Flexible ultrasonic fingerstall for early screening of Parkinson's disease

Abstract

The invention discloses a flexible ultrasonic fingerstall for early screening of Parkinson's disease. The flexible ultrasonic fingerstall comprises a fingerstall body, a flexible ultrasonic transducer array, a signal processing module, a data transmission module, a power module and a control unit. The flexible ultrasonic transducer array emits ultrasonic signals and receives reflected signals, and the frequency and amplitude characteristics of finger tip tremor signals are extracted in real time through signal amplification, circuit analog-to-digital conversion and DSP processing. And a dynamic step size adaptive filtering algorithm and a spectrum analysis method are adopted to identify a tremor main mode and determine a tremor level. A detection result is transmitted to an intelligent terminal or a cloud end through the wireless module, so that remote monitoring and management are realized. The Parkinson's disease tremor early-stage non-invasive high-precision screening device has the advantages of being high in sensitivity, low in power consumption and comfortable to wear, can achieve early-stage non-invasive high-precision screening of Parkinson's disease tremor, and is suitable for home monitoring and clinical auxiliary diagnosis.

Description

Technical Field

[0001] The invention relates to a flexible ultrasonic finger cuff for early screening of Parkinson's disease, and belongs to the field of medical sensors. Background Art

[0002] Parkinson's disease (PD) is a common neurodegenerative disease characterized by symptoms such as resting tremor, muscle rigidity, bradykinesia, and postural instability. Finger tremor is one of the typical early symptoms of Parkinson's disease. Clinical studies have shown that early screening and accurate monitoring of fingertip tremor characteristics in Parkinson's patients can help with early intervention and course management of the disease. However, traditional Parkinson's disease diagnosis mainly relies on clinical evaluation by neurologists, which has problems such as strong subjectivity and insufficient detection sensitivity. Therefore, fingertip tremor detection methods based on physical sensing technology have received increasing attention and have become an important means to assist in the early screening of Parkinson's disease.

[0003] Currently, technologies for detecting fingertip tremor primarily include accelerometers, gyroscopes, electrophysiological signal analysis (such as electromyography (EMG), and computer vision tracking. Accelerometers and gyroscopes can assess tremor characteristics by measuring changes in acceleration or angular velocity during small finger movements. Electromyography (EMG) technology reflects the occurrence of tremor by recording the electrical signal activity of hand muscles, while computer vision technology uses high-frame-rate camera systems to analyze the trajectory of finger tremor. These methods have improved the objectivity and quantitative accuracy of detection to a certain extent, but they still face issues such as data susceptibility to environmental interference, discomfort with wearing the device, and insufficient real-time performance. However, there are currently no studies or reports on the direct application of ultrasonic transducers to detect fingertip tremor.

[0004] Existing ultrasonic transducer technology has been widely used in medical imaging, blood flow monitoring and other fields, but traditional ultrasonic systems have low integration and bulky equipment, making it difficult to achieve long-term, portable, real-time monitoring. In addition, traditional ultrasonic probes are usually based on hard piezoelectric materials (such as PZT, BTO ceramics, single crystals, etc.), which are difficult to adapt to complex curved structures such as fingers, affecting wearing comfort and measurement accuracy. Therefore, the development of a flexible ultrasonic finger cuff system with high-voltage electrical performance, high sensitivity, strong real-time performance and high portability to achieve high-precision monitoring of Parkinson's disease fingertip tremors is a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In order to solve the problems in the existing technology such as low integration of ultrasonic transducers, bulky equipment, difficulty in real-time monitoring of fingertip tremors, inconvenience in wearing traditional transducers, and inability to adapt to the complex curved surface structure of fingers, the purpose of the present invention is to provide a flexible ultrasonic finger cuff for fingertip tremor monitoring, which can achieve high-sensitivity, non-invasive, and real-time detection of fingertip tremors in Parkinson's patients. Compared with traditional detection methods, it has higher portability and adaptability, and is conducive to early screening and long-term monitoring of Parkinson's disease.

[0006] The object of the present invention is achieved through the following technical solutions:

[0007] The present invention discloses a flexible ultrasonic finger cuff for monitoring fingertip tremor, which includes a finger cuff body, a flexible ultrasonic transducer array, a signal processing module, a data transmission module and a power supply module. The finger cuff body is made of highly elastic biocompatible material and conforms to ergonomic design to ensure comfort for long-term wear and adapt to different finger sizes. The flexible ultrasonic transducer array is integrated into the inner side of the finger cuff and arranged in an array form. It can fit the skin surface of the fingertip and achieve high-precision detection of tiny fingertip tremors. The signal processing module is responsible for driving the transducer and processing the received signal, and extracts tremor characteristic parameters such as tremor frequency and amplitude through an adaptive filtering algorithm. The data transmission module adopts wireless communication (such as Bluetooth or Wi-Fi) to transmit real-time data to an intelligent terminal to achieve remote monitoring and data storage. The power supply module adopts a micro rechargeable battery or wireless power supply to ensure portability and stability for long-term use.

[0008] The present invention discloses a flexible ultrasonic finger cuff for early screening of Parkinson's disease. The flexible ultrasonic transducer array is embedded in the inner surface of the finger cuff body and is composed of a piezoelectric composite material and a serpentine electrode. The transducer array is connected to a signal processing module disposed on the upper portion of the finger cuff body via flexible wiring. The signal processing module is connected to a control unit, which forms an electrical connection loop with a data transmission module and a power supply module. Each functional module is arranged inside the finger cuff via flexible wires and is covered and fixed by an encapsulation layer to form an integrated structure.

