Older adult and child incontinence monitoring system for wearable flexible ultrasound device

Abstract

This utility model relates to a wearable flexible ultrasound device for monitoring the excretion of the elderly and children, comprising: a flexible ultrasound sensor array, an ultrasound transducer unit, a biocompatible flexible acoustic coupling layer, a signal processing and control module, a data acquisition and intelligent processing module, a posture and movement sensing module, a wireless communication module, and a power management module. By integrating the flexible ultrasound sensor array and the biocompatible acoustic coupling layer, the system achieves a comfortable and close fit to human skin, significantly improving the feasibility of long-term wear and the user experience. Utilizing the phased array transducer unit and the advanced signal processing and control module, the system can efficiently and accurately acquire and process multimodal echo signals from the bladder and intestines, thereby achieving simultaneous monitoring and intelligent identification of various excretion conditions such as bladder fullness, urination events, intestinal fecal accumulation, and defecation events.

Description

Technical Field

[0001] This utility model relates to the field of medical monitoring technology, specifically to a wearable flexible ultrasound device for monitoring the excretion of the elderly and children. Background Technology

[0002] With the increasing global trend of population aging and the growing demand for more refined infant and toddler health management, continuous and accurate monitoring of excretory function has become an urgent need for home care and medical institutions. Traditional excretory monitoring relies heavily on manual observation and periodic checks by caregivers, which suffers from problems such as low efficiency, easy to miss detections, significant interference at night, and damage to patient dignity, while also placing a heavy workload on caregivers.

[0003] In recent years, although some monitoring devices based on sensor technology have emerged, most focus on monitoring physiological parameters such as heart rate, blood oxygen, and activity levels. Existing technologies have significant shortcomings in waste monitoring. Most devices are relatively simple in function, typically only monitoring urine (such as bladder capacity), lacking effective means to monitor bowel movements, such as intestinal accumulation and defecation events, thus failing to provide users with a comprehensive profile of their excretory health. Regarding wearing comfort, existing ultrasound monitoring devices mostly use rigid transducers and hard circuit boards, making it difficult to maintain a close fit with the skin for extended periods. They are prone to displacement or signal attenuation during human activity, resulting in poor wearing comfort and unsuitability for long-term continuous use. Furthermore, these devices often have low levels of intelligence, lacking effective signal processing and pattern recognition algorithms, and cannot accurately distinguish between bowel movement, urination, intestinal peristalsis, and motion artifacts, leading to high false alarm rates and significantly limiting their practicality and reliability. The equipment also has significant shortcomings in terms of battery life and signal coupling methods, generally suffering from high power consumption and the need for frequent charging or battery replacement; at the same time, traditional ultrasonic coupling agents are prone to drying out, which cannot guarantee the stability and consistency of signal transmission during long-term dynamic monitoring.

[0004] Therefore, there is an urgent need in this field for a comprehensive solution that can simultaneously monitor urination and defecation, is comfortable to wear, is highly intelligent, and is suitable for long-term dynamic monitoring. Utility Model Content

[0005] To address the shortcomings of existing technologies, this utility model provides a wearable flexible ultrasound device for monitoring the excretion of the elderly and children, aiming to solve one or more problems in the background technology.

[0006] To achieve the above objectives, this utility model adopts the following technical solution: a wearable flexible ultrasound device for monitoring excretion, comprising: a flexible ultrasound sensor array configured to adhere to the user's lower abdomen, containing multiple ultrasound transducer units arranged in a phased array on a flexible substrate for emitting ultrasound waves and receiving echo signals from the bladder and intestines; a biocompatible flexible acoustic coupling layer detachably disposed between the flexible ultrasound sensor array and the skin for achieving stable acoustic coupling; and a signal processing and control module electrically connected to the flexible ultrasound sensor array for controlling... The ultrasonic transducer unit operates and processes the echo signal. The data acquisition and intelligent processing module is used to perform array beamforming control, extract multimodal features from the processed echo signal, and identify and classify excretion events based on the multimodal features using a machine learning model. The excretion events include at least two of the following: bladder fullness, urination, intestinal fecal accumulation, and defecation. The posture and movement sensing module is used to monitor the user's body posture and activity status. The wireless communication module is used to interact with external terminals. The power management module is used to supply power to the system.

[0007] Furthermore, the machine learning model is a deep learning model, configured to: receive the fused multimodal features as input, and output classification results for fecal excretion events and urinary excretion events; the deep learning model includes a hybrid structure of convolutional neural networks and recurrent neural networks, wherein the convolutional neural network is used to extract spatial features from the B-mode texture features, and the recurrent neural network is used to process the temporal data composed of the A-mode features and the Doppler mode features.

[0008] Furthermore, features generated from echo signals in A-mode imaging are used to estimate bladder depth or volume; features generated from echo signals in Doppler mode are used to detect fluid flow; and texture features generated from echo signals in B-mode imaging are used to characterize the structure of intestinal contents.

