can understand the monitoring results more intuitively;

[0074] The remote data analysis platform integrates machine learning algorithms that can self-optimize based on historical data and user feedback, improving the accuracy of analysis and the applicability of personalized recommendations;

[0075] Realize the remote control function of smart devices, allowing medical staff to remotely access monitoring data and adjust monitoring parameters.

[0076] Based on the first embodiment, this embodiment further enhances the functionality and user experience of the fetal heart rate intelligent monitoring system, and introduces functions such as adaptive calibration, data visualization, machine learning algorithm optimization, and remote control, making the entire monitoring process more accurate, intuitive, and flexible. The following is a detailed analysis of each new measure:

[0077] Adaptive calibration of multimodal sensor monitoring units

[0078] Adaptive calibration: Considering the differences in body shape of different pregnant women and the dynamic changes in the position of the fetal heart, this embodiment introduces an adaptive calibration mechanism. This mechanism can automatically adjust the parameters and position of the sensor monitoring unit according to the real-time changes in the body shape characteristics of the pregnant woman and the position of the fetal heart to ensure accurate collection of fetal heart data. This helps to improve the reliability and accuracy of the monitoring results.

[0079] Visualize fetal heart rate data on smart devices

[0080] Data visualization: Smart devices not only serve as data transmission terminals, but also integrate data visualization functions. By displaying fetal heart data in various forms such as waveforms, heart rate values ​​and trend graphs, users can intuitively understand the changing trend and current status of the fetal heart rate. This intuitive display method helps users better understand the monitoring results and discover abnormal situations in a timely manner.

[0081] Remote data analysis platform integrates machine learning algorithms

[0082] Machine learning algorithms: The remote data analysis platform integrates advanced machine learning algorithms that can self-optimize based on historical monitoring data and user feedback. Through continuous learning and iteration, the algorithm can more accurately identify abnormal fetal heart patterns, improve the accuracy of analysis and the applicability of personalized recommendations. This intelligent processing method helps to provide more accurate and personalized medical services for pregnant women.

[0083] Realize remote control function of smart devices

[0084] Remote control: In order to facilitate remote management and guidance of medical staff, this embodiment implements the remote control function of smart devices. Medical staff can view the fetal heart monitoring data of pregnant women through remote access, and adjust monitoring parameters or give guidance suggestions as needed. This remote control method helps to strengthen communication and collaboration between medical staff and pregnant women, and improve the efficiency and quality of medical services.

[0085] In summary, this embodiment further improves the performance and user experience of the fetal heart rate intelligent monitoring system by introducing functions such as adaptive calibration, data visualization, machine learning algorithm optimization, and remote control. These measures not only improve the accuracy and reliability of the monitoring results, but also enhance the system's intelligent and personalized service capabilities, providing pregnant women and medical staff with more convenient, efficient, and accurate fetal heart rate monitoring services.

[0086] Embodiment 3

[0087] Based on the first embodiment, the difference of this embodiment is that: an application is installed in the smart phone or smart device, and the application installed in the smart device has the following user interaction functions:

[0088] Customized monitoring plans allow users to set monitoring time, frequency and alarm thresholds according to their needs; data cloud synchronization automatically uploads monitoring data to the cloud and supports data synchronization between multiple devices; data analysis reports regularly generate fetal heart monitoring reports, including data analysis charts, health advice and trend forecasts; intuitive user interface displays real-time data, historical trend charts and abnormal alarms of fetal heart monitoring, and supports sliding, zooming and touch operations.

[0089] Based on the first embodiment, this embodiment significantly enhances the user interaction function and experience through the application installed in the smart phone or smart device. The following is a detailed analysis of the newly added user interaction function:

[0090] Customized monitoring plan; Monitoring plan settings: The application allows users to flexibly set the time, frequency and alarm threshold of fetal heart monitoring according to their own needs. This personalized setting not only meets the monitoring needs of different pregnant women, but also improves the pertinence and effectiveness of monitoring.

[0091] Flexibility: Users can adjust the monitoring plan at any time to adapt to changes in different stages of pregnancy or special circumstances.

[0092] Data cloud synchronization; automatic upload: The application has a data cloud synchronization function, which can automatically upload monitoring data to the cloud server. This not only ensures the security and reliability of the data, but also makes it easier for users to seamlessly switch and view data between different devices.

[0093] Multi-device synchronization: supports data synchronization between multiple devices. Users can view and manage fetal heart monitoring data on multiple devices such as mobile phones, tablets or computers, which improves the convenience of use.

[0094] Data analysis report; regular generation: The application can generate fetal heart monitoring reports regularly (such as daily, weekly or monthly). These reports not only contain detailed data analysis charts, but also provide health advice and trend forecasts to help users better understand the status of the fetal heart.