[0009] The flexible ultrasonic transducer array is used to transmit ultrasonic signals and detect reflected signals, enabling highly sensitive acquisition and tracking of micro-displacement changes caused by fingertip tremors, providing raw data for subsequent tremor feature extraction and analysis.

[0010] The signal processing module includes a pulse excitation circuit that drives the flexible ultrasonic transducer array to emit ultrasonic signals. The received reflected signals are then amplified by the signal amplification circuit and input into the analog-to-digital conversion unit ADC for digital sampling processing. The digital signals are then transmitted to the digital signal processing unit DSP for vibration analysis.

[0011] The data transmission module is used for data transmission and supports remote monitoring;

[0012] The control unit is used to coordinate the workflow of the signal processing and data transmission modules, and realize the excitation tuning of the flexible ultrasonic transducer array by controlling the pulse excitation circuit.

[0013] After the reflected signal is received by the ultrasonic transducer array, it is sampled by the signal amplification circuit and the analog-to-digital converter (ADC) to form the original fingertip displacement waveform. This signal is input to the digital signal processing unit (DSP), where the main modal signal is extracted through a dynamic step-size LMS adaptive filter and further spectrum analysis is performed to finally complete the tremor level determination, including the following steps:

[0014] Step 1: Original signal acquisition and structural modeling, and generation of original fingertip displacement waveform;

[0015] 1.1. Receive ultrasonic reflection signals through the flexible ultrasonic transducer array;

[0016] 1.2. After the ultrasonic reflection signal is amplified by the signal amplifier circuit and then sampled and processed by the analog-to-digital conversion unit ADC, the original fingertip displacement waveform can be obtained, that is, the original input signal waveform structure function:

[0017] x(n)=s(n)+d(n)+η(n) (1)

[0018] Where x(n) is the current sampling signal; s(n) is the main modal component, which shows periodic fluctuations; d(n) is the low-frequency trend term; η(n) is the superimposed high-frequency noise; the variable n represents the sampling index number in the discrete time series, and the unit is the number of sampling points; if the sampling frequency of the system is fs, then the physical time corresponding to the sampling index number is

[0019] Step 2: Construct an LMS adaptive filter based on dynamic step size adjustment to extract the main mode;

[0020] 2.1. LMS adaptive filter structure construction

[0021] The input vector of the filter is constructed using a delay and is expressed as:

[0022] x n =[x(nD),x(nD-1),…,x(nD-K+1)] T (2)

[0023] Where D is the input delay; L is the filter order;

[0024] The output of the filter at the current moment is expressed as:

[0025] y(n)=w T (n)·x n (3)

[0026] Among them, w(n) is the weight vector at the current moment; w T (n) is the transpose of w(n); y(n) is the filter output at the current moment, that is, the main modal signal currently estimated by the system.

[0027] 2.2. Error calculation:

[0028] e(n)=x(n)-y(n) (4)

[0029] Among them, the error e(n) is the deviation between the main modal signal of the current filter and the true input signal. The error is used to "correct" the filter parameters at the next moment.

[0030] 2.3. Dynamic adjustment step size:

[0031]

[0032] Where μ(n) is the current step size, which is adaptively adjusted according to the square of the error e(n); μ0 is the initial step size constant; and α is the error gain adjustment coefficient, which controls the response of the learning rate to the error sensitivity.

[0033] 2.4. The update expression of weight vector at the next moment:

[0034] w(n+1)=w(c)+μ(n)·e(n)·x n (6)

[0035] Substitute the updated w(n+1) in equation (6) into equation (3) to obtain the output y(n+1) of the next filtering moment.

[0036] 2.5. Judgment of convergence control mechanism and determination of main modal signal:

[0037] ΔE(n)=|e 2 (n+1)-e 2 (n)| (7)

[0038] When ΔE(n)<ε, w(n+1) is the final weight vector. Substituting w(n+1) into equation (3) yields the final primary modal signal y(n). At this point, the weight vector w(n) can be stopped from being updated.

[0039] Where ε is the judgment threshold of error convergence; ΔE(n) is the error change; e(n+1) is y(n+1) Substituting into formula (4) we get

[0040] Step 3: Determine the tremor grade

[0041] 3.1、Obtain the spectrum representation of y(n) through fast Fourier transform FFT:

[0042]

[0043] Where N is the total number of sampling points; fs is the system sampling frequency; f k is the frequency corresponding to the point (unit: Hz); k is the frequency index.

[0044] Extract the main and secondary frequency positions and record the main and secondary frequency energy ratios:

[0045]

[0046] Among them, f max is the frequency with the highest amplitude of |Y(f)|; fsub is the second highest frequency of |Y(f)| amplitude extracted by additional extreme point search method; r is the energy ratio of primary and secondary frequencies, which measures the concentration of the tremor spectrum.