[0009] Furthermore, the posture and motion sensing module includes an inertial measurement unit and / or a tilt sensor, and the data acquisition and intelligent processing module is configured to dynamically adjust the beam emission angle and focusing area of ​​the ultrasonic waves according to the body posture.

[0010] Furthermore, the signal processing and control module includes a multiplexer for sequentially selecting the plurality of ultrasonic transducer units.

[0011] Furthermore, the power management module integrates a piezoelectric energy harvesting unit, which is used to convert the mechanical energy of human activity into electrical energy to replenish the battery.

[0012] Furthermore, the biocompatible flexible acoustic coupling layer is made of silicone hydrogel or polyurethane-based thermochromic gel material and has a semi-permeable structure.

[0013] A method for monitoring excretion, characterized by comprising the following steps:

[0014] Echo signals are acquired using the flexible ultrasonic sensor array.

[0015] Process the echo signal and extract multimodal features;

[0016] The multimodal features are input into a machine learning model to identify and classify excretion events;

[0017] The identification result is output through the wireless communication module.

[0018] Furthermore, before acquiring the signal, the posture and motion sensing module is used to determine whether the user is in a preset suitable measurement state; if so, signal acquisition is triggered.

[0019] Furthermore, based on the user's historical data and feedback information, the machine learning model is incrementally learned to optimize the recognition accuracy for that user.

[0020] This invention describes a wearable flexible ultrasound device for monitoring the excretion of the elderly and children. Its advantages include: By integrating a flexible ultrasound sensor array with a biocompatible acoustic coupling layer, the system achieves a comfortable and close fit to the skin, significantly improving the feasibility of long-term wear and user experience; utilizing phased array transducer units and advanced signal processing and control modules, the system can efficiently and accurately collect and process multimodal echo signals from the bladder and intestines, thereby achieving simultaneous monitoring and intelligent identification of various excretion conditions such as bladder fullness, urination events, intestinal fecal accumulation, and defecation events; combined with posture perception and adaptive beam control technology, the system maintains monitoring stability and accuracy under different user positions and movement states, effectively overcoming the problems of easy displacement and signal attenuation associated with traditional rigid devices; furthermore, the low-power power management design and wireless communication module support enable the system to operate continuously for extended periods and perform remote real-time data interaction, truly meeting the urgent needs of the elderly, children, and other special groups for unmanned, intelligent, and non-invasive continuous monitoring of their excretion health in daily life or medical care scenarios. Attached Figure Description

[0021] Figure 1 This is a system block diagram of an embodiment of the present utility model;

[0022] Figure 2 This is a schematic diagram of the bottom structure of the product according to an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of the top structure of a product according to an embodiment of this utility model.

[0024] Reference numerals: 1. Flexible substrate; 2. Flexible ultrasonic sensor array; 3. Biocompatible flexible acoustic coupling layer; 4. Signal processing and control module. Detailed Implementation

[0025] Typical embodiments embodying the features and advantages of this utility model will be described in detail in the following description. It should be understood that this utility model can have various variations in different embodiments, all of which do not depart from the scope of this utility model, and the descriptions and illustrations therein are for illustrative purposes only and not intended to limit this utility model.

[0026] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, 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 or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0027] To further illustrate the principle and structure of this utility model, the preferred embodiments of this utility model will now be described in detail with reference to the accompanying drawings.

[0028] like Figure 1-3 As shown in the figure, this utility model embodiment provides a wearable flexible ultrasound device for monitoring the excretion of the elderly and children, including: a wearable flexible ultrasound device for monitoring the excretion of the elderly and children. This system integrates flexible electronics, ultrasound imaging, signal processing, and artificial intelligence technologies, aiming to achieve dual, continuous, and accurate monitoring of bladder and bowel activities, and intelligently identify and classify excretion events.

[0029] To achieve the above objectives, the technical solution adopted by this utility model includes a system and a method.

[0030] In a first aspect, this utility model provides a wearable flexible ultrasound device for monitoring excretion, the system comprising:

[0031] Flexible substrate 1, made of polyimide or other biocompatible flexible polymer;

[0032] Flexible ultrasonic sensor array 2: This array is attached to the user's lower abdomen, covering the bladder and intestine projection area from the pubic symphysis to the upper abdomen. It comprises multiple (e.g., 16) independent ultrasonic transducer units arranged in a phased array and encapsulated on a flexible substrate 1, forming a generally flat, flexible patch structure. The transducer units are preferably microelectromechanical systems (MEMS) piezoelectric transducers or capacitive micromachining ultrasonic transducers (CMUTs), operating in the frequency range of 1 MHz to 10 MHz (preferably 2.5-4 MHz), ensuring both sufficient penetration depth and good resolution.

