Biosensing system for real-time monitoring of intestinal signs

Abstract

The invention discloses a biosensing system for real-time monitoring of intestinal signs, and relates to the technical field of medical electronics. The system comprises a wearable monitoring terminal, a mobile computing terminal and a remote cloud service platform. The wearable terminal adopts a split design: the flexible patch unit integrates a PVDF piezoelectric film sensor and a motion sensor, the host unit is internally provided with a real-time signal processing module, and the flexible patch unit and the host unit are automatically connected with a contact through magnetic attraction. The working process of the system is as follows: the patch unit collects an abdominal vibration signal, and the host unit performs motion artifact suppression, borborygmus event detection and feature extraction in real time and performs local state feedback; and the processed data is wirelessly transmitted to a mobile terminal APP for visualization and intermediate early warning, and is synchronized to a cloud for big data analysis and personalized health modeling based on machine learning, so that high-level accurate early warning is realized. According to the invention, high signal-to-noise ratio acquisition, intelligent real-time analysis, comfortable and convenient wearing and systematic health management of borborygmus and the like are realized, and the problems of subjectivity, discontinuity, discomfort and insufficient intelligence in the prior art are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of medical electronics technology, and in particular to a biosensor system for real-time monitoring of intestinal vital signs. Specifically, it relates to a wearable biosensor system, and more particularly to an intelligent system for real-time, continuous, and non-invasive monitoring of intestinal vital signs (with bowel sounds as the core) in the human body, especially in infants and young children who are unable to express themselves verbally. Background Technology

[0002] Gut health is an important indicator of overall health. Bowel sounds, as the direct acoustic manifestation of intestinal peristalsis, are crucial for the clinical diagnosis of various diseases such as intestinal obstruction, paralytic ileus, gastroenteritis, and functional gastrointestinal disorders, due to variations in their frequency, intensity, duration, and rhythm. For infants (0-12 months), who cannot verbally express discomfort, abnormal bowel function often manifests as unexplained crying, irritability, and abdominal distension, which are easily overlooked or misdiagnosed by parents, leading to delayed diagnosis and treatment.

[0003] Currently, clinical assessment of bowel sounds primarily relies on manual auscultation by physicians using a stethoscope. This method has significant limitations: 1. High subjectivity: Diagnostic results are highly dependent on the physician's experience and auditory sensitivity, lacking objective and quantifiable standards, easily leading to inter-observer variability and missed or misdiagnosed cases. 2. Transient nature: Manual auscultation can only capture fragments of bowel sounds at the moment of auscultation, making long-term continuous monitoring impossible. Many abnormal bowel motility (such as intermittent intestinal obstruction and periodic bowel dysfunction) require dynamic observation to detect. 3. Inefficient and inconvenient: Long-term quiet auscultation is particularly difficult for infants and young children, and continuous monitoring cannot be implemented in a home environment.

[0004] To overcome the aforementioned shortcomings, some research and application attempts have emerged in recent years regarding electronic bowel sound recording devices. These devices typically use acoustic sensors (such as electret condenser microphones) fixed to an abdominal binder to collect abdominal sounds and transmit them to a recorder via wired or wireless means. However, existing technical solutions still have the following key problems: Poor signal quality and weak anti-interference ability: Traditional air conduction microphones are easily interfered with by environmental noise (such as talking, crying, and friction sounds) and internal noise (such as heart sounds and vascular murmurs) while collecting bowel sounds (low sound pressure level, frequency mostly between 100-500Hz). The low signal-to-noise ratio makes subsequent analysis difficult and accuracy hard to guarantee.

[0005] Uncomfortable to wear and poor user experience: Existing devices are often bulky and rigid, and are tightly bound to the abdomen with abdominal bands or tape. Prolonged wear can easily cause skin indentations, redness, swelling, and allergies, making them especially unsuitable for long-term use by infants and young children with delicate skin. Irritation from electrodes or adhesive patches is also common.

[0006] Limited functionality and low level of intelligence: Most devices are merely signal recorders, lacking real-time, online signal processing and analysis capabilities. Data needs to be exported afterward and analyzed by professionals, failing to provide immediate feedback and alerts for home users or clinicians.

[0007] The system is closed and lacks scalability: The equipment is usually designed as an integrated unit, with the sensor fixedly connected to the host, which makes it inconvenient to clean, disinfect, or rotate among multiple users, and also makes it difficult to upgrade or integrate other physiological parameter sensors in the future.

[0008] Therefore, there is an urgent need for a comprehensive biosensor system capable of acquiring high-fidelity, high signal-to-noise ratio bowel sound signals, possessing excellent wearable comfort and safety, and integrating real-time signal processing, intelligent analysis, remote early warning, and data management. This system should be able to balance the precision requirements of clinical medicine with the convenience needs of family health management, providing a reliable technological platform for real-time monitoring and early intervention of gut health. Summary of the Invention

[0009] The technical problem this invention aims to solve is to provide a biosensor system for real-time monitoring of intestinal vital signs, addressing the shortcomings of existing bowel sound monitoring technologies, such as susceptibility to signal interference, discomfort during wear, inability to perform real-time intelligent analysis, and poor system scalability. This system achieves continuous, accurate, comfortable, and intelligent monitoring and assessment of intestinal vital signs (especially bowel sounds) through an innovative sensor scheme, intelligent signal processing chain, user-friendly wearable design, and cloud-based collaborative architecture.