[0047] 3.2. Extract two key features:

[0048] ① Extreme value difference:

[0049] A P2P =max(y(n))-min(y(n)) (11)②Root mean square value:

[0050]

[0051] Among them, AP2P mainly reflects the instantaneous characteristics of the extreme value of the main modal signal, and ARMS is used to describe the energy stability of the amplitude; 3.3. Determine the tremor level:

[0052] When the ratio of primary and secondary frequency energy is greater than 0.5, it is judged that there is no tremor. When r is less than 0.5, the AP2P and ARMS dual indicators are combined to further judge the tremor level:

[0053] If AP2P<30μm and ARMS<10μm: output “mild tremor”;

[0054] If AP2P is between 30–60 μm or ARMS is between 10–20 μm: output “moderate tremor”;

[0055] If AP2P>60μm or A RMS >20μm: output “severe tremor”;

[0056] Furthermore, the flexible ultrasonic finger cuff for early screening of Parkinson's disease, the flexible ultrasonic transducer array is integrally formed using a flexible piezoelectric composite material, wherein the piezoelectric phase is selected from PZT-5H, PMN-PT or potassium sodium niobate KNN, and the matrix phase is selected from PDMS, PVDF or its copolymer, to ensure d33 >400pC / N, dielectric loss less than 0.02, coupling coefficient k t Greater than 0.5;

[0057] Furthermore, in the flexible ultrasonic finger cuff for early screening of Parkinson's disease, the flexible ultrasonic transducer array may be arranged in a 4×4, 6×6, or 8×8 matrix, and the transducer units are interconnected by serpentine electrodes;

[0058] Furthermore, the finger sleeve body is made of medical-grade high-elasticity silicone or polyurethane material with a thickness of 0.5mm to 1.5mm. The inner surface is provided with a non-slip microstructure and is suitable for fingers with a diameter range of 15mm to 25mm.

[0059] Furthermore, the flexible ultrasonic transducer array adopts 1-3 type or 2-2 type piezoelectric composite material, with a center frequency of 5MHz to 10MHz and a unit size of 1mm×1mm to 3mm×3mm.

[0060] Furthermore, the data transmission module uses Bluetooth Low Energy (BLE 5.0) or Wi-Fi 6 to achieve data transmission within a range of 10m to 30m and supports remote monitoring;

[0061] Furthermore, the power module uses a micro rechargeable lithium battery (3.7V, 50mAh to 200mAh), supports wireless charging or Type-C charging, and has intelligent power consumption management function;

[0062] Furthermore, the pulse excitation circuit of the signal processing module can provide an adjustable drive signal of 10V to 50V to optimize the transducer excitation effect. After the received signal is processed by low-noise amplification, it is sampled by the ADC at a rate of more than 10MSPS to ensure accurate capture of the vibration signal;

[0063] Furthermore, the data transmission module integrates a low-power data compression algorithm, supports AES encryption, and has a transmission rate of up to 2Mbps to reduce data delay and improve security;

[0064] Furthermore, the power module is equipped with a low-power management circuit, which automatically enters a low-power mode (power consumption <10μW) when the transducer is not working to extend battery life and supports remote power monitoring and low-battery reminder functions;

[0065] Furthermore, the finger cuff body reserves a transducer window area, and the window thickness is reduced to 0.3mm to 0.8mm to reduce ultrasonic signal energy loss and improve detection sensitivity;

[0066] The present invention discloses a method for preparing a flexible ultrasonic finger cuff for early screening of Parkinson's disease, comprising the following steps:

[0067] S1. Preparation of flexible ultrasonic transducer array;

[0068] Step 1.1, using a 1-3 type or 2-2 type piezoelectric composite material to form a transducer unit through a flexible template process;

[0069] Step 1.2: Depositing flexible metal electrodes on the transducer surface and forming a serpentine electrode structure through photolithography and etching processes;

[0070] Step 1.3, using Parylene or PDMS for packaging to form a flexible ultrasonic transducer array;

[0071] S2, preparing the finger sleeve body;

[0072] Step 2.1, using medical grade silicone or polyurethane material for mold forming and forming a non-slip microstructure;

[0073] Step 2.2: Reserve a transducer window area on the inner surface of the finger cuff and control the thickness of the window;

[0074] S3, assembly;

[0075] Step 3.1, embed the transducer array into the cuff body and connect it to the signal processing module via a flexible PCB;

[0076] Step 3.2: Assemble the signal processing module, power module, and data transmission module, and package and fix them;

[0077] S4, system debugging;

[0078] Step 4.1, perform transducer excitation test and optimize transducer excitation voltage and operating frequency;

[0079] Step 4.2: Perform wireless communication debugging to ensure data transmission stability; perform overall system calibration and verify the accuracy and stability of tremor detection.

[0080] Beneficial effects:

[0081] 1. The present invention discloses a flexible ultrasonic finger cuff for early screening of Parkinson's disease. It uses an ultrasonic transducer array integrally formed from a flexible piezoelectric composite material. Compared with traditional rigid ultrasonic probes, this can conform to the complex curved surfaces of the fingertips, improve the coupling efficiency and detection sensitivity of tremor signals, and achieve more accurate real-time monitoring.

[0082] 2. The present invention discloses a flexible ultrasonic finger cuff for early screening of Parkinson's disease, which integrates a high-frequency (5MHz to 10MHz) ultrasonic transducer array and can detect fingertip tremor displacement at the micron level. Compared with traditional accelerometers and gyroscopes, the detection accuracy is improved by at least one order of magnitude, and is suitable for monitoring small abnormal changes in the early stages of tremor.

[0083] 3. The flexible ultrasonic finger cuff disclosed in the present invention is used for early screening of Parkinson's disease. The cuff body is made of highly elastic biocompatible materials and is equipped with a low-power wireless data transmission module to provide a non-invasive, small, comfortable, and portable long-term monitoring solution, breaking through the technical bottleneck of existing ultrasonic equipment that is bulky and uncomfortable to wear.