[0033] Biocompatible flexible acoustic coupling layer 3: detachably attached to the skin contact surface of the sensor array 2. This coupling layer 3 is made of medical-grade silicone, hydrogel, or polyurethane-based thermochromic gel material, with an acoustic impedance matched to human tissue. The layer is designed with a semi-permeable structure to maintain adequate moisture on the skin surface during prolonged wear, ensuring stable, low-loss transmission of ultrasound signals while avoiding skin irritation.

[0034] Signal processing and control module 4: Electrically connected to the sensor array 2, integrated into a flexible circuit board, and encapsulated in a waterproof housing. This module includes at least:

[0035] Multiplexer (F): Under the control of the processor, it sequentially selects different transducer units in the array for transmission or reception, so as to reduce the number of channels and reduce system complexity and power consumption.

[0036] High-voltage pulse generator (D): Used to generate high-voltage (e.g., 3.3V-200V) electrical pulses to excite selected transducer units to emit ultrasonic pulses.

[0037] Low-noise amplifier and time-gain compensation (TGC) circuit (M,L): used to amplify the received weak echo signal and compensate for the attenuation of ultrasound waves as they propagate through tissue with increasing depth.

[0038] Analog-to-digital converter (K): Converts analog echo signals into digital signals for processing.

[0039] Data Acquisition and Intelligent Processing Module: This is the core processing unit, comprising at least one processor (J) (such as a microcontroller (MCU) or FPGA) and memory (A, G). This module is configured to perform the following operations:

[0040] Array signal control and beamforming: Controlling the transmission delay of each unit in the phased array to achieve deflection and focusing of the ultrasonic beam, dynamically optimizing the scanning angle and area to adapt to the positional changes of the bladder and intestine under different body positions (acquired by posture sensor (B)).

[0041] Multimodal signal feature extraction: Processing digitized echo signals to extract various features, including:

[0042] A-mode ultrasound: Measure the time difference between the echoes from the anterior and posterior walls of the bladder, calculate the bladder depth, and estimate the urine volume.

[0043] Doppler mode: Analyzes the frequency shift of the echo signal to detect the flow of urine in the bladder and the movement of substances in the intestines, in order to determine urination events and intestinal peristalsis.

[0044] Brightness (B) mode: uses array scanning to acquire two-dimensional cross-sectional image information to help determine the accumulation status of intestinal contents (feces) (e.g., through echo intensity and texture features).

[0045] The intelligent excretion event recognition module is an artificial intelligence algorithm model (such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN / LSTM), or a hybrid model thereof) running on a processor or in the cloud. This model receives fused multimodal signal features (such as bladder volume change trends, Doppler blood flow / urination signals, and intestinal echo feature sequences), performs calculations, and outputs classification results, including: bladder fullness, urination events, intestinal fecal accumulation, intestinal peristalsis events, and defecation events, effectively distinguishing between defecation and urination events.

[0046] Attitude and Motion Sensing Module: Includes at least one inertial measurement unit (IMU) as a posture sensor (B) (such as a triaxial accelerometer, gyroscope) and / or tilt sensor for real-time monitoring of the user's body posture (e.g., standing, sitting, lying flat, side-lying) and activity status. This information is used to: 1) trigger or adjust ultrasonic measurement strategies (e.g., perform high-precision measurements when the user is stationary); 2) assist signal processing algorithms in identifying and filtering motion artifacts; and 3) provide guidance parameters for beamforming to ensure measurement accuracy.

[0047] Wireless communication module (C): Adopting a dual-mode design of Bluetooth Low Energy (BLE) and Wi-Fi, it is used to transmit processed status information, alarm signals and raw data (optional) to external terminal devices, such as smartphones, tablets, nurse station hosts or cloud servers.

[0048] The power management module (I) includes a rechargeable lithium battery or supercapacitor, along with corresponding charging management circuitry and a voltage converter. To extend battery life, the system supports energy clearing technologies, such as an integrated piezoelectric energy harvesting unit, which utilizes human activity to provide a small amount of energy to the battery. The processor (J) is configured to dynamically manage the operating modes of each module (e.g., active, sleep, intermittent operation) based on monitoring tasks and battery level, achieving ultra-low power consumption operation.

[0049] User feedback module: including miniature vibration motor, LED indicator and / or buzzer, used to provide tactile, visual or auditory alarms (such as bladder fullness reminder, urinary incontinence warning) to users or caregivers locally.

[0050] Secondly, this utility model provides a method for monitoring the excretion of the above-mentioned system, the method comprising the following steps:

[0051] S1. Device Wearing and Initialization: Secure the flexible ultrasound sensor array 2 to the user's lower abdomen using medical tape or a special abdominal binder, ensuring close contact between the coupling layer 3 and the skin. After powering on, the device performs a self-test and initialization calibration procedure, including determining the initial body position using a posture sensor and driving the ultrasound array to perform a preliminary scan to find the optimal signal receiving area and transducer combination.

