Lightweight wireless wearable scoliosis intelligent pressure monitoring equipment

Abstract

The invention belongs to the technical field of electronic sensing and medical instruments, and particularly discloses a lightweight wireless wearable scoliosis intelligent pressure monitoring device which comprises a pressure sensor integration unit and an information processing and receiving unit. The pressure sensor integration unit is mainly composed of a flexible circuit board, a magnetic connector female head, four sets of S-shaped copper foil circuits, pin contacts of the S-shaped copper foil circuits, four film pressure sensors and the like. The information processing and receiving unit is mainly composed of a single-chip microcomputer, a magnetic connector male head, a shell, a Wi-Fi signal receiving module, a vibration motor, a voltage conversion module, a display screen, a main switch and the like. The flexible circuit board is used, the lightweight design is achieved, the equipment size is small, the weight is light, the S-shaped copper foil circuit has better ductility and can better adapt to the human body curve, the wearing comfort is ensured, multiple paths of pressure data can be collected through the multiple thin film pressure sensors, and the pressure sensor can be used for receiving the pressure value of a complex surface force application area.

Description

Technical Field

[0001] The present invention relates to the technical fields of electronic sensing and medical devices, and particularly relates to a lightweight wireless wearable intelligent scoliosis pressure monitoring device, which is applied to a scoliosis orthosis. Background Art

[0002] Adolescent idiopathic scoliosis (AIS) is an abnormal three-dimensional deformation of the spine that occurs in adolescents during puberty or before skeletal maturity. Idiopathic means that the cause of the disease is unknown. Orthotic braces can effectively correct spinal deformities when worn for a long time based on the three-point force principle. At present, the application of 3D technology and the research content of intelligent Internet of Things technology for spinal orthotic braces at home and abroad are relatively few, and the research results mainly focus on the manufacture of the brace body, lacking research on the intelligent wearing method of the brace and the tracking of the brace correction effect. It is difficult for actual users of the brace to ensure the accuracy of brace wearing and the correction effect. Clinicians lack the conditions to supervise the use of the brace and cannot monitor the treatment of the patient's spine in real time, thus affecting the correction effect of the brace. On the other hand, there is still a lack of specific data collection on the spinal orthosis effect of patients. There is no systematic collection of orthosis data of patients wearing braces and establishment of a database for orthosis effect analysis. The lack of daily communication between patients and matching treating physicians leads to the inability to improve the treatment plan for scoliosis in a timely manner. In the prior art, some intelligent orthoses are equipped with pressure sensors, but most devices have problems such as large device volume, inconvenient wearing, and inefficient data transmission methods, and cannot achieve real-time remote monitoring and data recording. Therefore, there is an urgent need for an intelligent pressure monitoring device that can monitor and feedback the pressure value of the force application area in real time, which can help patients achieve accurate orthosis effects, and at the same time has a convenient wearing design and remote data monitoring function. Summary of the Invention

[0003] The purpose of the present invention is to solve the technical problems existing in the background art. For this reason, a lightweight wireless wearable intelligent scoliosis pressure monitoring device is provided.

[0004] In order to achieve the above purpose, the technical solutions adopted by the present invention are as follows:

[0005] A lightweight wireless wearable intelligent scoliosis pressure monitoring device includes a pressure sensor integration unit and an information processing and receiving unit, and the pressure sensor integration unit and the information processing and receiving unit are electrically connected through a magnetic connector;

[0006] The pressure sensor integration unit includes a flexible circuit board, on which a female magnetic connector, N groups of S-shaped copper foil circuits, and N sensor reserved holes are fixedly arranged, where N≥2. N thin-film pressure sensors are installed in the N sensor reserved holes, and the N thin-film pressure sensors are electrically connected to the N groups of S-shaped copper foil circuits one by one. The N groups of S-shaped copper foil circuits are electrically connected to the female magnetic connector;

[0007] The information processing and receiving unit includes a single-chip microcomputer and a male magnetic connector. The single-chip microcomputer and the male magnetic connector are electrically connected, and the male magnetic connector and the female magnetic connector are magnetically plugged to achieve electrical connection.