[0084] 4. The flexible ultrasonic finger cuff disclosed in the present invention for early screening of Parkinson's disease innovatively applies flexible ultrasonic technology to fingertip tremor detection, breaking through the current technical gap in the direct use of ultrasonic transducers for tremor monitoring, and providing a new highly sensitive, non-invasive, wearable solution for early screening of Parkinson's disease.

[0085] 5. This invention discloses a flexible ultrasonic finger cuff for early screening of Parkinson's disease. Its tremor processing algorithm utilizes a delayed-structured LMS adaptive filtering method, combined with spectrum analysis and amplitude determination, to achieve real-time extraction and automatic grading of fingertip tremor frequency and intensity in Parkinson's patients. Compared to traditional detection methods that rely on manual analysis, this invention can extract the dominant tremor frequency and identify its grade on a low-power DSP platform. It offers the advantages of high precision, deployability, quantification, and intelligence, significantly enhancing the automatic identification capabilities and clinical practicality of Parkinson's disease early screening systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 Schematic diagram of the overall structure of the flexible ultrasonic finger cuff proposed in the present invention;

[0087] Figure 2 This is a schematic diagram of the three-dimensional structure of the flexible ultrasonic finger cuff body 1 proposed by the present invention;

[0088] Figure 3 This is a schematic diagram of the three-dimensional structure of the ultrasonic transducer array 2 of the flexible ultrasonic cuff proposed in the present invention;

[0089] Figure 4 Schematic diagram of the processing process of the adaptive filtering algorithm proposed in the present invention, where (a) is the waveform of the original input signal after acquisition; (b) is the main modal signal after filtering; and (c) is the spectrum analysis diagram of the main modal signal.

[0090] Figure 5 Schematic diagram of the data transmission module 4 and remote monitoring of the present invention;

[0091] Figure 6 This is a diagram of the overall system architecture of the flexible ultrasonic cuff proposed in the present invention.

[0092] In the figure, 1 is the finger cuff body, 2 is the flexible ultrasonic transducer array, 3 is the signal processing module, 4 is the data transmission module, 5 is the power module, 6 is the control unit, 7 is the packaging layer, 8 is the piezoelectric composite material, and 9 is the snaking electrode. DETAILED DESCRIPTION

[0093] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments and the accompanying drawings.

[0094] Example 1

[0095] like Figure 1 As shown, this embodiment discloses a flexible ultrasonic finger cuff for early screening of Parkinson's disease. This device uses a highly sensitive ultrasonic transducer to monitor fingertip tremor in real time, enabling portable, non-invasive, and highly accurate Parkinson's disease screening and long-term follow-up. The device comprises a finger cuff body 1, a flexible ultrasonic transducer array 2, a signal processing module 3, a data transmission module 4, a power supply module 5, and a control unit 6. These modules work together to ensure efficient and stable operation.

[0096] like Figure 1 The overall structural diagram of the flexible ultrasonic finger cuff is shown. A flexible ultrasonic transducer array 2 is embedded in the finger cuff body 1, which is integrally formed using a flexible piezoelectric composite material, and the transducer unit fits tightly to the skin of the fingertip. Each array unit of the flexible ultrasonic transducer array 2 is connected to the signal acquisition path through a flexible metal electrode (Ag-PDMS or Au-PI film), ensuring that the ultrasonic signal received by the flexible ultrasonic transducer array 2 can be stably transmitted to the signal processing module 3. The entire flexible ultrasonic transducer array 2 is connected to the signal processing module 3 through a flexible FPCB, so that the flexible ultrasonic transducer array 2 can still maintain stable electrical signal transmission in a bent state. The pulse excitation circuit of the signal processing module 3 is connected to the flexible ultrasonic transducer array 2 through a micro coaxial cable or a flexible FPCB, providing an adjustable 10V to 50V high-frequency pulse to drive ultrasonic emission.

[0097] Ultrasonic echo signals received by the flexible ultrasonic transducer array 2 are processed by a low-noise signal amplifier and then transmitted through a shielded flexible FPCB to an analog-to-digital converter (ADC) for digitization. The signal transmission path utilizes a double-layer flexible PCB shielding structure to reduce external electromagnetic interference and ensure stable data transmission with low noise.

[0098] The tremor data processed by the DSP of the signal processing module 3 is transmitted via SPI or I 2The C bus is transmitted to the data transmission module 4 to optimize the data transmission rate and power consumption. The clock synchronization interface uses a low-power oscillator to ensure the clock synchronization between the DSP and the data transmission module 4, improving data stability.

[0099] Data transmission module 4 is responsible for wirelessly transmitting the processed vibration signal to a smart terminal (such as a mobile phone, computer, or medical monitoring system). The wireless communication interface uses a BLE 5.0 or Wi-Fi 6 module, and the built-in antenna is integrated on the outside of the cuff body to avoid interference with the operation of the flexible ultrasonic transducer array 2.

[0100] Power module 5 uses a micro rechargeable lithium battery (3.7V, 50-200mAh), which supplies power to various subsystems via a power management chip (PMIC). Flexible ultrasonic transducer array 2 is powered by a low-noise LDO (low-dropout voltage regulator) providing a stable 3.3V to 10V DC voltage, ensuring efficient operation. A dual-channel 1.8V and 3.3V regulated power supply is used for the DSP and ADC, ensuring low power consumption and high-precision data processing.