[0010] The above-mentioned objective of this invention is achieved through the following technical solutions: This invention provides a biosensor system for real-time monitoring of intestinal vital signs, comprising: Wearable monitoring terminal, which is worn on the user's abdomen to collect raw physiological signals in real time in a non-invasive manner; The mobile computing terminal runs a dedicated application and establishes a wireless data connection with the wearable monitoring terminal to receive data, provide local real-time analysis, visualization, and human-computer interaction. And a remote cloud service platform, which is connected to the mobile computing terminal via the Internet, for receiving, storing, and deeply analyzing monitoring data, and providing interfaces for long-term trend analysis, health model construction, anomaly warning and professional medical services; The wearable monitoring terminal includes a flexible patch unit and a host unit detachably connected to the flexible patch unit; The flexible patch unit includes: A flexible base layer with a biocompatible adhesive surface for adhesion to the skin; The core sensing module integrated within the flexible substrate includes at least one polyvinylidene fluoride piezoelectric film sensor for sensing mechanical vibrations on the abdominal surface caused by bowel sounds and converting them into a first electrical signal. The second communication and interface module is disposed on the flexible patch unit and is used to transmit the first electrical signal and provide a mechanical and electrical connection interface with the host unit; The host unit includes: shell; The main control and processing module, located inside the housing, is used to control the operation of the entire wearable monitoring terminal and to preprocess the signals from the core sensing module at least. The first communication and interface module is disposed on the host unit and is used to connect with the second communication and interface module of the flexible patch unit to obtain signals and to wirelessly communicate with the mobile computing terminal. The power module supplies power to the host unit; The main control and processing module is further configured to execute the following real-time signal processing procedure: S1: Signal Acquisition and Primary Conditioning: Receives the first electrical signal from the polyvinylidene fluoride piezoelectric film sensor, performs impedance matching, primary amplification and anti-aliasing filtering to obtain the analog conditioning signal; S2: Analog-to-digital conversion and digital filtering: The analog conditioning signal is converted into a digital signal and passed through a bandpass digital filter to filter out noise outside the preset frequency band and extract the target digital signal containing bowel sound characteristics; S3: Real-time extraction of feature parameters: Perform time-domain and / or frequency-domain analysis on the target digital signal to calculate one or more bowel sound feature parameters in real time; S4: Local logic judgment and status feedback: The feature parameters extracted in real time are compared with preset thresholds or dynamic baselines to generate a preliminary judgment result of the current intestinal status, and the indicator component of the host unit is controlled to provide corresponding status visualization feedback.

[0011] According to one embodiment of the present invention, the core sensing module further includes at least one motion sensor for detecting the motion acceleration of the wearable monitoring terminal and generating a second electrical signal; The main control and processing module is also configured to: receive the second electrical signal, identify the user's body movement or the shaking state of the patch itself, and in the signal processing flow S3, use motion sensor data to identify and suppress motion artifacts in the bowel sound signal, so as to improve the accuracy of bowel sound feature parameter extraction.

[0012] According to one embodiment of the present invention, the method for motion artifact recognition and suppression by the main control and processing module includes: when the acceleration value detected by the motion sensor exceeds a first preset threshold, it is determined to be a period of high motion interference, and the target digital signal of bowel sounds during this period is marked or downweighted. And / or, an adaptive filtering algorithm is used to filter out motion interference components associated with the target digital signal of bowel sounds by using the motion sensor signal as reference noise.

[0013] According to one embodiment of the present invention, the event detection algorithm used by the main control and processing module in step S3 is as follows: envelope detection is performed on the target digital signal after digital filtering to obtain the signal envelope; an amplitude threshold and a minimum duration threshold are set, and when the signal envelope exceeds the amplitude threshold and the duration is greater than the minimum duration threshold, it is determined to be a valid bowel sound event; the bowel sound event is continuously detected, and the number of bowel sounds per unit time is calculated accordingly.

[0014] According to one embodiment of the present invention, the dedicated application running on the mobile computing terminal is configured to execute: A1: Receive real-time data from the wearable monitoring terminal, including bowel sound characteristic parameters, raw waveform segments, device status information, and motion data; A2: Perform secondary data processing and visualization: dynamically display trend charts and real-time waveforms of bowel sound characteristic parameters in the form of charts, and show the results of bowel status assessment; A3: Abnormal Warning: Based on a more complex algorithm model or user-personalized settings, determine whether an abnormal bowel sound pattern occurs. If an abnormality is detected, trigger a local audible and visual alarm and push a warning message to the user interface. A4: Data Compression and Upload: After the monitoring data is compressed and encrypted, it is automatically synchronized to the remote cloud service platform via the Internet.

[0015] According to one embodiment of the present invention, the remote cloud service platform is configured to perform: C1: Receives and stores massive amounts of anonymized or identified monitoring data from different users; C2: Conduct big data analysis and machine learning: Based on massive amounts of data, establish and optimize a general bowel sound feature model and a personalized user health baseline model; C3: Advanced Early Warning and Report Generation: Using the general model and personalized baseline model, the uploaded data is analyzed in depth. If a significant deviation from the personalized baseline is found or a known abnormal pattern is matched, a high-level early warning is generated and the user and / or their associated medical staff are notified through the mobile computing terminal application or direct message. C4: Provide data interfaces: Provide secure and ethical data access interfaces for medical institutions or researchers.

[0016] According to one embodiment of the present invention, the host unit and the flexible patch unit are detachably connected by a magnetic coupling mechanism, and an electrical connection is automatically established at the same time as the magnetic connection through an integrated electrical contact point; The magnetic coupling mechanism includes a first magnetic component disposed on the host unit and a second magnetic component disposed on the flexible patch unit; The integrated electrical contact point includes multiple first conductive contacts disposed on the host unit and multiple second conductive contacts disposed on the flexible patch unit and corresponding to the positions of the first conductive contacts.

[0017] According to one embodiment of the present invention, the flexible base layer of the flexible patch unit is made of medical nonwoven fabric or polymer film, and its adhesive surface is coated with low-sensitivity acrylic adhesive or hydrocolloid. The PVDF piezoelectric thin film sensor is integrated into the flexible substrate layer using a flexible circuit connection method, with an overall thickness of no more than 0.5 mm.

[0018] According to one embodiment of the present invention, the outer shell of the host unit is made of food-grade silicone material and has a rounded shape without sharp edges; its surface is provided with: a display screen for displaying simple information, a multi-color LED light ring for indicating working status by color, touch buttons, and a speaker opening for playing heartbeat sound effects or prompt sounds.

[0019] The present invention also provides a method for monitoring intestinal status based on the above-mentioned biosensor system for real-time monitoring of intestinal vital signs, comprising the following steps: Wearing steps: Attach the flexible patch unit to the designated location on the user's abdomen, and then magnetically connect the main unit to the flexible patch unit; Continuous monitoring steps: Power on the system and begin continuously collecting abdominal physiological signals; Real-time processing and local feedback steps: Signal conditioning, feature extraction and preliminary logic judgment are completed in real time within the host unit, and the status is monitored through indicator lights or sound feedback. Data transmission and intelligent analysis steps: The host unit wirelessly transmits the processed data to the mobile computing terminal, where a dedicated application performs further analysis, display, and local alerts; simultaneously, the data is synchronized to a remote cloud service platform for deep learning and advanced alerts. Results output and intervention recommendations: Users and / or healthcare professionals can obtain gut health assessment results, historical trends, and personalized health recommendations through mobile computing terminal applications or cloud reports.