[0095] Rich information: The report is comprehensive, including real-time analysis of current fetal heart data and trend analysis of historical data, providing users with a comprehensive health reference.

[0096] Intuitive user interface; real-time data display: The user interface is clear and intuitive, and can display the current data of fetal heart monitoring in real time, such as heart rate value, waveform, etc.

[0097] Historical trend chart: Provides historical trend chart function, users can view the historical change trend of fetal heart data and understand the fluctuation of fetal heart rate in different time periods.

[0098] Abnormal alarm: Once an abnormality is detected during the monitoring process, the application will immediately issue an alarm through sound, vibration or screen prompts to alert the user.

[0099] Touch operation: supports multiple operation modes such as sliding, zooming and touching. Users can view and manage fetal heart monitoring data through simple operations, which improves the convenience and interactivity of use.

[0100] In summary, this embodiment provides users with rich user interaction functions and intuitive operation interfaces through applications installed in smart phones or smart devices. These functions not only enhance the personalized settings and data analysis capabilities of fetal heart monitoring, but also improve the user experience and satisfaction.

[0101] Embodiment 4

[0102] Based on the first embodiment, the difference of this embodiment is that:

[0103] like Figure 2 As shown: The remote data analysis platform uses artificial intelligence algorithms to build intelligent analysis models to conduct in-depth analysis of fetal heart data, evaluate the changing trends of fetal health status, and generate personalized medical recommendations. The artificial intelligence algorithm used is the wavelet analysis algorithm.

[0104] The steps for building the intelligent analysis model include: signal acquisition: real-time fetal heart Doppler signals are collected through wireless fetal heart monitoring sensors; signal preprocessing: low-pass filtering, absolute value operation and envelope extraction preprocessing are performed on the collected multi-source signals to filter out high-frequency noise and interference; wavelet decomposition: selecting a suitable wavelet basis and decomposition layer number, and performing wavelet decomposition on the preprocessed signal; threshold processing: threshold quantization processing is performed on the decomposed high-frequency coefficients to suppress noise; wavelet reconstruction: wavelet reconstruction is performed based on the processed high-frequency coefficients and low-frequency coefficients to obtain the denoised fetal heart signal; fetal heart rate calculation: the fetal heartbeat cycle is calculated through the low-frequency signal to obtain the fetal heart rate.

[0105] In this embodiment, by introducing a remote data analysis platform and artificial intelligence algorithms, the intelligence level of fetal heart monitoring and the quality of personalized medical services are significantly improved, and artificial intelligence algorithms are used to conduct in-depth analysis of fetal heart data to assess the changing trend of fetal health status. This intelligent analysis can detect subtle changes that are difficult to detect with traditional methods, providing doctors with a more comprehensive and accurate basis for diagnosis.

[0106] like Figure 3 As shown: In order to implement the above method, the present invention also provides an intelligent fetal heart monitoring system for obstetrics, including: a multimodal sensing monitoring unit: comprising multiple wireless fetal heart monitoring sensors, used to collect fetal heart data of pregnant women in real time; at least one intelligent device, as a relay station for data transmission, receiving fetal heart data from the fetal heart monitoring sensor, and sending the data to a remote data analysis platform through a stable network connection after preliminary processing, and providing a user interface for users to view fetal heart monitoring information; the remote data analysis platform is used to receive fetal heart data from the intelligent device, perform real-time analysis and processing, generate alarm information, and provide real-time data, historical records and personalized medical advice for fetal heart monitoring.

[0107] The multimodal sensing monitoring unit includes: four main wireless fetal heart monitoring sensors, which are designed to fit the shape of different positions of the pregnant woman's abdomen, including sensors on the top, bottom and sides. Each sensor is integrated with a fetal heart sound collector, a fetal heart vibration sensor and a temperature sensor to capture fetal heart information in multiple dimensions; a secondary wireless fetal heart monitoring sensor, designed as a lightweight belt-type, with a low-power fetal heart sound collector and a vibration sensor integrated inside, which is used for daily auxiliary monitoring and has an automatic wake-up function. It can monitor according to preset time intervals or the activity status of pregnant women. The main wireless fetal heart monitoring sensor includes a suction cup in contact with the skin and a sensor body mounted on the suction cup. The suction cup is a flexible suction cup, and a medical-grade adhesive is provided on the surrounding side of the suction cup. The secondary wireless fetal heart monitoring sensor includes a belt and a sensor body mounted on the belt. It also includes a data security protection mechanism to ensure the security of fetal heart monitoring data during transmission, storage and processing; the data security protection mechanism adopts the following measures:

[0108] During the transmission process between smart devices and remote data analysis platforms, data is encrypted using the TLS / SSL protocol to ensure the security of data transmission; the remote data analysis platform uses firewalls, intrusion detection systems and data backup and recovery mechanisms to ensure the security of data storage and processing; users can set data access permissions through smart devices to control which data can be viewed or shared by which people.