[0101] The control unit 6 is responsible for managing the entire system and ensuring the coordinated operation of each module: MCU 2 The C interface controls the excitation, signal acquisition, and transmission modes of the flexible ultrasonic transducer array 2. The BLE / Wi-Fi module interacts with the MCU via UART for data storage and remote communication. Touch or vibration feedback interface (optional): The finger cuff can be integrated with a micro touch sensor or vibration feedback device to provide real-time monitoring feedback.

[0102] The outer structure of the fingertip main body 1 proposed by the present invention is as follows Figure 2As shown. The finger cuff body 1 is made of medical-grade high-elasticity silicone (Silicone) or polyurethane (PU) material, with a thickness controlled at 0.5mm to 1.5mm to ensure softness and comfort when wearing. It also has good biocompatibility and is suitable for long-term wear. This material is low-irritating, non-toxic and water-resistant, which can effectively reduce the risk of skin allergies or discomfort and ensure medical-grade safety. The inside of the finger cuff body 1 adopts a microstructured anti-slip layer design, which can enhance skin fit through micron-level textures to prevent the signal stability from being affected by the sliding of the finger cuff during the detection process. In addition, the finger cuff body reserves a transducer window in the area of the flexible ultrasonic transducer array 2, and the thickness of this area is slightly reduced (0.3mm to 0.8mm) to reduce the energy loss of the ultrasonic signal and improve the detection sensitivity. The size of the finger cuff can be adjusted according to different finger diameters and is suitable for fingers with diameters of 15mm to 25mm. At the same time, a microstructured anti-slip layer is provided inside the finger cuff to enhance skin fit and avoid signal interference caused by the sliding of the finger cuff. The use of flexible materials makes the device suitable for users of different ages and hand sizes, and can be worn for long periods of time without affecting daily activities.

[0103] Figure 3 A specific structural scheme for a flexible ultrasonic transducer array 2 is presented. The flexible ultrasonic transducer array 2 is integrated inside the fingertip and is made of a 1-3 or 2-2 piezoelectric composite material. In one specific example, the flexible ultrasonic transducer array 2 comprises an encapsulation layer 7, a piezoelectric composite material 8, and a serpentine electrode 9. The encapsulation layer 7, made of a biocompatible polymer (such as PDMS or Parylene), protects the piezoelectric composite material 8 from external humidity, mechanical stress, and electromagnetic interference, while ensuring efficient transmission of ultrasound waves. The piezoelectric composite material 8 utilizes a 1-3 or 2-2 flexible piezoelectric composite structure, with the piezoelectric phase being PZT-5H or PMN-PT and the matrix being PVDF or PDMS, ensuring a high piezoelectric constant (d33 > 400 pC / N) and good flexibility matching. The serpentine electrode 9, composed of a flexible metal (such as Ag-PI or Au-PI), adopts a stretchable serpentine structure that not only adapts to fingertip bending and deformation but also ensures stable transmission of electrical signals, improving the detection sensitivity of tremor signals.

[0104] The transducer's center frequency can be set between 5MHz and 10MHz, and its unit size ranges from 1mm×1mm to 3mm×3mm. Specific arrangements include 4×4, 6×6, or 8×8 arrays to accommodate different detection requirements. The flexible ultrasonic transducer array 2 is interconnected by flexible electrodes, ensuring good signal transmission even on the complex curved surfaces of the finger.

[0105] Signal processing module 3 consists of a pulse excitation circuit, a signal amplification circuit, an analog-to-digital converter (ADC), and a digital signal processing unit (DSP). The pulse excitation circuit provides an adjustable 10V-50V drive signal to optimize the ultrasonic excitation effect. The received vibration signal undergoes low-noise amplification (noise less than 1nV / √Hz) and is then digitized with high precision by a 16-bit ADC at a sampling rate exceeding 10MSPS. The DSP uses an adaptive filtering algorithm to remove low-frequency interference generated by autonomous finger movement in real time and extract the frequency (4Hz-12Hz) and amplitude (micrometer level) of fingertip tremors.

[0106] The data transmission module 4 supports Bluetooth low energy (BLE 5.0) or Wi-Fi 6, with a transmission rate of up to 2Mbps. It can stably transmit tremor data to smartphones, tablets or cloud servers within a range of 10m to 30m. Its basic principle structure is as follows Figure 5 The data transmission module also adopts an intelligent data compression algorithm to effectively reduce the amount of data and improve transmission efficiency, while integrating the AES encryption protocol to ensure data security.

[0107] The power module 5 uses a micro rechargeable lithium battery (3.7V, 50mAh-200mAh) and supports wireless charging (Qi standard) or USB Type-C charging. A full charge provides 6-12 hours of continuous operation. The power management unit (PMU) can enter sleep mode (power consumption <10μW) when the device is not in operation, effectively extending the device's battery life. Furthermore, the power module can interact with smart terminals via the data transmission module, enabling remote power monitoring and low-battery reminders.

[0108] The control unit 6, a low-power microcontroller (MCU), coordinates the flexible ultrasonic transducer array 2, signal processing, and data transmission workflow. The MCU features a mode switching function, allowing it to flexibly switch between vibration detection mode, data storage mode, and standby mode, ensuring efficient device operation.