[0020] In summary, compared with the prior art, the present invention has at least one of the following beneficial technical effects: A complete monitoring system integrating "device-edge-cloud" collaboration has been constructed: This invention not only provides hardware devices (wearable terminals), but also builds a complete system including mobile terminals (edge) and a cloud platform (cloud). The wearable terminal is responsible for accurate data collection and preliminary processing, achieving low-latency status feedback; the mobile terminal provides a user-friendly interface and intermediate analysis, enabling real-time visualization and early warning; the cloud platform is responsible for big data storage, deep intelligent analysis, and long-term health management. The three work together to balance real-time performance, intelligence, and scalability.

[0021] Achieving high signal-to-noise ratio and high-precision signal acquisition and processing: At the sensing level: A PVDF piezoelectric thin-film sensor is used as the core to directly sense abdominal wall micro-vibrations, avoiding the main interference path of air-transmitted noise and improving the signal-to-noise ratio from the source. At the processing level: A real-time signal processing chain (S1-S4) is integrated within the main unit, enabling the conversion from analog signals to characteristic parameters and the execution of preliminary logical judgments as soon as data is generated, significantly reducing the amount of data transmitted wirelessly and the latency of backend analysis. At the anti-interference level: An innovative motion sensor is introduced and motion artifact suppression processing is performed, effectively distinguishing bowel sound signals from interference signals generated by body activity, significantly improving the accuracy and robustness of monitoring under complex activity states (such as infant crying and wriggling).

[0022] It provides a multi-layered, intelligent analysis and early warning mechanism: Local rapid feedback: Based on simple logic judgments and indicator lights within the host unit, users can immediately know whether the device is working properly and its general status (such as "collecting", "complete", "weak signal"). Mobile intermediate analysis: The application can run more complex algorithms to achieve threshold-based anomaly detection (such as bowel sounds disappearing for more than 3 minutes) and provide rich visualizations. Cloud-based advanced intelligence: Utilizing machine learning, the cloud can establish personalized health baselines, identify complex abnormal patterns (such as the changing trends of specific frequency combinations), and achieve early and accurate warnings, which is impossible with traditional methods and single devices.

[0023] Significantly enhances wearing comfort and ease of use: The split magnetic design allows the main unit (including battery and complex circuitry) and the patch unit (including sensors) to be separated. The patch unit is ultra-thin, soft, and skin-friendly, allowing for continuous use for extended periods, even days. The main unit only attaches when monitoring or charging is needed, making it convenient for users to shower, change clothes, and for device maintenance and charging. Magnetic connection automatically activates the circuitry, providing an excellent user experience. Material safety: All materials in contact with the skin (silicone shell, non-woven fabric substrate, hypoallergenic adhesives) meet medical or food contact standards, ensuring safety for infants and other sensitive individuals.

[0024] It possesses significant clinical and health management value: For families: It enables non-professional parents to objectively and continuously understand their infants' bowel movements, reducing anxiety caused by the unknown and providing timely alerts when abnormalities occur, thus promoting early medical attention. For clinicians: It provides doctors with objective, continuous, and quantitative bowel sound records, aiding in diagnosis and efficacy evaluation. The structured big data accumulated in the cloud helps advance medical research on bowel sounds and establish more refined diagnostic criteria. For individual health management: Long-term monitoring data helps establish personal gut health profiles, explore the relationship between diet, lifestyle, and gut function, and provide data support for personalized health management (such as probiotic supplementation and dietary adjustments).

[0025] The system boasts strong scalability: the modular design of the flexible patch unit allows for future integration of more types of physiological sensors (such as skin temperature sensors and impedance sensors for monitoring abdominal distension). The "edge-cloud" architecture also facilitates the addition of new analytical algorithms and functions through software updates without requiring hardware replacement.

[0026] In summary, this invention provides a novel intestinal health monitoring solution through comprehensive innovation in hardware, algorithms, and systems. It fundamentally overcomes the shortcomings of existing technologies, such as subjectivity, intermittency, discomfort, and low intelligence, achieving objective, continuous, comfortable, and intelligent monitoring of intestinal vital signs, and possesses significant clinical application prospects and commercial value. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the overall architecture of the system of the present invention.

[0028] Figure 2 This is a schematic diagram of the overall structure of the wearable monitoring terminal of the present invention.

[0029] Figure 3 This is a front view of the wearable monitoring terminal of the present invention.

[0030] Figure 4 This is a reverse view of the main body of the wearable monitoring terminal of the present invention.

[0031] Figure 5 This is a front view of the bottom shell of the wearable monitoring terminal of the present invention.

[0032] Figure 6 This is a schematic diagram showing the state of the wearable monitoring terminal of the present invention during use.

[0033] Figure 7 This is a flowchart of the real-time signal processing performed by the main control and processing module of the present invention.

[0034] Reference numerals: 1. Wearable monitoring terminal; 11. Main unit; 12. Flexible patch unit; 13. Bottom shell; 14. First magnetic component; 15. Second magnetic component; 16. First conductive contact; 17. Second conductive contact; 18. Groove; 19. Positioning protrusion; 110. Positioning recess; 111. Flexible substrate layer; 112. Biocompatible adhesive layer; 113. Display screen; 114. Multi-color LED light ring; 115. Touch button; 116. Speaker opening; 117. Release paper; 2. Mobile computing terminal; 3. Remote cloud service platform. Detailed Implementation