[0052] S2. Signal Acquisition: The system operates in a low-duty-cycle intermittent mode. During each working cycle, the posture sensor continuously monitors the user's status. When measurement conditions are met (e.g., the user is stationary), the processor controls the multiplexer and high-voltage pulse generator to drive the selected transducer unit to emit ultrasonic pulses and receive reflected echo signals from the bladder and intestines.

[0053] S3. Signal Processing and Feature Fusion: The acquired raw echo signals are amplified, filtered, gain-compensated, and digitized. Then, the A-mode, Doppler, and B-mode information are processed in parallel or serially to extract multi-dimensional feature vectors, including time difference, frequency shift, echo intensity, texture features, and temporal variation patterns.

[0054] S4. Intelligent Recognition and Classification: The fused multi-dimensional feature vector is input into a pre-trained deep learning model. The model outputs the classification probability of the current state and / or the predicted event (e.g., "Bladder fullness 70%", "Urination detected", "Strong intestinal peristalsis detected", "High echo in colon area, suspected fecal accumulation").

[0055] S5. Data Transmission and Alarms: Identification results and key data are uploaded to external terminals and cloud platforms in real time via the wireless communication module. If preset alarm conditions are identified (such as bladder volume exceeding a threshold or detection of incontinence), the system will trigger the user feedback module locally and simultaneously send a remote alarm to the caregiver's terminal.

[0056] S6. Adaptive Learning and Optimization: The system continuously records measurement data, user feedback (such as confirmation / false alarms), and final discharge results. It uses this data to incrementally learn or fine-tune the local or cloud-based recognition model, thereby achieving personalized monitoring for specific users and continuously improving recognition accuracy.

[0057] The above description is merely a preferred embodiment of the present utility model and does not constitute any limitation on the technical scope of the present utility model. Therefore, any minor modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present utility model shall still fall within the scope of the technical solution of the present utility model.

Claims

1. A wearable flexible ultrasound device for monitoring excretion, characterized in that, include: A flexible ultrasound sensing array, configured to be attached to the user's lower abdomen, contains multiple ultrasound transducer units arranged in a phased array on a flexible substrate for emitting ultrasound waves and receiving echo signals from the bladder and intestines. A biocompatible flexible acoustic coupling layer is detachably disposed between the flexible ultrasound sensing array and the skin to achieve stable acoustic coupling; The signal processing and control module is electrically connected to the flexible ultrasonic sensor array and is used to control the operation of the ultrasonic transducer unit and process the echo signal. The data acquisition and intelligent processing module is used to perform array beamforming control, extract multimodal features from the processed echo signal, and identify and classify excretion events based on the multimodal features using a machine learning model. The excretion events include at least two of the following: bladder fullness, urination, intestinal fecal accumulation, and defecation. The posture and motion sensing module is used to monitor the user's body posture and activity status; The wireless communication module is used for data interaction with external terminals; The power management module is used to supply power to the system.

2. The excretion monitoring system of the wearable flexible ultrasound device according to claim 1, characterized in that, The machine learning model is a deep learning model, configured to: receive the fused multimodal features as input, and output the classification results of defecation events and urination events; the deep learning model includes a hybrid structure of convolutional neural networks and recurrent neural networks, wherein the convolutional neural network is used to extract spatial features from the B-mode texture features, and the recurrent neural network is used to process the temporal data composed of the A-mode features and the Doppler mode features.

3. The excretion monitoring system of the wearable flexible ultrasound device according to claim 1 or 2, characterized in that, Features generated from echo signals in A-mode ultrasound for estimating bladder depth or volume, features generated from echo signals in Doppler mode for detecting fluid flow, and texture features generated from echo signals in B-mode imaging for characterizing the structure of intestinal contents.

4. The wearable, flexible ultrasound device-based urinary monitoring system of claim 1, wherein, The posture and motion sensing module includes an inertial measurement unit and / or a tilt sensor, and the data acquisition and intelligent processing module is configured to dynamically adjust the beam emission angle and focusing area of ​​the ultrasonic waves according to the body posture.

5. The wearable, flexible ultrasound device-based urinary monitoring system of claim 1, wherein, The signal processing and control module includes a multiplexer for sequentially selecting the multiple ultrasonic transducer units.

6. The wearable, flexible ultrasound device-based urinary monitoring system of claim 1, wherein, The power management module integrates a piezoelectric energy acquisition unit, which is used to convert the mechanical energy of human activity into electrical energy to replenish the battery.

7. The wearable, flexible ultrasound device-based urinary monitoring system of claim 1, wherein, The biocompatible flexible acoustic coupling layer is made of silicone hydrogel or polyurethane-based thermochromic gel material and has a semi-permeable structure.

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