[0109] The present invention provides a further connection scheme for each component in the flexible ultrasonic finger cuff, such as Figure 6 As shown. The flexible ultrasonic finger cuff of the present invention consists of a finger cuff body 1, a flexible ultrasonic transducer array 2, a signal processing module 3, a data transmission module 4, a power supply module 5 and a control unit 6. Each module is connected through a flexible circuit (FPCB), a micro coaxial cable and a wireless communication interface to achieve efficient and stable data transmission and signal processing. The flexible ultrasonic transducer array 2 is embedded in the finger cuff body 1 and is connected to the signal processing module 3 through a flexible electrode (Ag-PDMS or Au-PI) for receiving and processing the vibration signal. The signal processing module 3 is connected through I 2C or SPI bus interacts with data transmission module 4, transmitting processed tremor data to a smart terminal (mobile phone / cloud) via BLE 5.0 or Wi-Fi 6. Power module 5 is powered by a 3.7V lithium battery and provides stable power to each module through a low-power management circuit (PMIC). Control unit 6 manages signal acquisition, mode switching, and wireless transmission to ensure efficient device operation.

[0110] Example 2

[0111] The user first places the fingertip on their index or middle finger, ensuring that the flexible ultrasonic transducer array 2 is in close contact with the skin surface of the fingertip. After the device is turned on, the MCU in the control unit 6 initiates the transducer adaptive calibration process. By controlling the pulse excitation circuit, it adjusts the excitation voltage (adjustable from 10V to 50V) and the operating frequency of the flexible ultrasonic transducer array 2 (5 to 10MHz) to match the physiological characteristics of different users' fingertips and optimize the ultrasonic echo signal acquisition effect.

[0112] The MCU controls the flexible ultrasonic transducer array 2 to transmit high-frequency pulsed ultrasound waves while simultaneously receiving the reflected signals from the fingertip tissue in real time. After low-noise amplification, the reflected signals are transmitted to the analog-to-digital converter (ADC) for high-precision sampling at a rate exceeding 10 MSPS to generate the time-domain tremor input signal x(n). The DSP subsystem of the signal processing module 3 processes x(n) in real time, extracting the main modal components of the tremor using an LMS adaptive filtering algorithm with dynamic step size adjustment.

[0113] like Figure 4 As shown in (a), the first stage involves the acquisition of the raw input signal. The sampled raw signal x(n) contains the target tremor main frequency component (4–12 Hz), low-frequency posture changes (<2 Hz), and high-frequency electronic noise (>15 Hz).

[0114] like Figure 4 As shown in Figure (b), the second stage involves adaptive filtering to extract the primary modal signal. Through dynamic-step LMS adaptive filtering, the output primary modal signal y(n) exhibits clear tremor rhythm characteristics in the time domain, while low-frequency drift and high-frequency noise are effectively suppressed, preserving the true tremor component of the fingertip.

[0115] like Figure 4 As shown in (c), the third stage is frequency domain feature extraction. The main modal signal y(n) is subjected to fast Fourier transform (FFT) spectrum analysis to obtain the main frequency peak f max =6.0Hz, the main frequency corresponds to an amplitude of 19.99μm. At the same time, the secondary main frequency f sub =7.4Hz, and the secondary frequency amplitude is 4.28μm.

[0116] According to the calculation formula of the main and secondary frequency energy ratio r:

[0117]

[0118] Since r<0.5, it was preliminarily determined that there was a significant tremor feature.

[0119] Further extract the time domain amplitude characteristic indicators:

[0120] A P2P =max(y(n))-min(y(n))=64.06um

[0121] According to the comprehensive tremor determination rules, the test results are:

[0122] r≈0.21, obvious tremor; A P2P A value >60μm is considered severe tremor. Therefore, the system automatically outputs the tremor level as severe tremor.

[0123] The entire tremor signal processing, feature extraction, and grading process is completed in real time on the DSP platform. After testing, the tremor frequency, amplitude, primary-to-secondary frequency ratio, and grade determination results are wirelessly transmitted to a smart terminal via BLE 5.0 or Wi-Fi 6 via the data transmission module 4, allowing users to view them in real time via the accompanying app. Tremor data can also be uploaded to a cloud server, allowing doctors to remotely assess a patient's long-term tremor trends. When testing is completed or if no testing is performed for an extended period, the control unit 6 switches to a low-power standby mode, retaining only essential communication functions to extend battery life.

[0124] This embodiment shows that the flexible ultrasonic finger cuff system proposed in the present invention can achieve high-precision, low-power, intelligent fingertip tremor detection and automatic judgment in an actual wearing environment, and has good application prospects for early screening and home monitoring.

[0125] The flexible ultrasonic finger cuff of the present invention has significant innovation and technical advantages over existing tremor detection methods. First, in terms of detection accuracy, compared with traditional accelerometers and gyroscopes, the present invention uses ultrasonic transducers to detect micron-level tremor displacements, and the detection sensitivity is improved by an order of magnitude. It can identify early subtle changes in tremor in Parkinson's patients and provide high-precision data support for early screening of the disease. Second, in terms of comfort and portability, the ultrasonic transducer array made of flexible piezoelectric composite materials is integrated with the flexible biocompatible material finger cuff, so that the device can perfectly fit the finger curve and achieve long-term non-invasive wear. Compared with traditional rigid ultrasound probes, it greatly improves user comfort and adaptability. In addition, in terms of data transmission and remote monitoring, the device supports low-power Bluetooth (BLE 5.0) or Wi-Fi 6, realizing wireless data interaction with smartphones, tablets or cloud servers, supporting remote real-time monitoring, allowing doctors and patients to obtain test results anytime and anywhere, and conduct long-term trend analysis, improving the convenience of disease management.