[0008] The following is a further limited technical solution of the present invention. The flexible circuit board includes a transparent polyester substrate with a thickness of 0.14 mm.

[0009] The following is a further limited technical solution of the present invention. The female magnetic connector is fixedly arranged at the center position of the flexible circuit board. The N sensor reserved holes are evenly distributed on the outer periphery of the flexible circuit board, and the N groups of S-shaped copper foil circuits are evenly distributed on the outer periphery of the female magnetic connector. Each group of S-shaped copper foil circuits includes 2 S-shaped copper foils.

[0010] The following is a further limited technical solution of the present invention. One end of the N groups of S-shaped copper foil circuits far from the female magnetic connector is fixedly connected with pin contacts. The pin contacts are fixedly arranged on the flexible circuit board, and the N groups of S-shaped copper foil circuits are electrically connected to the N thin-film pressure sensors one by one through the pin contacts.

[0011] The following is a further limited technical solution of the present invention. The information processing and receiving unit further includes a housing, a Wi-Fi signal receiving module, a vibration motor, a voltage conversion module, a display screen, and a main switch;

[0012] The voltage conversion module is used to process the resistance signal output by the thin-film pressure sensor into a voltage signal and transmit the voltage signal to the single-chip microcomputer for processing;

[0013] The single-chip microcomputer is used to receive and process the pressure signal values collected by the N thin-film pressure sensors. By constructing a data window with a fixed length, the original signals of the thin-film pressure sensors are smoothed in real time; when new data is collected each time, the historical data is updated by sliding in chronological order to ensure that the window always contains the latest continuous sampling values;

[0014] The single-chip microcomputer displays the processed pressure signal through the display screen. At the same time, the processed pressure signal is transmitted to the cloud data platform through the Wi-Fi signal receiving module, and an instruction is sent to the vibration motor to control the vibration intensity of the motor;

[0015] A vibration motor is used to remind the patient of the magnitude of the current pressure value. The greater the difference between the pressure value and the preset value, the higher the vibration intensity of the vibration motor. The smaller the difference between the pressure value and the preset value, the lower the vibration intensity of the vibration motor. When the pressure value is equal to the preset value, the vibration motor does not vibrate;

[0016] The power supply is used to supply power to the overall device. When the main switch is turned on, the single-chip microcomputer is in the signal receiving state.

[0017] The following is a further limited technical solution of the present invention. When constructing a data window, an array storing 12 historical data samples is dynamically maintained. The data window is the core storage unit of the sliding filtering algorithm. In each sampling period, the system will collect the value of the current thin-film pressure sensor and store it in the last position of the array. At the same time, the oldest data value in the array is removed to form a dynamic sliding window, achieving the purpose of eliminating high-frequency noise.

[0018] The following is a further limited technical solution of the present invention. N thin-film pressure sensors are independently managed in multiple channels to achieve independent window management of multiple sensors. The data of each channel is isolated to avoid cross-interference.

[0019] The following is a further limited technical solution of the present invention. The pressure sensor integration unit real-time collects the pressure values at N points in the force application area through N thin-film pressure sensors, and then transmits them to the information processing and receiving unit through a magnetic connector. The sliding average filtering algorithm is used to perform real-time filtering on the pressure data of N channels of sensors to eliminate noise interference. Through incremental average calculation, the reference of the pressure value is dynamically adjusted to improve data stability. Based on the fuzzy control algorithm, the pressure value is compared with the preset interval to dynamically adjust the vibration motor intensity. The pressure data is uploaded to the cloud data platform through the Wi-Fi signal receiving module, supporting remote access and analysis.

[0020] The following is a further limited technical solution of the present invention. The sliding average filtering algorithm calculates the average value within the data window and uses the average value as the output of the current point. When the data window moves along the signal, the new average value of the data in the data window is calculated to obtain the smoothed signal. The formula is as follows:

[0021]

[0022] Among them, x[n] is the input signal, (N) is the size of the sliding window, and y[n] is the output of the sliding average filter.

