Neck and shoulder rehabilitation sticking and pricking suitability regulation and control system and method based on pressure sensing

Abstract

The invention relates to the technical field of sensing rehabilitation, in particular to a neck and shoulder rehabilitation sticking and pricking suitability regulation and control system and method based on pressure sensing, and the system comprises a pressure acquisition module, a time sequence phase analysis module, a stress direction vector module, a sticking and pricking path adaptation module and a support control module. According to the method, local pressure changes are obtained in a time-space correlation mode, noise suppression is completed, a stress curve is made to present a continuous trend, a stress direction derivation basis is formed through pressure difference and time sequence difference, a direction relation is constructed to be used for calibrating the point location and the trend of a sticking path, and the sticking path is made to be attached to the actual stress trend. Through comparison of a target pressure threshold value and real-time feedback, circulation adjustment is formed, so that the supporting strength and direction are synchronously corrected along with the training state, stress distribution is kept balanced and stable, the attachment adaptability and the regulation and control precision are improved, and the problem that pressure judgment depends on perception and adaptability fluctuation in traditional attachment is solved.

Description

Technical Field

[0001] This invention relates to the field of sensory rehabilitation technology, and in particular to a neck and shoulder rehabilitation taping adaptation control system and method based on pressure sensing. Background Technology

[0002] The field of sensor-based rehabilitation technology involves core aspects of human-computer interaction rehabilitation training, such as pressure sensing, mechanical data acquisition, posture detection, and adaptive bonding structures. It achieves systematic monitoring and control of rehabilitation movements, loads, and postures by deploying flexible sensing media on soft tissue surfaces, acquiring local force distribution, analyzing muscle group force patterns, and combining this with adjustable adhesive materials. This field comprehensively covers pressure-sensitive element configuration design, human body surface adaptation methods for flexible adhesive structures, force signal acquisition and analysis processes, and rehabilitation assistance strategies based on taping layouts, forming a comprehensive sensor-based rehabilitation system for areas such as the neck and shoulders.

[0003] Among them, the traditional cervical and shoulder rehabilitation taping adaptation control system refers to the taping structure and pressure distribution control method used when the cervical and shoulder areas need to be supported by taping due to muscle tension or dysfunction. It is a traditional method to achieve taping adaptation by manually cutting elastic tape on the skin surface of the cervical and shoulder areas, selecting the tape stretch ratio according to experience, manually determining the tape direction according to the estimated muscle direction, adjusting local tension by using a simple segmented application method, and relying on manual palpation to sense changes in tape pressure.

[0004] Traditional taping relies on manual cutting and stretching to determine the shape and tension distribution of the tape. Pressure perception is mainly based on palpation and local somatosensory feedback, which cannot show the continuous changes in the force on the neck and shoulder muscles. When the skin curvature and movement pull cause the tape tension to fluctuate with training, there is a lack of quantitative basis. The taping direction is based on experience to infer the direction of the muscle group, which is difficult to match the actual force trend. Local support is prone to deviation and loosening. Uneven pressure during training causes unstable support effect. Lagging feedback affects movement control and safety, and it is difficult to form a reusable control mechanism. Summary of the Invention

[0005] To address the technical problems of traditional taping, which relies on manual cutting and stretching to determine the shape and tension distribution of the tape, and pressure sensing primarily based on palpation and local somatosensory feedback, failing to reflect the continuous changes in the force on the neck and shoulder muscles, lacking quantitative evidence when the tape tension fluctuates with training due to skin curvature and movement, relying on experience to infer muscle group direction for taping direction which is difficult to match with actual force trends, leading to local support deviation and loosening, uneven pressure during training causing unstable support effects, and delayed feedback affecting movement control and safety, and making it difficult to form a reusable control mechanism, this invention provides a pressure-sensing-based neck and shoulder rehabilitation taping adaptability control system and method. The technical solution is as follows:

[0006] On the one hand, a pressure-sensing-based cervical and shoulder rehabilitation taping adaptation control system is provided, which includes: The pressure acquisition module acquires the taping pressure signal of the neck and shoulder muscles through the piezoresistive array sensor, obtains the pressure amplitude and timestamp of the sensing unit, and combines it with spatial coordinates to form a pressure time-space data set. The Kalman filter algorithm is used to filter and remove noise, and outputs the pressure time series, which is then transmitted to the time-phase analysis module. The timing phase analysis module calls the pressure time series, uses the dynamic time warping algorithm to calculate the phase difference of signals from adjacent sensing units, extracts phase advance and delay parameters, performs phase difference classification, forms a timing phase parameter set, and transmits it to the force direction vector module. The force direction vector module calls the time phase parameter set, calculates the pressure difference and position relationship between adjacent units by combining the spatial coordinates of the sensing unit, derives the pressure change direction and amplitude vector of the force area, performs vector superposition operation, outputs the force direction vector field data, and transmits it to the taping path adaptation module. The taping path adaptation module, in conjunction with the force direction vector field data, calculates the deviation angle between the taping path and the force direction of the muscle group based on the vector field characteristics, corrects the preset path coordinate points, forms a taping path adjustment instruction set, and transmits it to the support control module.

[0007] As a further embodiment of the present invention, the pressure time series includes a filtered pressure amplitude sequence, a corresponding timestamp sequence, and a set of spatial coordinates; the time-series phase parameter set includes the phase difference value between adjacent sensing units, phase advance, phase delay, and phase difference category label; the force direction vector field data includes the pressure change direction vector, pressure change amplitude vector, and regional vector superposition field of the force area; and the taping path control instruction set includes the deviation angle value between the path and the force direction and the corrected path coordinate point sequence.

[0008] As a further aspect of the present invention, the pressure acquisition module includes: The array acquisition submodule acquires the electrical signals of the piezoresistive array sensor in the taping area of ​​the neck and shoulder muscles. It performs amplitude conversion and records the timestamp based on the resistance change of the sensing unit. It performs sequential arrangement and indexing of amplitude and timestamp, corrects abnormal jump items, and establishes the original quantity of pressure amplitude time sequence. The coordinate registration submodule performs coordinate extraction based on the original pressure amplitude time series and the array layout table, calls the timestamp to match the amplitude and coordinates, corrects missing coordinates and abnormal spatial offsets, and obtains the pressure spatiotemporal mapping set. The filter output submodule constructs state prediction and measurement update quantities based on the pressure spatiotemporal mapping set, performs prediction residual calculation and gain correction according to the Kalman filter recursive relationship, performs smoothing and out-of-bounds removal on the time amplitude, and performs time sequence reorganization to generate a pressure time series.

[0009] As a further aspect of the present invention, the timing phase analysis module includes: The pressure sequence alignment submodule calls the pressure time series, collects pressure sampling points of the sensing unit, constructs a distance matrix based on the pressure difference of the sampling points, matches the corresponding relationship of the sampling points according to the path with the minimum cumulative difference, rearranges the sequence time index, and generates a time alignment offset sequence. The phase difference extraction submodule obtains the pressure value of adjacent sensing units at the corresponding position on the registration path based on the time alignment offset sequence, performs time interval calculation according to the registration path index difference, marks the interval with symbols and arranges them in the path order to generate a unit phase difference value vector. The phase classification and aggregation submodule extracts the symbol and interval data based on the unit phase difference vector, performs advance and delay state determination based on the zero-crossing reference, and writes the determination label and corresponding phase difference value into the sequence structure in unit order to generate a time-series phase parameter set.

[0010] As a further aspect of the present invention, the force direction vector module includes: The coordinate difference calculation submodule calls the time-series phase parameter set to perform component comparison between the spatial coordinates of the sensing unit and the coordinates of adjacent units, calculates the difference for the coordinate axes and performs sign verification, applies phase weights to the difference components and performs weighted integration to generate a spatial difference vector set. The pressure difference vector extraction submodule performs normalization conversion on the pressure difference components based on the spatial difference vector set and the corresponding pressure difference components of adjacent units. It then calls the spatial difference vector set to perform direction mapping and scale correction on the conversion sequence to generate a pressure difference feature vector group. The direction field superposition generation submodule calls the pressure difference feature vector group and the positional relationship of the area unit to perform vector correspondence superposition, performs amplitude correction on the superposition result according to the superposition reference scale and integrates the direction consistency to generate force direction vector field data.