[0126] The present invention also has unique advantages in intelligent signal processing. It uses adaptive filtering algorithms and DSP processing units to effectively eliminate autonomous hand movements and external environmental noise, thereby improving the reliability and accuracy of the data. Traditional electromyography (EMG) methods are easily affected by changes in skin conductivity and poor electrode contact. The present invention obtains mechanical vibration signals through ultrasonic transducers, avoiding this problem and making the detection results more stable. In addition, in terms of low-power management and battery life, the present invention adopts an efficient power management system. The device can automatically enter low-power mode when not in operation to reduce energy consumption. At the same time, it supports long-term use through wireless charging or Type-C charging. It can work continuously for 6 to 12 hours when fully charged, meeting daily monitoring needs.

[0127] The flexible ultrasonic finger cuff of this invention is suitable for use in hospitals, rehabilitation centers, and home health management, providing accurate Parkinson's disease screening and long-term monitoring. This device overcomes the limitations of existing technologies, filling a technological gap in ultrasonic transducers for fingertip tremor detection. It has broad clinical application value and market prospects, providing important technical support for future smart healthcare, wearable health monitoring, and neurological disease diagnosis.

[0128] Compared to traditional accelerometers, gyroscopes, and electromyography (EMG) detection technologies, the flexible ultrasonic finger cuff of this invention offers significant advantages in detection accuracy, wearing comfort, anti-interference capabilities, and remote monitoring. The following table compares the key technical indicators of this invention with existing technologies to highlight its innovation and application value.

[0129] Table 1. Comparison of the flexible ultrasonic finger cuff proposed by the present invention and the prior art

[0130]

[0131] The above specific description further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A flexible ultrasonic finger cuff for early screening of Parkinson's disease, characterized by: A flexible ultrasonic transducer array is embedded in the inner surface of the cuff body and is composed of a piezoelectric composite material and serpentine electrodes. The transducer array is connected to a signal processing module located on the upper portion of the cuff body via flexible wiring. The signal processing module is connected to a control unit, which forms an electrical connection loop with the data transmission module and the power supply module. Each functional module is arranged inside the cuff via flexible wires and is covered and fixed by an encapsulation layer, forming an integrated structure. The flexible ultrasonic transducer array is used to transmit ultrasonic signals and detect reflected signals, enabling highly sensitive acquisition and tracking of micro-displacement changes caused by fingertip tremors, providing raw data for subsequent tremor feature extraction and analysis. The signal processing module includes a pulse excitation circuit that drives the flexible ultrasonic transducer array to emit ultrasonic signals. The received reflected signals are then amplified by the signal amplification circuit and input into the analog-to-digital conversion unit ADC for digital sampling processing. The digital signal is then transmitted to the digital signal processing unit DSP for performing vibration analysis on the signal; The data transmission module is used for data transmission and supports remote monitoring; The control unit is used to coordinate the workflow of the signal processing and data transmission modules, and realize the excitation tuning of the flexible ultrasonic transducer array by controlling the pulse excitation circuit.

2. A flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 1, characterized in that: After being received by the ultrasonic transducer array, the reflected signal is sampled by the signal amplification circuit and the analog-to-digital conversion unit (ADC) to form the original fingertip displacement waveform. This signal is then input into the digital signal processing unit (DSP), where the main modal signal is extracted using a dynamic step-size LMS adaptive filter. Further spectrum analysis is performed to determine the tremor level. The specific implementation method includes the following steps: Step 1: Original signal acquisition and structural modeling, and generation of original fingertip displacement waveform 1.

1. Receive ultrasonic reflection signals through the flexible ultrasonic transducer array; 1.

2. After the ultrasonic reflection signal is amplified by the signal amplifier circuit and then sampled and processed by the analog-to-digital conversion unit ADC, the original fingertip displacement waveform can be obtained, that is, the original input signal waveform structure function: x(n)=s(n)+d(n)+η(n) (1) Where x(n) is the sampling signal at the current moment; s(n) is the main modal component, which shows periodic fluctuations; d(n) is the low-frequency trend term; η(n) is the superimposed high-frequency noise; the variable n represents the sampling index number in the discrete time series, and the unit is the number of sampling points; if the sampling frequency of the system is f s , then the physical time corresponding to the sampling index number is Step 2: Construct an LMS adaptive filter based on dynamic step size adjustment to extract the main mode 2.

1. Construct LMS adaptive filter structure; The input vector of the filter is constructed using a delay and is expressed as: x n =[x(nD),x(nD-1),…,x(nD-L+1)] T (2) Where D is the input delay; L is the filter order; The output of the filter at the current moment is expressed as: y(n)=w T (n)·x n (3) Among them, w(n) is the weight vector at the current moment; w T (n) is the transpose of w(n); y(n) is the filter output at the current moment, that is, the main modal signal currently estimated by the system; 2.

2. Error calculation: e(n)=x(n)-y(n) (4) Among them, the error e(n) is the deviation between the main modal signal of the current filter and the true input signal. The error is used to "correct" the filter parameters at the next moment; 2.

3. Dynamic adjustment step size: Where μ(n) is the current step size, which is adaptively adjusted according to the square of the error e(n); μ0 is the initial step size constant; α is the error gain adjustment coefficient, which controls the response of the learning rate to the error sensitivity; 2.

4. The update expression of weight vector at the next moment: w(n+1)=w(n)+μ(n)·e(n)·x n (6) Substitute the updated w(n+1) in formula (6) into formula (3) to obtain the output y(n+1) of the next filtering moment; 2.