[0035] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0036] In the description of this application, it should be noted that the terms "upper," "lower," "inner," "outer," "top / bottom," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0037] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installed," "equipped with," "sleeved / connected," "connected," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0038] Reference Figures 1-7 This invention discloses a biosensor system for real-time monitoring of intestinal vital signs, comprising: Wearable monitoring terminal 1: worn on the user's abdomen to collect raw physiological signals in real time in a non-invasive manner; wearable monitoring terminal 1 includes a flexible patch unit 12 and a host unit 11 detachably connected to the flexible patch unit 12; Mobile computing terminal 2: runs a dedicated application and establishes a wireless data connection with wearable monitoring terminal 1 to receive data, provide local real-time analysis, visualization, and human-computer interaction; And remote cloud service platform 3: connected to mobile computing terminal 2 via the Internet, used to receive, store, and deeply analyze monitoring data, and provide long-term trend analysis, health model building, abnormal early warning and professional medical service interface; The flexible patch unit 12 includes: The flexible base layer 111 has a biocompatible adhesive surface for adhesion to the skin; The core sensing module integrated within the flexible substrate 111 includes at least one polyvinylidene fluoride piezoelectric film sensor for sensing mechanical vibrations on the abdominal surface caused by bowel sounds and converting them into a first electrical signal. The second communication and interface module is disposed on the flexible patch unit 12, and is used to transmit the first electrical signal and provide a mechanical and electrical connection interface with the host unit 11. The host unit 11 includes: shell; The main control and processing module, located inside the housing, is used to control the operation of the entire wearable monitoring terminal 1 and to preprocess the signals from the core sensing module at least. The first communication and interface module is disposed on the host unit 11 and is used to connect with the second communication and interface module of the flexible patch unit 12 to obtain signals and to communicate wirelessly with the mobile computing terminal 2. The power module supplies power to the main unit 11; The main control and processing module is further configured to execute the following real-time signal processing flow: S1: Signal Acquisition and Primary Conditioning: Receives the first electrical signal from the PVDF piezoelectric film sensor, performs impedance matching, primary amplification and anti-aliasing filtering to obtain the analog conditioning signal; S2: Analog-to-digital conversion and digital filtering: Converts the analog conditioning signal into a digital signal, and passes it through a bandpass digital filter to filter out noise outside the preset frequency band and extract the target digital signal containing bowel sound characteristics; S3: Real-time feature parameter extraction: Perform time-domain and / or frequency-domain analysis on the target digital signal to calculate one or more bowel sound feature parameters in real time. Feature parameters include, but are not limited to: number of bowel sound events per unit time, average duration, average amplitude, and dominant frequency. S4: Local logic judgment and status feedback: The feature parameters extracted in real time are compared with preset thresholds or dynamic baselines to generate a preliminary judgment result of the current intestinal status, and the indicator component of the host unit 11 is controlled to provide corresponding status visualization feedback.

[0039] Furthermore, the core sensing module also includes at least one motion sensor for detecting the motion acceleration of the wearable monitoring terminal 1 and generating a second electrical signal; the main control and processing module is also configured to: receive the second electrical signal, identify the user's body movement or the shaking state of the patch itself, and in the signal processing flow S3, use the motion sensor data to identify and suppress motion artifacts in the bowel sound signal to improve the accuracy of bowel sound feature parameter extraction.

[0040] Furthermore, the method for motion artifact recognition and suppression by the main control and processing module includes: when the acceleration value detected by the motion sensor exceeds a first preset threshold, it is determined to be a period of high motion interference, and the target digital signal of bowel sounds during this period is marked or downweighted; and / or, an adaptive filtering algorithm is used to filter out the motion interference components associated with the motion sensor signal as reference noise from the target digital signal of bowel sounds.

[0041] Furthermore, the event detection algorithm used by the main control and processing module in step S3 is as follows: envelope detection is performed on the target digital signal after digital filtering to obtain the signal envelope; an amplitude threshold and a minimum duration threshold are set, and when the signal envelope exceeds the amplitude threshold and the duration is greater than the minimum duration threshold, it is determined to be a valid bowel sound event; bowel sound events are continuously detected, and the number of bowel sounds per unit time is calculated accordingly.

[0042] Furthermore, the dedicated application running on mobile computing terminal 2 is configured to execute: A1: Receives real-time data from wearable monitoring terminal 1, including bowel sound characteristic parameters, raw waveform segments, device status information, and motion data; A2: Perform secondary data processing and visualization: dynamically display trend charts and real-time waveforms of bowel sound characteristic parameters in the form of charts, and show the results of bowel status assessment; A3: Abnormal Warning: Based on a more complex algorithm model or user-personalized settings, determine whether an abnormal bowel sound pattern occurs. If an abnormality is detected, trigger a local audible and visual alarm and push a warning message to the user interface. A4: Data Compression and Upload: After compressing and encrypting the monitoring data, it will be automatically synchronized to the remote cloud service platform via the Internet.

[0043] Furthermore, the remote cloud service platform 3 is configured to execute: C1: Receives and stores massive amounts of anonymized or identified monitoring data from different users; C2: Conduct big data analysis and machine learning: Based on massive amounts of data, establish and optimize a general bowel sound feature model and a personalized user health baseline model; the general model is used to identify common abnormal bowel sound patterns; the personalized baseline model learns the individualized normal fluctuation range of bowel sounds by analyzing long-term user data. C3: Advanced Alerts and Reports Generation: Utilizing general and personalized baseline models, the uploaded data undergoes in-depth analysis. If significant deviations from the personalized baseline are found or a known abnormal pattern is matched, a high-level alert is generated and notified to the user and / or their associated healthcare personnel via the Mobile Computing Terminal 2 application or direct message. C4: Provide data interfaces: Provide secure and ethical data access interfaces for medical institutions or researchers to support clinical research and epidemiological investigations.

[0044] Furthermore, the host unit 11 and the flexible patch unit 12 are detachably connected through a magnetic coupling mechanism, and an electrical connection is automatically established at the same time as the magnetic connection through an integrated electrical contact point; the magnetic coupling mechanism includes a first magnetic element 14 disposed on the host unit 11 and a second magnetic element 15 disposed on the flexible patch unit 12; the integrated electrical contact point includes a plurality of first conductive contacts 16 disposed on the host unit 11 and a plurality of second conductive contacts 17 disposed on the flexible patch unit 12 and corresponding to the positions of the first conductive contacts 16.

[0045] Furthermore, the flexible substrate layer 111 of the flexible patch unit 12 is made of medical non-woven fabric or polymer film, and its adhesive surface is coated with low-sensitivity acrylic adhesive or hydrocolloid; the PVDF piezoelectric film sensor is integrated in the flexible substrate layer 111 in a flexible circuit connection manner, and the overall thickness is no more than 0.5mm.

[0046] Furthermore, the outer shell of the main unit 11 is made of food-grade silicone material and has a rounded shape without sharp edges; its surface is provided with: a display screen 113 for displaying simple information, a multi-color LED light ring 114 for indicating the working status by color, touch buttons 115, and a speaker opening 116 for playing heartbeat sound effects or prompt sounds.

[0047] Furthermore, the system also includes a system-based intestinal state monitoring method, characterized by comprising the following steps: Wearing steps: Attach the flexible patch unit 12 to the designated position on the user's abdomen, and magnetically connect the main unit 11 to the flexible patch unit 12; Continuous monitoring steps: Power on the system and begin continuously collecting abdominal physiological signals; Real-time processing and local feedback steps: Signal conditioning, feature extraction and preliminary logic judgment are completed in real time within the host unit 11, and the status is monitored through indicator lights or sound feedback; Data transmission and intelligent analysis steps: The host unit 11 wirelessly transmits the processed data to the mobile computing terminal 2, where a dedicated application performs further analysis, display, and local alerts; at the same time, the data is synchronized to the remote cloud service platform 3 for deep learning and advanced alerts. Results output and intervention recommendations: Users and / or healthcare professionals can obtain gut health assessment results, historical trends, and personalized health recommendations through mobile computing terminal 2 applications or cloud reports. Example 1

[0048] Please see Figure 1 This invention provides a biosensor system for real-time monitoring of intestinal vital signs. Its overall architecture comprises three core components: a wearable monitoring terminal 1, a mobile computing terminal 2, and a remote cloud service platform 3. This system works collaboratively through a network to achieve real-time, continuous, and intelligent monitoring and management of a user's (taking infants as an example, but not limited to this) intestinal vital signs.