[0011] As a further aspect of the present invention, the bonding path adaptation module includes: The vector field analysis submodule detects the position direction component based on the force direction vector field data, compares the difference between adjacent direction components, filters data whose difference is greater than the direction change threshold, makes a consistency judgment based on the change amplitude, and generates the regional direction change rate value. The path deviation calculation submodule calls the regional direction change rate value and obtains the direction component of the coordinate point based on the preset path coordinate point. It performs angle calculation with the direction component at the same position of the vector field, filters angles greater than the angle amplitude threshold, and performs judgment to obtain the path deviation angle value. The path coordinate correction submodule adjusts the coordinates based on the path deviation angle value and the preset path coordinate points, superimposes the adjustment amount with the original coordinate points, calls the regional direction change rate value to make a reasonable judgment on the superimposed coordinates, and generates a tape path control instruction set.

[0012] As a further embodiment of the present invention, the direction change threshold is based on the original statistical results of the direction components of the force direction vector field data within a preset sampling window, and is obtained by dividing the mean and standard deviation of the direction components within the preset sampling window into discrete intervals. The angle amplitude threshold is based on the original statistical results of the direction components of the preset path coordinate points within the preset path length range. It is obtained by dividing the cumulative distribution of the change angle of the direction components within the preset path length range into quantile intervals to obtain the angle interval boundary value.

[0013] As a further embodiment of the present invention, the support control module calls the taping path adjustment instruction set, calculates the electronically controlled support adjustment instruction by comparing the target pressure threshold in the instruction set with the real-time pressure feedback value, controls the taping support structure actuator to adjust the support direction and force along the correction path, and performs cyclic verification of the support adjustment instruction according to the pressure feedback signal, and outputs a stable taping support state. The stable taping support state includes the target pressure threshold setting value, real-time pressure feedback signal value, electronic support adjustment command parameters, final support direction, final support force, and closed-loop verification pass mark.

[0014] As a further aspect of the present invention, the support control module includes: The pressure difference calculation submodule calculates the difference and extracts the absolute value based on the target pressure threshold and real-time pressure feedback value in the patching path control instruction set. It then performs a quantization compression action based on the single-value data after the absolute value is extracted to generate the pressure difference amount. The target pressure threshold is generated by calibration based on the thickness parameters of the patching material and the original pressure statistics of the patching area, and is imported before patching is performed; The support instruction generation submodule calls the pressure difference and the correction path parameters obtained by parsing the patching path control instruction set, performs a weighted operation on the two to construct directional and force components, and performs a combination operation based on the directional and force components to obtain the support adjustment instruction vector. The stability verification submodule calls the support adjustment command vector and the real-time pressure feedback value, performs an amplitude comparison based on the directional component and the real-time pressure feedback value and obtains the comparison value, performs an interval judgment on the comparison value and the target pressure threshold, and generates a stable bonding support state.

[0015] On the other hand, the pressure-sensing-based cervical and shoulder rehabilitation taping adaptation adjustment method, which is executed based on the aforementioned pressure-sensing-based cervical and shoulder rehabilitation taping adaptation adjustment system, includes the following steps: S1: The neck and shoulder muscle taping pressure signal is collected by the piezoresistive array sensor. The pressure amplitude and timestamp of the sensing unit are obtained. Combined with the spatial coordinates, a pressure time-space data set is formed. The Kalman filter algorithm is used to filter and remove noise, and the pressure time series is output. S2: Call the pressure time series, use the dynamic time warping algorithm to calculate the phase difference of signals from adjacent sensing units, extract phase advance and delay parameters, perform phase difference classification, and form a time-series phase parameter set; S3: Call the time-phase parameter set, combine the spatial coordinates of the sensing unit to calculate the pressure difference and positional relationship between adjacent units, derive the pressure change direction and amplitude vector of the stressed area, perform vector superposition operation, and output the stress direction vector field data. S4: Combining the force direction vector field data, calculate the deviation angle between the taping path and the force direction of the muscle group based on the vector field characteristics, correct the preset path coordinate points, form a taping path adjustment instruction set, and transmit it to the support control module; S5: Call the patching path control instruction set, calculate the electronic support adjustment instruction by comparing the target pressure threshold in the instruction set with the real-time pressure feedback value, control the patching support structure actuator to adjust the support direction and force along the correction path, and perform cyclic verification of the support adjustment instruction according to the pressure feedback signal to output a stable patching support state.