5. Convergence control mechanism judgment and main modal signal determination: ΔE(n)=|e 2 (n+1)-e 2 (n)| (7) When ΔE(n)<ε, w(n+1) is the final weight vector. Substituting w(n+1) into equation (3) yields the final primary modal signal y(n). At this point, the weight vector w(n) can be stopped from being updated. Among them, ε is the judgment threshold of error convergence; ΔE(n) is the error change; e(n+1) is obtained by substituting y(n+1) into formula (4); Step 3: Determine the tremor grade 3.1、Obtain the spectrum representation of y(n) through fast Fourier transform FFT: Where N is the total number of sampling points; f s is the system sampling frequency; f k is the frequency corresponding to the point; k is the frequency index; Extract the main and secondary frequency positions and record the main and secondary frequency energy ratios: Among them, f max is the frequency with the highest amplitude of |Y(f)|; f sub In order to additionally adopt the extreme point search method, the second high frequency of the |Y(f)| amplitude is extracted; r is the energy ratio of the primary and secondary frequencies, which measures the concentration of the tremor spectrum; 3.

2. Extract two key features: ① Extreme value difference: HAS P2P =max(y(n))-min(y(n)) (11) ②Root mean square value: Among them, A P2P Mainly reflects the instantaneous characteristics of the extreme value of the main mode signal, A RMS Used to describe the energy stability of the amplitude; 3.

3. Determine the level of tremor: When the energy ratio of the main and secondary frequencies is r>0.5, it is judged that there is no tremor. When r≦0.5, it is combined with A P2P and A RMS Two indicators are used to further determine the tremor grade: If A P2P <30μm and A RMS <10μm: output "mild tremor"; If A P2P Between 30–60 μm or A RMS Between 10–20 μm: output "moderate tremor"; If A P2P >60μm or A RMS >20μm: Output "Severe Tremor".

3. The flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 2, characterized in that: The flexible ultrasonic transducer array is formed in one piece using a flexible piezoelectric composite material, wherein the piezoelectric phase is selected from PZT-5H, PMN-PT or potassium sodium niobate KNN, and the matrix phase is selected from PDMS, PVDF or its copolymer to ensure d 33 >400pC / N, dielectric loss less than 0.02, coupling coefficient k t Greater than 0.

5.

4. A flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 1 or 3, characterized in that: The flexible ultrasonic transducer array may be arranged in a 4×4, 6×6 or 8×8 matrix, with the transducer units interconnected via serpentine electrodes; 5. The flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 1, characterized in that: The finger sleeve body is made of medical-grade high-elasticity silicone or polyurethane material with a thickness of 0.5mm to 1.5mm. The inner surface is provided with a non-slip microstructure and is suitable for fingers with a diameter of 15mm to 25mm. The flexible ultrasonic transducer array adopts 1-3 type or 2-2 type piezoelectric composite material, with a center frequency of 5MHz to 10MHz and a unit size of 1mm×1mm to 3mm×3mm; The data transmission module uses low-power Bluetooth or Wi-Fi 6 to achieve data transmission within a range of 10m to 30m and supports remote monitoring; The power module uses a micro rechargeable lithium battery, supports wireless charging or Type-C charging, and has intelligent power consumption management function; The pulse excitation circuit of the signal processing module can provide an adjustable drive signal of 10V to 50V to optimize the transducer excitation effect. After the received signal is processed by low-noise amplification, it is sampled by the ADC at a rate of more than 10MSPS to ensure accurate capture of the vibration signal.

6. The flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 1, characterized in that: The data transmission module integrates a low-power data compression algorithm, supports AES encryption, and has a transmission rate of up to 2Mbps to reduce data delay and improve security.

7. The flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 1, characterized in that: The power module is equipped with a low-power management circuit, which automatically enters a low-power mode of less than 10μW when the transducer is not working to extend battery life and supports remote power monitoring and low-battery reminder functions.

8. The flexible ultrasonic finger cuff for early screening of Parkinson's disease as claimed in claim 1, characterized in that: The finger cuff body reserves a transducer window area, and the window thickness is reduced to 0.3mm to 0.8mm to reduce ultrasonic signal energy loss and improve detection sensitivity.

9. A method for preparing the flexible ultrasonic finger cuff according to claim 1, characterized in that: The steps include: S1. Preparation of flexible ultrasonic transducer array; Step 1.1, using a 1-3 type or 2-2 type piezoelectric composite material to form a transducer unit through a flexible template process; Step 1.2: Depositing flexible metal electrodes on the transducer surface and forming a serpentine electrode structure through photolithography and etching processes; Step 1.3, using Parylene or PDMS for packaging to form a flexible ultrasonic transducer array; S2, preparing the finger sleeve body; Step 2.1, using medical grade silicone or polyurethane material for mold forming and forming a non-slip microstructure; Step 2.2: Reserve a transducer window area on the inner surface of the finger cuff and control the thickness of the window; S3, assembly; Step 3.1, embed the transducer array into the cuff body and connect it to the signal processing module via a flexible PCB; Step 3.2: Assemble the signal processing module, power module, and data transmission module, and package and fix them; S4, system debugging; Step 4.1, perform transducer excitation test and optimize transducer excitation voltage and operating frequency; Step 4.2: Perform wireless communication debugging to ensure data transmission stability; perform overall system calibration and verify the accuracy and stability of tremor detection.

Images