[0049] like Figures 2-6 As shown, the wearable monitoring terminal 1 adopts an innovative split design, mainly consisting of a flexible patch unit 12 and a host unit 11.

[0050] like Figure 2 As shown, the flexible patch unit 12 is the part that directly contacts the user's abdominal skin. Its core design features extreme softness, thinness, skin-friendliness, and high signal-to-noise ratio sensing. The flexible patch unit 12 includes a bottom shell 13, a flexible base layer 111, a biocompatible adhesive layer 112, release paper 117, a second communication and interface module, and a core sensing module disposed within the bottom shell 13.

[0051] Reference Figure 6 The flexible base layer 111 serves as a carrier, made of single-layer or multi-layer composite medical-grade non-woven fabric or polyurethane film, exhibiting excellent breathability and flexibility. One side (the adhesive side) is coated with a biocompatible adhesive layer 112, preferably a low-sensitivity acrylate or hydrocolloid, ensuring that it remains tacky even after prolonged adhesion (e.g., 24-72 hours) without causing skin irritation or allergies. The other side has a bottom shell 13. Before adhesion, the adhesive side of the flexible base layer 111 is covered and protected by release paper 117. The area of ​​the flexible base layer 111 is larger than the area of ​​the bottom shell 13 supporting it, forming a ring of "wings" to provide stable and reliable adhesion. All edges are rounded with large arc transitions, without any sharp corners.

[0052] The core sensing module, which is the source of signal acquisition, is integrated and packaged inside the bottom shell 13. The core sensing module includes a PVDF piezoelectric film sensor and a motion sensor.

[0053] PVDF piezoelectric film sensor: As the main sensor, its thickness is only 0.1-0.3 mm (0.2 mm in this embodiment). It is precisely attached to a specific position on the flexible substrate 111 (typically corresponding to the optimal auscultation area for bowel sounds). When intestinal peristalsis generates sound / vibration waves that travel to the abdominal wall, the PVDF film undergoes slight deformation, generating a charge (voltage) signal proportional to the vibration intensity. This direct vibration sensing method fundamentally avoids the sensitivity of air-conducting microphones to environmental noise.

[0054] Motion sensor: This embodiment employs a microelectromechanical system (MEMS) triaxial accelerometer. It is positioned side-by-side or adjacent to the patch unit (i.e., the abdomen) to monitor the motion state of the patch unit in real time. The data is primarily used in subsequent signal processing to identify and suppress signal artifacts caused by body movement.

[0055] The second communication and interface module is used for physical and electrical connection with the host unit 11. The second communication and interface module includes a second magnetic element 15 and a second conductive contact 17. The second magnetic component 15 is a permanent magnet (such as a neodymium iron boron magnet) embedded in the central region of the upper surface of the flexible patch unit 12, arranged in a specific polarity pattern.

[0056] The second conductive contact 17 consists of multiple (e.g., four) metal discs exposed on the upper surface, connected to the output terminals of the PVDF piezoelectric film sensor and the motion sensor via flexible circuitry (such as printed circuitry on a polyimide substrate). The contact surface is gold-plated to prevent oxidation.

[0057] All electronic components are interconnected by flexible circuits and are encapsulated by flexible encapsulation materials (such as medical silicone) to form a thin, waterproof (at least IPX7 level), and robust whole.

[0058] like Figure 1 and Figure 2 As shown, the host unit 11 is the intelligent processing and communication hub, which is attached to the patch unit only when monitoring is required. The host unit 11 includes a housing, a display screen 113 mounted on the housing, a multi-color LED light ring 114 surrounding the display screen 113, touch buttons 115 mounted on the display screen 113, a speaker opening 116 on the housing, a main control and processing module inside the housing, and a first communication and interface module at the bottom of the housing.

[0059] Shell: Made of food-grade liquid silicone through a one-piece injection molding process, it is soft in texture and has rounded edges. The top integrates user interaction components. Display 113: Small circular OLED display 113 for displaying time, battery level, connection status or simple bowel sound event counts.

[0060] Multi-color LED light ring 114: Surrounds the display screen 113 and can emit multiple colors such as red, yellow, green, and blue, as well as different flashing modes, to intuitively indicate the system status (e.g., red breathing light - standby / charging, yellow solid light - data acquisition in progress, green flashing rapidly - data is being sent, green solid light - single monitoring completed / data normal).

[0061] Touch button 115: Capacitive touch button used for power on / off and starting / stopping single monitoring.

[0062] Speaker opening 116: Internally connected to a miniature speaker for playing operation prompts, alarm sounds, or simulated heartbeats (for soothing infants and young children).

[0063] The first communication and interface module is used for physical and electrical connection with the flexible patch unit 12. The first communication and interface module includes a first magnetic element 14, a first conductive contact 16, a wireless communication chip, and a power supply module.

[0064] The first magnetic element 14 has a polarity corresponding to the second magnetic element 15, ensuring that the host unit 11 can be strongly attracted to the flexible patch unit 12 in the correct direction.

[0065] The first conductive contact 16 is a flexible probe or a gold-plated copper pillar, and its position corresponds one-to-one with the second conductive contact 17. When magnetically aligned, these contacts reliably make contact and automatically establish an electrical connection.

[0066] Wireless communication chip: Bluetooth Low Energy chip is preferred. It is responsible for packaging the data processed by the main control and processing module (such as characteristic parameters, tagged raw signal segments, and device status) and wirelessly transmitting it to the mobile computing terminal 2.

[0067] Power module: Includes a rechargeable lithium polymer battery and charging management circuitry. The main unit 11 can be charged via a wireless charging coil on its bottom or a concealed USB-C port.

[0068] In the embodiments, reference is made to Figure 4 and Figure 5 The bottom shell 13 has a groove 18 on the side facing the main unit 11; at least a part of the structure of the main unit 11 can be embedded in the groove 18; the bottom surface of the groove 18 has a positioning protrusion 19, and the bottom surface of the main unit 11 has a positioning recess 110 that matches the shape of the positioning protrusion 19; the second magnetic attractor and the second conductive contact 17 are disposed on the positioning protrusion 19, and the first magnetic attractor and the first conductive contact 16 are disposed in the positioning recess 110.