[0016] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: By acquiring local pressure changes and suppressing noise through temporal and spatial correlation, the force curve presents a continuous trend. The force direction is derived based on pressure difference and time sequence difference, and the directional relationship is constructed to calibrate the patching path points and direction, so that the patching path conforms to the actual force trend. By comparing the target pressure threshold with real-time feedback, a cyclic adjustment is formed, so that the support force and direction are synchronously corrected with the training state, the force distribution remains balanced and stable, the patching adaptability and control accuracy are improved, and the problems of pressure judgment relying on perception and adaptability fluctuation in traditional patching are solved. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the accompanying drawings without creative effort.

[0018] Figure 1 This is a system schematic diagram of the present invention; Figure 2 This is a schematic diagram of the system framework of the present invention; Figure 3 This is a flowchart of the pressure acquisition module in this invention; Figure 4 This is a flowchart of the timing phase analysis module in this invention; Figure 5 This is a flowchart of the force direction vector module in this invention; Figure 6 This is a flowchart of the bonding path adaptation module in this invention; Figure 7 This is a flowchart of the supporting control module in this invention; Figure 8 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0020] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0021] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0022] In this embodiment of the invention, sometimes the subscript such as W1 is written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0023] All user-related information involved in this invention (including but not limited to biometric information, identity verification information, behavioral data, device information, and other data that can be used for identity verification and personalized services) is collected and processed with the user's full knowledge and voluntary consent. The collection, storage, and use of all information strictly comply with applicable national and regional laws and regulations, and meet relevant data protection standards and policy requirements. The use of data is limited to purposes necessary for providing the technical services of this invention, and reasonable technical and management measures will be taken to ensure the security and confidentiality of users' personal information in terms of information protection and privacy.

[0024] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0025] This invention provides a pressure-sensing-based cervical and shoulder rehabilitation taping fit adjustment system, such as... Figure 1-2 The diagram shown illustrates a pressure-sensing-based cervical and shoulder rehabilitation taping adaptation control system. This system includes: The pressure acquisition module acquires the taping pressure signal of the neck and shoulder muscles through a piezoresistive array sensor, obtains the pressure amplitude and timestamp of the sensing unit, and combines it with spatial coordinates to form a pressure time-space data set. The Kalman filter algorithm is used to filter and remove noise, and outputs the pressure time series, which is then transmitted to the time-phase analysis module. The timing phase analysis module calls the pressure time series, uses the dynamic time warping algorithm to calculate the phase difference of signals from adjacent sensing units, extracts phase advance and delay parameters, performs phase difference classification, forms a timing phase parameter set, and transmits it to the force direction vector module. The force direction vector module calls the timing phase parameter set, calculates the pressure difference and position relationship between adjacent units by combining the spatial coordinates of the sensing unit, derives the pressure change direction and amplitude vector of the force area, performs vector superposition operation, outputs the force direction vector field data, and transmits it to the bonding path adaptation module. The taping path adaptation module combines the force direction vector field data, calculates the deviation angle between the taping path and the force direction of the muscle group based on the vector field characteristics, corrects the preset path coordinate points, forms a taping path adjustment instruction set, and transmits it to the support control module. The support control module calls the tape path adjustment instruction set, calculates the electronic support adjustment instruction by comparing the target pressure threshold in the instruction set with the real-time pressure feedback value, controls the tape support structure actuator to adjust the support direction and force along the correction path, and performs cyclic verification of the support adjustment instruction based on the pressure feedback signal, outputting a stable tape support state. The pressure time series includes a filtered pressure amplitude sequence, a corresponding timestamp sequence, and a set of spatial coordinates. The time-series phase parameter set includes the phase difference value between adjacent sensing units, phase advance, phase delay, and phase difference category label. The force direction vector field data includes the pressure change direction vector, pressure change amplitude vector, and regional vector superposition field of the force area. The bonding path control command set includes the deviation angle value between the path and the force direction and the corrected path coordinate point sequence. The stable bonding support state includes the target pressure threshold setting value, real-time pressure feedback signal value, electronic support adjustment command parameters, final support direction, final support force, and closed-loop verification pass mark.