[0023] The following are the further limited technical solutions of the present invention. The pressure detection program is used to compare the collected pressure values with the preset pressure values. The single-chip microcomputer will output PWM waves with different frequencies according to fuzzy rules to control the vibration intensity of the vibration motor. The greater the difference between the filtered pressure value and the preset value, the stronger the vibration intensity of the motor; the smaller the difference between the filtered value and the preset value, the weaker the vibration intensity of the motor.

[0024] Compared with the prior art, the present invention has the following technical effects:

[0025] The present invention uses a flexible circuit board with a transparent polyester substrate and a thickness of 0.14 mm to achieve a lightweight design. The device is small in size and light in weight. The unique S-shaped copper foil circuit has better ductility and can better adapt to the human curve to ensure wearing comfort. Multiple thin-film pressure sensors can be used to collect multi-channel pressure data, which can be used to receive the magnitude of pressure values in the force application area of a complex surface. At the same time, a pogopin magnetic connector is used to achieve quick disassembly and assembly, further improving the convenience of use. In addition, the low-power design of the device supports long-term continuous operation, meeting the needs of daily use. Finally, the pressure data is real-time uploaded to the cloud data platform through the Wi-Fi signal receiving module, supporting remote monitoring and data analysis.

[0026] The present invention will be further described below in conjunction with the drawings and embodiments. Description of the Drawings

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0028] Figure 1 is the structural schematic diagram of the present invention;

[0029] Figure 2 is the structural schematic diagram of the pressure sensor integration unit in the present invention;

[0030] Figure 3 is the structural schematic diagram of the information processing and receiving unit in the present invention, where Figure 3 (a) is the reverse structural schematic diagram of the information processing and receiving unit, Figure 3 (b) is the front structural schematic diagram of the information processing and receiving unit;

[0031] Figure 4 is the line graph of the pressure value of the thin-film pressure sensor and the PWM wave value output by the vibration motor in the present invention.

[0032] Reference numerals: 1, flexible circuit board; 2, S-shaped copper foil circuit; 3, pin contact; 4, reserved hole for sensor; 5, female magnetic connector; 6, connector pin; 7, male magnetic connector; 8, housing; 9, display screen; 10, main switch. Detailed implementation manners

[0033] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the following will describe in detail the specific implementation manners of the present invention with reference to the accompanying drawings. Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0034] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as limiting the present invention.

[0035] In the embodiments of the present invention, unless otherwise clearly defined and limited, the terms "mounted", "connected", "connected", "fixed", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific situations.

[0036] As Figures 1-3 shown, this embodiment provides a lightweight wireless wearable spinal scoliosis intelligent pressure monitoring device, which mainly consists of two parts: a pressure sensor integration unit and an information processing and receiving unit. The pressure sensor integration unit is used to collect pressure value data at multiple points in the force application area, and the information processing and receiving unit is used to process pressure data, transmit Wi-Fi signals to the cloud data platform, display pressure data, and give vibration feedback reminders. The pressure sensor integration unit and the information processing and receiving unit are electrically connected through a pogopin magnetic connector, so that the pressure data collected by the pressure sensor integration unit is transmitted to the information processing and receiving unit for data processing.

[0037] As Figure 2As shown in the figure, the pressure sensor integration unit mainly consists of a flexible circuit board, a female magnetic connector, 4 groups of S-shaped copper foil circuits and their pin contacts, 4 thin-film pressure sensors, etc. The flexible circuit board includes a transparent polyester substrate with a thickness of 0.14 mm; the female magnetic connector (the female magnetic connector includes connector pins) is fixedly arranged at the center of the flexible circuit board, and 4 sensor reserved holes are evenly distributed around the flexible circuit board. Therefore, the 4 thin-film pressure sensors are respectively installed around the flexible circuit board through the 4 sensor reserved holes; the 4 groups of S-shaped copper foil circuits are electrically connected to the female magnetic connector and the 4 groups of S-shaped copper foil circuits are evenly distributed around the female magnetic connector. One end of the 4 groups of S-shaped copper foil circuits far from the female magnetic connector is fixedly connected to the pin contacts, and the pin contacts are fixedly arranged on the flexible circuit board. Each group of S-shaped copper foil circuits includes 2 S-shaped copper foils; the 4 groups of S-shaped copper foil circuits are all electrically connected to the 4 thin-film pressure sensors one by one through the pin contacts.