[0109] In this embodiment, the system integrates a multimodal sensor monitoring unit, intelligent devices, and a remote data analysis platform. Through a highly coordinated workflow, it provides accurate and real-time fetal heart monitoring services to pregnant women and generates personalized medical advice.

[0110] The specific system composition is as follows:

[0111] Multimodal sensor monitoring unit:

[0112] Four main wireless fetal heart monitoring sensors: These sensors are carefully designed to fit different positions of the pregnant woman's abdomen (above, below and on both sides) to ensure that the fetal heart information can be fully captured. Each sensor integrates a fetal heart sound collector, a fetal heart vibration sensor and a temperature sensor to collect fetal heart data from multiple dimensions to improve the accuracy and reliability of monitoring.

[0113] Suction cup design: The main sensor uses a flexible suction cup to contact the skin, and medical-grade adhesive is provided around the suction cup to ensure that the sensor can fit firmly on the pregnant woman's abdomen while reducing irritation and discomfort to the skin.

[0114] A secondary wireless fetal heart monitoring sensor: designed as a lightweight belt-type, easy to wear daily. The sensor integrates a low-power fetal heart sound collector and vibration sensor, has an automatic wake-up function, and can automatically monitor according to the preset time interval or the activity status of the pregnant woman, effectively extending battery life and reducing unnecessary interference.

[0115] Smart devices:

[0116] As a relay station for data transmission, the smart device is responsible for receiving fetal heart data from the multimodal sensor monitoring unit.

[0117] Perform preliminary data processing, such as data compression and encryption, to ensure the security and integrity of data during transmission.

[0118] The processed data is sent to a remote data analysis platform via a stable network connection (such as Wi-Fi, Bluetooth or cellular network).

[0119] Provides an intuitive user interface for users to view real-time data and history of fetal heart monitoring and receive alarm information.

[0120] Remote data analysis platform:

[0121] Receive fetal heart data from smart devices and use advanced artificial intelligence algorithms for real-time analysis and processing.

[0122] Assess the changing trends of fetal health status, detect abnormal conditions in a timely manner and generate alarm information.

[0123] Provides real-time data, historical records and personalized medical advice on fetal heart rate monitoring to help medical staff and pregnant women better understand the condition of the fetus and develop scientific and reasonable health management plans.

[0124] System Advantages

[0125] Multi-dimensional monitoring: Through the multi-modal sensor monitoring unit, comprehensive capture of multi-dimensional information such as fetal heart sound, vibration and temperature can be achieved to improve the accuracy and reliability of monitoring.

[0126] Personalized settings: Smart devices support customized monitoring plans, allowing users to set monitoring time, frequency and alarm thresholds according to needs to meet the personalized needs of different pregnant women.

[0127] Remote analysis and management: The remote data analysis platform uses artificial intelligence algorithms to conduct in-depth analysis and provide personalized medical advice. It also supports medical staff to remotely access monitoring data and adjust monitoring parameters to improve the efficiency and quality of medical services.

[0128] User-friendly interface: Smart devices provide an intuitive user interface that supports sliding, zooming and touch operations, making it easy for users to view fetal heart monitoring information and receive alarm information.

[0129] In summary, the intelligent fetal heart rate monitoring system for obstetrics provided by the present invention provides comprehensive and accurate monitoring services for the health of pregnant women and fetuses through highly integrated hardware equipment and advanced data analysis technology, and is an important innovation in the field of modern obstetric medicine.

[0130] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0131] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent fetal heart monitoring method for obstetrics, characterized in that: The following steps are involved: S1: deploy and use a multimodal sensor monitoring unit to collect fetal heart rate data of pregnant women in real time; S2: transmitting the collected fetal heart data to a smart phone or other smart device via wireless communication technology; S3: Use an efficient data cleaning algorithm to remove noise and outliers, then use data compression technology to reduce the amount of data transmission, and use the AES-256 bit encryption algorithm to encrypt the data; S4: The smart device transmits the processed fetal heart data to the remote data analysis platform through a stable network connection; S5: The remote data analysis platform performs real-time analysis on the received fetal heart data, transmits the analysis results to the smart device, and generates an alarm message when an abnormality is found; S6: The alarm information is notified to pregnant women and / or medical staff through smart devices, and real-time data, historical records and personalized medical advice of fetal heart monitoring are provided.

2. The method for intelligent monitoring of fetal heart rate in obstetrics according to claim 1, characterized in that: It also includes the following measures: Adaptive calibration of the multimodal sensor monitoring unit to accommodate changes in the body shape and fetal heart position of different pregnant women; Visualize fetal heart data in smart devices, including waveforms, heart rate values ​​and trend graphs, so that users can understand the monitoring results more intuitively; The remote data analysis platform integrates machine learning algorithms that can self-optimize based on historical data and user feedback, improving the accuracy of analysis and the applicability of personalized recommendations; Realize the remote control function of smart devices, allowing medical staff to remotely access monitoring data and adjust monitoring parameters.