[0069] Main control and processing module: This is the "brain" of the host unit 11, and its specific structure and processing flow are the key to this invention.

[0070] Hardware components include a microprocessor (such as an ARM Cortex-M series low-power MCU), a signal conditioning circuit (used to receive analog signals from the sensor at the contact point, and amplify and filter them), an analog-to-digital converter, and a memory (used to temporarily store programs and data).

[0071] Real-time signal processing flow ( Figure 7 The microprocessor executes embedded software to perform the following steps: S1: Acquisition and Primary Conditioning: The weak charge signal from the PVDF piezoelectric film sensor is received through the first conductive contact 16. The signal conditioning circuit converts it into a voltage signal and amplifies it, while a hardware low-pass filter (anti-aliasing) filters out high-frequency noise higher than half the sampling frequency.

[0072] S2: Analog-to-Digital Conversion and Digital Filtering: The ADC digitizes the analog signal at a certain sampling rate (e.g., 1kHz). The MCU applies a digital bandpass filter (e.g., passband 50Hz-600Hz) to the digital signal to preserve the main energy frequency band of the bowel sounds while filtering out power line interference (50 / 60Hz) and higher-frequency irrelevant noise.

[0073] S3: Real-time Feature Parameter Extraction: This is the core algorithm step. First, motion artifact suppression is performed: Acceleration data from the motion sensor is read. If the vector amplitude exceeds a set threshold, it is considered to be in a period of high motion interference. The bowel sound digital signals in the same period are then marked or given lower weight in subsequent analysis. More advanced methods can use adaptive filters, with the acceleration signal as a reference input, to dynamically filter out motion-related components in the bowel sound signal.

[0074] Next, bowel sound event detection is performed: the envelope of the filtered signal is calculated (which can be obtained through Hilbert transform or low-pass filtering after full-wave rectification). An adaptive amplitude threshold (e.g., based on background noise level) and a minimum duration threshold (e.g., 0.1 seconds) are set. When the envelope exceeds the amplitude threshold and the duration exceeds the minimum threshold, a bowel sound event is detected. The MCU counts the number of events per unit time (e.g., 1 minute) in real time and calculates the average amplitude and duration of each event. The dominant frequency of the event can also be estimated through short-time Fourier transform.

[0075] S4: Local Logic Judgment and Feedback: The real-time calculated "bowel sounds frequency / minute" is compared with simple thresholds stored in memory (e.g., <2 times / 5 minutes is "diminished", >10 times / minute is "excessive"). Based on the comparison result, the multi-color LED ring 114 is immediately controlled to change its color or flashing mode (e.g., yellow remains on during monitoring, and if no event is detected for 3 consecutive minutes, the yellow turns to red and flashes as an alarm), or a speaker is triggered to emit a soft alert sound. This local, real-time feedback is crucial, especially when the network connection is unstable or the mobile device is not readily available.

[0076] like Figure 6 As shown, in use, first peel off the release paper 117 and attach the flexible patch unit 12 to the user's clean, dry abdominal skin. Then, roughly align the main unit 11 with the patch unit and place it down. Under the action of strong magnetic attraction (between the first magnetic element 14 and the second magnetic element 15), the main unit 11 is automatically pulled and aligned, adhering tightly. At the same time, the first conductive contact 16 and the second conductive contact 17 achieve stable, low-resistance electrical contact under the action of magnetic force. The entire process requires no precise alignment or plugging and unplugging, achieving a "foolproof" connection. When disassembling, simply overcome the magnetic force and gently pull up the main unit 11; the flexible patch unit 12 can remain on the skin.

[0077] Mobile computing terminal 2 is typically a user's smartphone or tablet computer, on which an application developed specifically for this system is installed.

[0078] Functional modules: Device connection and management module: responsible for searching, pairing, and connecting to wearable monitoring terminal 1 via Bluetooth, and managing the connection status.

[0079] Data receiving and caching module: continuously receives streaming data from host unit 11 and caches it locally.

[0080] Data processing and visualization module: This is the core of the app. It runs more complex algorithms than host unit 11, for example: The received bowel sound events are re-analyzed and classified more accurately.

[0081] By combining motion sensor data, the validity of the data can be determined more intelligently (such as marking periods when data is unavailable due to intense crying).

[0082] Data is presented in a variety of chart formats: real-time scrolling waveforms, trend charts of bowel sound events over time (hourly / daily), amplitude distribution charts, etc.

[0083] Local alert module: Based on preset rules (e.g., "no bowel sounds for 5 consecutive minutes" or "bowle frequency continuously higher than 12 times / minute for more than 10 minutes") or personalized rules downloaded from the cloud, trigger local push notifications, in-app pop-up alerts and sound reminders.

[0084] User interaction and settings module: Provides a user-friendly interface that allows users to view historical records, set monitoring plans, adjust alarm thresholds (within safe limits), and input related events such as feeding and defecation.

[0085] Data synchronization module: Compresses and encrypts locally cached data (including raw data, feature data, and user logs), and automatically, periodically, or manually uploads it to a remote cloud service platform via Wi-Fi or cellular network.

[0086] The remote cloud service platform 33 is deployed on a cloud server cluster, providing powerful data storage and intelligent analysis capabilities.

[0087] Functional architecture: Data access and storage layer: Receives data uploaded from tens of thousands of mobile terminals and securely stores it in a massive database. The data is anonymized to protect privacy.

[0088] Computation engine and analytics layer: Batch processing: Perform offline analysis on historical data to calculate more complex statistical features.

[0089] Machine learning model training and deployment: This is the core of system intelligence. Using massive amounts of labeled data (partially from collaborating medical institutions), the following models are trained and continuously optimized: The general bowel sound abnormality recognition model can identify complex patterns such as "typical hyperactive sounds of mechanical intestinal obstruction" and "silent abdomen of paralytic intestinal obstruction," and its accuracy far exceeds that of simple threshold judgment.

[0090] Personalized baseline modeling: For each user, analyze their long-term monitoring data and use statistical methods or time series models to learn the normal diurnal rhythm and individualized fluctuation range of their bowel sound activity, and establish a dynamic, personalized health baseline.

[0091] Real-time Stream Processing and Early Warning Layer: Processes continuously uploaded real-time data streams. New data is input into the user's personalized baseline model and general anomaly model for analysis. Once a significant deviation from the baseline or a matching anomaly pattern is detected, a high-level early warning event is immediately generated.