[0026] Specifically, such as Figure 2 , 3 As shown, the pressure acquisition module includes: The array acquisition submodule acquires the electrical signals of the piezoresistive array sensor in the taping area of ​​the neck and shoulder muscles. It performs amplitude conversion and records the timestamp based on the resistance change of the sensing unit. It performs sequential arrangement and indexing of amplitude and timestamp, corrects abnormal jump items, and establishes the original quantity of pressure amplitude time sequence. For rehabilitation taping scenarios targeting the trapezius muscle area of ​​the neck and shoulders, activate the taping area. The piezoresistive thin-film sensor array acquisition program sets the microcontroller's main clock frequency to [value missing]. And frequency division generation The sampling interrupt signal sequentially selects the array in each sampling period. Each independent sensing unit channel is applied to each channel. A constant bias voltage is applied, and the voltage division value in the series circuit of the sensing unit is read using a 12-bit analog-to-digital converter. The read analog voltage signal is then quantized into... to The number between The function calls a preset resistance-pressure conversion function, which is set based on the piezoresistive characteristics of conductive polymer materials. First, it uses the formula... Calculate the resistance of the current sensing unit, where the reference resistor is... Values If a certain unit for Then the calculation yields for Then, based on the linear relationship between conductivity and pressure, amplitude conversion is performed, and the calculation formula is as follows: ,in Set the sensitivity coefficient to Initial resistance value Set as Substituting the values, the pressure amplitude is calculated. (Dimensionless normalized value), and simultaneously read the millisecond-level count value from the system's real-time clock register as the timestamp of this data frame. ,For example This will include channel index and amplitude. and timestamp Data packets are written to a circular buffer. When the buffer contains 100 packets, a quicksort algorithm is initiated. Sort the data packets by key-value pairs in ascending order, traverse the sorted sequence, and calculate the time difference between adjacent data points. ,like Less than the minimum sampling interval Data is identified as redundant and those with larger amplitudes are retained. Next, amplitude jump detection is performed, with the sliding window size set to [value missing]. Calculate the average amplitude within the window. and standard deviation If the current point amplitude satisfy and The point is determined to be an abnormal jump caused by poor contact, for example, during stable output. Suddenly appeared nearby For the peak, the linear interpolation results of the adjacent valid points are used. Replace the outlier, complete the cleaning and correction of the channel data, and establish the original pressure amplitude timing quantity containing pure amplitude and strict timing.

[0027] The coordinate registration submodule performs coordinate extraction based on the original pressure amplitude time series and the array layout table, calls the timestamp to match the amplitude and coordinates, corrects missing coordinates and abnormal spatial offsets, and obtains the pressure spatiotemporal mapping set. The generated pressure amplitude timing raw data is invoked, and the array layout table stored in non-volatile memory is loaded. This table records in detail the physical space coordinates corresponding to each logical channel index in the sensor array. The specific parameter configuration is shown in Table 1. Each data packet in the timing raw data is traversed, and its channel logical index is extracted. Retrieve the array layout table corresponding row coordinates Column coordinates and physical location coordinates For example, for logical indexes The data packet was matched to the physical coordinates. The extracted coordinate information is appended to the data packet, and then the data is processed according to the timestamp. The data stream is segmented into frames, and those with the same timestamp (within the error range) are processed to achieve this. The sensor unit data (within) are grouped into pressure distribution frames at the same time, and a data structure is constructed for each frame. The spatial matrix is ​​examined to identify zero-valued elements, isolated zeros surrounded by non-zero values, and a neighborhood determination threshold is set. If a certain zero point If a point has more than four non-zero valid values ​​within its eight neighborhoods (up, down, left, right, and diagonal), it is determined to be a point with missing coordinates. Spatial interpolation correction is then performed, and the arithmetic mean of the magnitudes of its valid neighboring points is calculated. For example, if the valid values ​​within the neighborhood are... Calculate the mean Fill in the missing coordinates, then calculate the Euclidean distance between the center of pressure (CoP) of two consecutive frames, using the formula: The inter-frame displacement threshold caused by the maximum displacement rate limit of human muscle movement is set to... If the calculated for If the threshold is exceeded, an abnormal spatial offset is determined, and the coordinate system of the current frame is shifted in the opposite direction. The distance vector is forcibly corrected, or outliers that deviate from the centroid in the frame are directly discarded. Finally, the corrected pressure data with accurate physical coordinates and time stamps are integrated to obtain the pressure spatiotemporal mapping set.