[0038] In summary, considering the wearing needs of patients, the pressure sensor integration unit uses a flexible circuit board (FPC) with a transparent polyester (Polyerster, abbreviated as PET) substrate and a thickness of 0.14 mm. The unique S-shaped copper foil circuit has better ductility and can better adapt to the human body curve. Connecting 4 thin-film pressure sensors can realize the acquisition of 4-channel pressure data, can be used to receive the pressure value of the force application area on the complex surface, support static / dynamic pressure sensing, has excellent flexibility and reliability, and meets the wearing requirements of intelligent wearable devices with miniaturization and lightness of electronic products.

[0039] As Figure 3 shown in the figure, the information processing and receiving unit mainly consists of a single-chip microcomputer, a male magnetic connector, a housing, a Wi-Fi signal receiving module, a vibration motor, a voltage conversion module, a display screen and a main switch, etc.

[0040] The single-chip microcomputer is electrically connected to the male magnetic connector, and the male magnetic connector and the female magnetic connector are magnetically plugged to achieve electrical connection.

[0041] The voltage conversion module is used to process the resistance signal output by the thin-film pressure sensor into a voltage signal and transmit the voltage signal to the single-chip microcomputer for processing. The output signal of the thin-film pressure sensor is usually very weak (for example, a small voltage change generated by the change of resistance), and these signals usually cannot be accurately recognized by the ADC (analog-to-digital converter) of the single-chip microcomputer directly. The voltage conversion module can amplify the signal through an operational amplifier so that the signal intensity reaches the range that can be recognized by the single-chip microcomputer, thereby improving the accuracy and reliability of the sensor.

[0042] The single-chip microcomputer is used to receive and process the pressure signal values collected by N thin-film pressure sensors. By constructing a data window with a fixed length, real-time smoothing processing is performed on the original signals of the thin-film pressure sensors. Each time new data is collected, the historical data is slid and updated in chronological order to ensure that the window always contains the latest continuous sampling values. The signals of thin-film pressure sensors are often easily affected by factors such as environmental noise and power supply interference. Using filtering processing can ensure that the signals transmitted to the single-chip microcomputer are more stable and accurate. The moving average filter does not use a fixed number of sample points, but dynamically maintains an array that stores 12 historical data samples. The data window is the core storage unit of the moving filter algorithm. During each sampling period, the system collects the current value of the thin-film pressure sensor and stores it in the last position of the array. At the same time, the oldest data value in the array is removed, forming a dynamic "sliding" window to achieve the purpose of eliminating high-frequency noise. Multi-channel independent management of N thin-film pressure sensors can realize independent window management of multiple sensors, isolate the data of each channel, and avoid cross-interference.

[0043] The single-chip microcomputer displays the processed pressure signal through a display screen. At the same time, the processed pressure signal is transmitted to the cloud data platform through the Wi-Fi signal receiving module, and an instruction is sent to the vibration motor to control the vibration intensity of the motor.

[0044] The vibration motor is used to remind the patient of the magnitude of the current pressure value. When the difference between the pressure value and the preset value is larger, the vibration intensity of the vibration motor is higher. When the difference between the pressure value and the preset value is smaller, the vibration intensity of the vibration motor is lower. When the pressure value is equal to the preset value, the vibration motor does not vibrate. The intensity of the vibration motor is determined according to the difference between the current pressure value and the preset value. For example, when the preset value is 30N, the vibration intensity when the current pressure value is 10N or 50N (the difference is 20N) will be greater than when the current pressure value is 25N or 35N (the difference is 5N).

[0045] The power supply is used to supply power to the whole device. When the main switch is turned on, the single-chip microcomputer is in the signal receiving state.

[0046] Combined with a digital signal switch, the single-chip microcomputer can be switched to the sleep mode, turning off the radio frequency module and the Wi-Fi signal receiving module. It is suitable for scenarios that require periodic networking, and the power consumption can be reduced to about 20 - 30 mA, achieving low-power design of the device.