[0092] Service and Interface Layer: Early warning service: Pushes early warning events to the corresponding mobile computing terminal 2 APP in real time, and can notify emergency contacts through additional channels such as SMS and email.

[0093] Reporting services: Generate user health reports regularly (e.g., weekly, monthly), summarize and analyze results, and provide visual charts and easy-to-understand health advice.

[0094] Professional Interfaces: Provide authorized physicians or researchers with secure web portals or APIs that enable them to view detailed patient data, participate in remote consultations, or access anonymized datasets for research.

[0095] To illustrate a typical use case (taking home monitoring of infants and young children as an example): Initialization and Wearing: Parents attach the new flexible patch unit 12 to the infant. When monitoring is needed, the charged main unit 11 is attached. The main unit 11 is powered on, and the multi-color LED ring 114 illuminates a red breathing light (standby). At the same time, the parent opens the mobile app, which automatically searches for and connects to the main unit 11.

[0096] Monitoring Activation: Parents can activate monitoring via the app or by pressing the touch button 115 on the main unit 11. The multi-color LED ring 114 on the main unit 11 turns solid yellow, indicating that monitoring has begun. Figure 7 The real-time signal processing flow is shown. The APP interface displays "Monitoring" and begins plotting real-time waveforms.

[0097] Continuous monitoring and local feedback: The system continues to operate for the next few hours. The host unit 11 analyzes data every second and keeps it yellow via a multi-color LED ring 114. If a simple algorithm within the host unit 11 fails to detect any bowel sound events for three consecutive minutes, its multi-color LED ring 114 may flash red and emit a soft beep (if the settings allow), providing a local, immediate alarm.

[0098] Data transmission and mobile analytics: Simultaneously, the processed feature data and fragmented raw data are continuously sent to the mobile app via Bluetooth. The app performs secondary processing and visualization, allowing parents to view a clear trend chart of bowel sound activity on their phones. If the app's algorithm also identifies an anomaly (e.g., judging "significantly weakened bowel sounds" based on data from a longer period), a prominent warning notification will pop up on the phone screen.

[0099] Cloud synchronization and intelligent analysis: The mobile app encrypts and uploads data to the cloud platform in the background. The cloud platform uses the infant's historical data to establish a personalized baseline and evaluates the new interval data. Suppose the cloud platform's machine learning model finds that the current pattern has a high similarity to the hidden characteristics of "early intussusception," even if the alarm threshold set by the parents or the app has not yet been reached, the system may generate a high-level, high-confidence warning and notify the parents through a strong reminder in the app or even by phone.

[0100] Results Application and Intervention: After receiving the alert, parents can immediately view the detailed report and waveforms in the app to decide whether to soothe and observe the infant, adjust feeding, or take the cloud report to the doctor promptly. Doctors can access the infant's complete and continuous bowel sound records through a professional interface, serving as an important objective basis for diagnosis.

[0101] End of monitoring and maintenance: After monitoring is completed, remove the main unit 11 for charging. The flexible patch unit 12 can be removed and discarded according to the product design (e.g., for single use), or (e.g., for limited use) retained until the next monitoring. The entire process is safe, convenient, and intelligent.

[0102] This invention is not a simple device improvement, but rather the construction of a complete technical system, from high-fidelity signal sensing (PVDF + motion sensing) to real-time edge intelligence (algorithms within the host unit 11) and then to deep intelligence in the cloud (machine learning models). It resolves the conflict between comfort and convenience through a magnetic split design, and balances immediacy and accuracy through dual "local + cloud" early warning systems. In particular, the introduction of motion sensors and real-time artifact suppression, as well as machine learning modeling of personalized health baselines, are the core innovations that enhance the system's practicality and accuracy in real-world, complex scenarios.

[0103] The implementation principle of this invention is as follows: This invention discloses a biosensor system for real-time monitoring of intestinal vital signs, relating to the field of medical electronics technology. The system includes a wearable monitoring terminal 1, a mobile computing terminal 2, and a remote cloud service platform 3. The wearable terminal adopts a split design: a flexible patch unit 12 integrates a PVDF piezoelectric film sensor and a motion sensor, while the host unit 11 has a built-in real-time signal processing module; the two are automatically connected via magnetic attraction and contacts. The system workflow is as follows: the patch unit collects abdominal vibration signals; the host unit 11 performs real-time motion artifact suppression, bowel sound event detection and feature extraction, and provides local status feedback; the processed data is wirelessly transmitted to a mobile terminal APP for visualization and intermediate-level early warning, and simultaneously transmitted to the cloud for machine learning-based big data analysis and personalized health modeling, achieving high-level accurate early warning. This invention achieves high signal-to-noise ratio acquisition of bowel sounds, intelligent real-time analysis, comfortable and convenient wear, and systematic health management, effectively solving the problems of subjective, intermittent, uncomfortable, and insufficient intelligence in existing technologies.

[0104] The embodiments described herein are preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape, and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A biosensor system for real-time monitoring of intestinal vital signs, characterized in that, include: Wearable monitoring terminal (1) is used to wear on the user's abdomen to collect raw physiological signals in real time in a non-invasive manner; The mobile computing terminal (2) runs a dedicated application and establishes a wireless data connection with the wearable monitoring terminal (1) to receive data, provide local real-time analysis, visualization display and human-computer interaction; And a remote cloud service platform (3), which is connected to the mobile computing terminal (2) via the Internet, for receiving, storing, and deeply analyzing monitoring data, and providing long-term trend analysis, health model construction, abnormal early warning and professional medical service interfaces; The wearable monitoring terminal (1) includes a flexible patch unit (12) and a host unit (11) detachably connected to the flexible patch unit (12); The flexible patch unit (12) includes: A flexible base layer (111) with a biocompatible adhesive surface for adhesion to the skin; The core sensing module integrated within the flexible substrate (111) includes at least one polyvinylidene fluoride piezoelectric film sensor for sensing mechanical vibrations on the abdominal surface caused by bowel sounds and converting them into a first electrical signal. The second communication and interface module is disposed on the flexible patch unit (12) for transmitting the first electrical signal and providing a mechanical and electrical connection interface with the host unit (11); The host unit (11) includes: shell; The main control and processing module is located inside the housing and is used to control the operation of the entire wearable monitoring terminal (1) and at least preprocess the signals from the core sensing module; The first communication and interface module is disposed on the host unit (11) and is used to connect with the second communication and interface module of the flexible patch unit (12) to obtain signals and to communicate wirelessly with the mobile computing terminal (2); The power supply module supplies power to the host unit (11); The main control and processing module is further configured to execute the following real-time signal processing procedure: S1: Signal Acquisition and Primary Conditioning: Receives the first electrical signal from the polyvinylidene fluoride piezoelectric film sensor, performs impedance matching, primary amplification and anti-aliasing filtering to obtain the analog conditioning signal; S2: Analog-to-digital conversion and digital filtering: The analog conditioning signal is converted into a digital signal and passed through a bandpass digital filter to filter out noise outside the preset frequency band and extract the target digital signal containing bowel sound characteristics; S3: Real-time extraction of feature parameters: Perform time-domain and / or frequency-domain analysis on the target digital signal to calculate one or more bowel sound feature parameters in real time; S4: Local logic judgment and status feedback: The feature parameters extracted in real time are compared with the preset threshold or dynamic baseline to generate a preliminary judgment result of the current intestinal status, and the indicator component of the host unit (11) is controlled to provide visual feedback of the corresponding status.