3. The method for intelligent monitoring of fetal heart rate in obstetrics according to claim 1, characterized in that: The smartphone or smart device has an application installed therein, and the application installed in the smart device has the following user interaction functions: Customized monitoring plan, allowing users to set monitoring time, frequency and alarm threshold according to needs; Data cloud synchronization, automatically upload monitoring data to the cloud, and support data synchronization between multiple devices; Data analysis report: regularly generate fetal heart monitoring reports, including data analysis charts, health advice and trend forecasts; The intuitive user interface displays real-time data, historical trend charts and abnormal alarms of fetal heart monitoring, and supports sliding, zooming and touch operations.

4. The method for intelligent monitoring of fetal heart rate in obstetrics according to claim 1, characterized in that: The remote data analysis platform uses an artificial intelligence algorithm to build an intelligent analysis model to conduct in-depth analysis of fetal heart data, evaluate the changing trend of fetal health status, and generate personalized medical advice. The artificial intelligence algorithm used is a wavelet analysis algorithm.

5. The method for intelligent monitoring of fetal heart rate in obstetrics according to claim 4, characterized in that: The steps of building the intelligent analysis model include: Signal acquisition: Real-time fetal heart Doppler signals are collected through wireless fetal heart monitoring sensors; Signal preprocessing: Perform low-pass filtering, absolute value calculation and envelope extraction preprocessing on the collected multi-source signals to filter out high-frequency noise and interference; Wavelet decomposition: Select appropriate wavelet basis and decomposition level to perform wavelet decomposition on the preprocessed signal; Threshold processing: threshold quantization processing is performed on the decomposed high-frequency coefficients to suppress noise; Wavelet reconstruction: wavelet reconstruction is performed based on the processed high-frequency coefficients and low-frequency coefficients to obtain the denoised fetal heart signal; Fetal heart rate calculation: Calculate the fetal heartbeat cycle through low-frequency signals to obtain the fetal heart rate.

6. An intelligent fetal heart monitoring system for obstetrics, used to implement the intelligent fetal heart monitoring method for obstetrics described in any one of 1-5 above, characterized in that: include: Multimodal sensor monitoring unit: contains multiple wireless fetal heart monitoring sensors, which are used to collect fetal heart data of pregnant women in real time; At least one smart device, as a relay station for data transmission, receives fetal heart data from a fetal heart monitoring sensor, performs preliminary processing on the data and sends it to a remote data analysis platform via a stable network connection, and provides a user interface for users to view the fetal heart monitoring information; The remote data analysis platform is used to receive fetal heart data from smart devices, perform real-time analysis and processing, generate alarm information, and provide real-time data, historical records and personalized medical advice for fetal heart monitoring.

7. The intelligent fetal heart rate monitoring system for obstetrics according to claim 6, characterized in that: The multimodal sensor monitoring unit includes: Four main wireless fetal heart monitoring sensors are designed to fit different positions of the pregnant woman's abdomen, including sensors on the top, bottom and sides. Each sensor is integrated with a fetal heart sound collector, fetal heart vibration sensor and temperature sensor to capture fetal heart information in multiple dimensions. A secondary wireless fetal heart monitoring sensor, designed as a lightweight belt, is equipped with a low-power fetal heart sound collector and vibration sensor for daily auxiliary monitoring. It also has an automatic wake-up function and can monitor according to preset time intervals or the activity status of the pregnant woman.

8. The intelligent fetal heart monitoring system for obstetrics according to claim 7, characterized in that: The main wireless fetal heart monitoring sensor comprises a suction cup in contact with the skin and a sensor body mounted on the suction cup. The suction cup is a flexible suction cup, and a medical-grade adhesive is arranged on the circumference of the suction cup.

9. The intelligent fetal heart rate monitoring system for obstetrics according to claim 7, characterized in that: The secondary wireless fetal heart rate monitoring sensor comprises a waist belt and a sensor body mounted on the waist belt.

10. The intelligent fetal heart monitoring system for obstetrics according to claim 6, characterized in that: It also includes a data security protection mechanism to ensure the security of fetal heart monitoring data during transmission, storage and processing; The data security protection mechanism adopts the following measures: During the transmission of data between smart devices and remote data analysis platforms, TLS / SSL protocol is used for encryption to ensure the security of data transmission; The remote data analysis platform uses firewalls, intrusion detection systems and data backup and recovery mechanisms to ensure the security of data storage and processing; Users can set data access permissions through smart devices to control which data can be viewed or shared by which people.

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