[0047] In summary, the pressure sensor integration unit collects the pressure values at N points in the force application area in real time through N thin-film pressure sensors, and then transmits them to the information processing and receiving unit through a magnetic connector. The sliding average filtering algorithm is used to perform real-time filtering on the pressure data of N channels of sensors to eliminate noise interference. Through incremental average calculation, the reference of the pressure value is dynamically adjusted to improve data stability. Based on the fuzzy control algorithm, the pressure value is compared with the preset interval, and the intensity of the vibration motor is dynamically adjusted. The pressure data is uploaded to the cloud data platform through the Wi-Fi signal receiving module, supporting remote access and analysis.

[0048] The sliding average filtering algorithm calculates the average value within the data window and uses the average value as the output of the current point. When the data window moves along the signal, the new average value of the data in the data window is calculated to obtain the smoothed signal. The formula is as follows:

[0049]

[0050] Among them, x[n] is the input signal, (N) is the size of the sliding window, and y[n] is the output of the sliding average filter.

[0051] Fuzzy control is an intelligent control method based on fuzzy set theory, fuzzy language variables, and fuzzy logic reasoning. It is an intelligent control algorithm that mimics the fuzzy reasoning and decision-making process of humans in terms of behavior. The pressure detection program compares the collected pressure value with the preset pressure value, and the single-chip microcomputer outputs PWM waves with different frequencies according to the fuzzy rules to control the vibration intensity of the vibration motor. The greater the difference between the filtered pressure value and the preset value, the stronger the vibration intensity of the motor; the smaller the difference between the filtered value and the preset value, the weaker the vibration intensity of the motor. In the actual application of fuzzy control, the controller needs to be designed first, that is, to design the fuzzy control rules. In this study, it is set that the vibration motor has three output modes: non-vibration, low-intensity vibration, and high-intensity vibration, which are represented by the numbers 0, 1, and 2 respectively. The fuzzy control rules can be shown in the following table:

[0052] The rule set of fuzzy control

[0053]

[0054] The first row in the above table represents the voltage increment change rate ΔU, which can be divided into: PS (Positive Small): positive small change; PM (Positive Medium): positive medium change; PB (Positive Big): positive big change; NS (Negative Small): negative small change; NM (Negative Medium): negative medium change; NB (Negative Big): negative big change, a total of six change levels. Fuzzy calculation and reasoning are realized through the fuzzy control rules in the table. Defuzzification is the process of converting fuzzy values into precise values, so as to obtain a specific precise value of the output motor control signal, thereby controlling the vibration strength of the motor. Under different pressure values, the vibration motor under fuzzy control will have different PWM wave values. The larger the PWM wave value output by the vibration motor, the stronger the vibration of the motor, and vice versa. Taking the preset pressure value set as 50N as an example, the line graph of its pressure value and PWM wave value is as Figure 4 shown.

[0055] The above is only the preferred embodiment of the present invention, and it is not intended to limit the present invention in any form. Any person skilled in the art can make many possible changes and modifications to the technical solution of the present invention, or modify it into an equivalent embodiment with equivalent changes, without departing from the scope of the technical solution of the present invention. Therefore, all equivalent changes made according to the shape, structure and principle of the present invention without departing from the content of the technical solution of the present invention shall be covered by the protection scope of the present invention.

Claims

1. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device, characterized in that: It includes a pressure sensor integrated unit and an information processing receiving unit, wherein the pressure sensor integrated unit and the information processing receiving unit are electrically connected via a magnetic connector; The pressure sensor integrated unit includes a flexible circuit board, on which a magnetic connector female head, N groups of S-shaped copper foil circuits and N sensor reserved holes are fixedly arranged, wherein N ≥ 2, the N sensor reserved holes are all installed with thin film pressure sensors, the N thin film pressure sensors are electrically connected to the N groups of S-shaped copper foil circuits in a one-to-one correspondence, and the N groups of S-shaped copper foil circuits are electrically connected to the magnetic connector female head; The information processing receiving unit comprises a single chip microcomputer and a male head of a magnetic connector. The single chip microcomputer and the male head of the magnetic connector are electrically connected. The male head of the magnetic connector and the female head of the magnetic connector are electrically connected by magnetic plugging.

2. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 1, characterized in that: The flexible circuit board includes a transparent polyester substrate with a thickness of 0.14 mm.

3. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 1, characterized in that: The magnetic connector female head is fixedly arranged at the center position of the flexible circuit board, N sensor reserved holes are evenly distributed on the periphery of the flexible circuit board, N groups of S-shaped copper foil circuits are evenly distributed on the periphery of the magnetic connector female head, and each group of S-shaped copper foil circuits includes 2 S-shaped copper foils.

4. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 3, characterized in that: The N groups of S-shaped copper foil circuits are fixedly connected to pin contacts at one end away from the female head of the magnetic connector. The pin contacts are fixedly arranged on the flexible circuit board. The N groups of S-shaped copper foil circuits are electrically connected to the N thin film pressure sensors one by one through the pin contacts.

5. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 1, characterized in that: The information processing receiving unit also includes a housing, a Wi-Fi signal receiving module, a vibration motor, a voltage conversion module, a display screen and a main switch; The voltage conversion module is used to convert the resistance signal output by the thin film pressure sensor into a voltage signal, and transmit the voltage signal to the single chip microcomputer for processing; The single-chip microcomputer is used to receive and process the pressure signal values ​​collected by N thin-film pressure sensors. By constructing a data window of fixed length, the original signal of the thin-film pressure sensor is smoothed in real time. Every time new data is collected, the historical data is updated in chronological order to ensure that the window always contains the latest continuous sampling value. The single chip microcomputer displays the processed pressure signal through the display screen. At the same time, it transmits the processed pressure signal to the cloud data platform through the Wi-Fi signal receiving module and sends instructions to the vibration motor to control the vibration intensity of the motor. The vibration motor is used to remind the patient of the current pressure value. When the difference between the pressure value and the preset value is greater, the vibration intensity of the vibration motor is higher. When the difference between the pressure value and the preset value is smaller, the vibration intensity of the vibration motor is lower. When the pressure value is equal to the preset value, the vibration motor does not vibrate. The power supply is used to power the entire device. When the main switch is turned on, the microcontroller is in the signal receiving state.

6. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 5, characterized in that: When constructing the data window, an array storing 12 historical data samples is dynamically maintained. The data window is the core storage unit of the sliding filtering algorithm. In each sampling cycle, the system will collect the value of the current thin film pressure sensor and store it in the last position of the array. At the same time, the oldest data value in the array is removed to form a dynamic sliding window to eliminate high-frequency noise.

7. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 5, characterized in that: N thin film pressure sensors are managed independently in multiple channels, thus realizing independent window management of multiple sensors. The data of each channel is isolated to avoid cross interference.

8. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 5, characterized in that: The pressure sensor integrated unit collects the pressure values ​​of N points in the force application area in real time through N thin film pressure sensors, and then transmits them to the information processing receiving unit through a magnetic connector. The sliding average filtering algorithm is used to filter the pressure data of the N sensors in real time to eliminate noise interference. The pressure value benchmark is dynamically adjusted through incremental average calculation to improve data stability. Based on the fuzzy control algorithm, the pressure value is compared with the preset interval and the vibration motor intensity is dynamically adjusted. The pressure data is uploaded to the cloud data platform through the Wi-Fi signal receiving module to support remote access and analysis.

9. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 8, characterized in that: The sliding average filtering algorithm calculates the average value within the data window and uses the average value as the output of the current point. When the data window moves along the signal, the new average value of the data in the data window is calculated to obtain a smoothed signal. The formula is as follows: Where x[n]) is the input signal, (N) is the size of the sliding window, and y[n] is the output of the sliding average filter.

10. A lightweight, wireless, wearable, intelligent scoliosis pressure monitoring device as claimed in claim 8, characterized in that: The pressure detection program is used to compare the collected pressure values ​​with the preset pressure values. The single chip will output PWM waves of different frequencies according to fuzzy rules to control the vibration intensity of the vibration motor. The greater the difference between the filtered pressure value and the preset value, the stronger the vibration intensity of the motor. The smaller the difference between the filtered value and the preset value, the weaker the vibration intensity of the motor.

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