2. The biosensor system for real-time monitoring of intestinal vital signs according to claim 1, characterized in that, The core sensing module also includes at least one motion sensor for detecting the motion acceleration of the wearable monitoring terminal (1) and generating a second electrical signal; The main control and processing module is also configured to: receive the second electrical signal, identify the user's body movement or the shaking state of the patch itself, and in the signal processing flow S3, use motion sensor data to identify and suppress motion artifacts in the bowel sound signal, so as to improve the accuracy of bowel sound feature parameter extraction.

3. A biosensor system for real-time monitoring of intestinal vital signs according to claim 2, characterized in that, The method for motion artifact recognition and suppression by the main control and processing module includes: when the acceleration value detected by the motion sensor exceeds a first preset threshold, it is determined to be a high motion interference period, and the target digital signal of bowel sounds during this period is marked or downweighted; and / or, an adaptive filtering algorithm is used to filter out motion interference components related to the target digital signal of bowel sounds by using the motion sensor signal as reference noise.

4. A biosensor system for real-time monitoring of intestinal vital signs according to claim 1, characterized in that, The event detection algorithm used by the main control and processing module in step S3 is as follows: envelope detection is performed on the target digital signal after digital filtering to obtain the signal envelope; an amplitude threshold and a minimum duration threshold are set. When the signal envelope exceeds the amplitude threshold and the duration is greater than the minimum duration threshold, it is determined to be a valid bowel sound event. The bowel sound events are continuously detected, and the number of bowel sounds per unit time is calculated accordingly.

5. A biosensor system for real-time monitoring of intestinal vital signs according to claim 1, characterized in that, The dedicated application running on the mobile computing terminal (2) is configured to execute: A1: Receive real-time data from the wearable monitoring terminal (1), the data including bowel sound characteristic parameters, raw waveform segments, device status information and motion data; A2: Perform secondary data processing and visualization: dynamically display trend charts and real-time waveforms of bowel sound characteristic parameters in the form of charts, and show the results of bowel status assessment; A3: Abnormal Warning: Based on a more complex algorithm model or user-personalized settings, determine whether an abnormal bowel sound pattern occurs. If an abnormality is detected, trigger a local audible and visual alarm and push a warning message to the user interface. A4: Data compression and uploading: After the monitoring data is compressed and encrypted, it is automatically synchronized to the remote cloud service platform via the Internet (3).

6. A biosensor system for real-time monitoring of intestinal vital signs according to claim 1 or 5, characterized in that, The remote cloud service platform (3) is configured to execute: C1: Receives and stores massive amounts of anonymized or identified monitoring data from different users; C2: Conduct big data analysis and machine learning: Based on massive amounts of data, establish and optimize a general bowel sound feature model and a personalized user health baseline model; C3: Advanced warning and report generation: Using the general model and personalized baseline model, the uploaded data is analyzed in depth. If a significant deviation from the personalized baseline or a known abnormal pattern is found, a high-level warning is generated and the user and / or their associated medical staff are notified through the mobile computing terminal (2) application or direct message. C4: Provide data interfaces: Provide secure and ethical data access interfaces for medical institutions or researchers.

7. A biosensor system for real-time monitoring of intestinal vital signs according to claim 1, characterized in that, The host unit (11) and the flexible patch unit (12) are detachably connected by a magnetic coupling mechanism, and an electrical connection is automatically established at the same time as the magnetic connection through an integrated electrical contact point; the magnetic coupling mechanism includes a first magnetic element (14) disposed on the host unit (11) and a second magnetic element (15) disposed on the flexible patch unit (12); the integrated electrical contact point includes a plurality of first conductive contacts (16) disposed on the host unit (11) and a plurality of second conductive contacts (17) disposed on the flexible patch unit (12) and corresponding to the positions of the first conductive contacts (16).

8. A biosensor system for real-time monitoring of intestinal vital signs according to claim 1, characterized in that, The flexible base layer (111) of the flexible patch unit (12) is made of medical non-woven fabric or polymer film, and its adhesive surface is coated with low-sensitivity acrylic adhesive or hydrocolloid; the PVDF piezoelectric film sensor is integrated in the flexible base layer (111) in a flexible circuit connection manner, and the overall thickness is no more than 0.5mm.

9. A biosensor system for real-time monitoring of intestinal vital signs according to claim 1, characterized in that, The outer shell of the main unit (11) is made of food-grade silicone and has a rounded shape without sharp edges. Its surface is provided with: a display screen (113) for displaying simple information, a multi-color LED light ring (114) for indicating the working status by color, a touch button (115), and a speaker opening (116) for playing heartbeat sound effects or prompts.

10. A method for monitoring intestinal condition based on the biosensor system according to any one of claims 1-9, characterized in that, Includes the following steps: Wearing steps: Attach the flexible patch unit (12) to the designated position on the user's abdomen, and attach the main unit (11) to the flexible patch unit (12) by adsorption; Continuous monitoring steps: Power on the system and begin continuously collecting abdominal physiological signals; Real-time processing and local feedback steps: Signal conditioning, feature extraction and preliminary logic judgment are completed in real time in the host unit (11), and the status is monitored by indicator lights or sound feedback; Data transmission and intelligent analysis steps: The host unit (11) wirelessly transmits the processed data to the mobile computing terminal (2), where a dedicated application performs further analysis, display, and local early warning; at the same time, the data is synchronized to the remote cloud service platform (3) for deep learning and advanced early warning. Results output and intervention recommendations: Users and / or healthcare professionals can obtain gut health assessment results, historical trends and personalized health recommendations through mobile computing terminal (2) applications or cloud reports.

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