[0028] Table 1: Array Layout and Coordinate Mapping Parameters Logical Index (ID) Matrix row numbers Matrix column number (Col) Physical x-axis (mm) Physical vertical axis Y (mm) Initial calibration resistance (kΩ) 0 0 0 0.0 0.0 20.1 1 0 1 7.5 0.0 19.8 ... ... ... ... ... ... 12 1 4 15.0 22.5 20.0 ... ... ... ... ... ... 63 7 7 52.5 52.5 20.2 As shown in Table 1, this table defines the correspondence between the logical number of the sensor array and the physical space, as well as the initial state, which is used for spatial position extraction and verification in the coordinate registration submodule.

[0029] The filter output submodule constructs state prediction and measurement update quantities based on the pressure spatiotemporal mapping set, performs prediction residual calculation and gain correction according to the Kalman filter recursive relationship, performs smoothing and out-of-bounds removal of time amplitude and performs time sequence reorganization to generate pressure time series. Construct a state vector for each independent coordinate point ,in express Pressure amplitude at any given moment To represent the rate of change of pressure, establish the state transition equation. The transition matrix , Sampling interval Set the process noise covariance matrix The diagonal element is Measurement noise covariance Set as The prediction step of the Kalman filter is performed, utilizing the previous time step. The posterior estimate (e.g.) Calculate the current time. Prior prediction value Obtain the actual measurement value at the current moment from the mapping set. (e.g., after correction of previous steps) ), calculate the predicted residual Calculate Kalman gain Assuming the current prediction error covariance Observation matrix ,but Perform measurement update steps to correct the state estimate. Update the error covariance matrix The updated amplitude sequence is smoothed using a five-point weighted moving average, with the weight vector set to... If at the current moment The amplitudes of the two points before and after it are respectively Calculate the smoothing value Finally, the effective boundary of the physiological pressure amplitude was set as... ,examine Whether it exceeds the limit, if the calculation result is If the data is normal, it will be forced to zero; otherwise, it will be retained. The processed data points will be sorted according to their timestamps. The absolute order is reassembled into a continuous data stream to generate the final stress time series.

[0030] Specifically, such as Figure 2 , 4 As shown, the timing and phase analysis module includes: The pressure sequence alignment submodule calls the pressure time series, collects pressure sampling points of the sensing unit, constructs a distance matrix based on the pressure difference of the sampling points, matches the corresponding relationship of the sampling points according to the path with the minimum cumulative difference, rearranges the sequence time index, and generates a time alignment offset sequence. The sequence from the stress time series targeting the left trapezius muscle monitoring point in the neck was used as the baseline sequence. The sequence of monitoring points at the right-side symmetrical position is used as the target sequence. Set the sampling frequency to The length of the segment containing one complete neck flexion movement is... Data fragments from sampling points, constructing a dimension of Distance cost matrix For each element in the matrix First, calculate the local Euclidean distance between the two points. For example, in the first Each sampling point, baseline pressure value Target pressure value The local distance is calculated. Then, based on the recursive cumulative formula The cumulative difference is calculated in this formula. This represents the matching cost at the current point. The term represents the minimum original path cost extending to the current point from the left, below, or lower left. The aim is to find a non-linear regular path that minimizes the overall morphological difference between two sequences. Assume the cumulative costs of the preceding positions are respectively... , , The cumulative cost at the current point After traversing the entire matrix, start from the endpoint. We begin by backtracking based on the minimum cumulative cost gradient to extract the optimal matching path composed of coordinate points. If there are points in the path This indicates the first step of the benchmark sequence. The sampling time corresponds to the first sampling time of the target sequence. Calculate the index difference at each sampling time. This indicates that there is a [something] here. The time offset of each sampling point is used to arrange the index differences of the points on the path in order, generating a time-aligned offset sequence.

[0031] The phase difference extraction submodule obtains the pressure values ​​of adjacent sensing units at the corresponding positions on the registration path based on the time alignment offset sequence, performs time interval calculation according to the registration path index difference, marks the intervals with symbols and arranges them in the path order to generate a unit phase difference value vector. Based on time-aligned offset sequence and corresponding best matching path Iterate through each matching pair node on the path. Read the reference sensing unit respectively Pressure value at any moment and target sensing unit in Pressure value at any moment At the same time, combined with the sampling period The conversion of physical time intervals is calculated using the following formula: In this formula and The target and baseline sequences are respectively in the 1st... The time index of each matching node. The dimensionless index difference is converted into a physically meaningful time difference (milliseconds) to quantify the force phase difference between two muscle groups during the execution of a movement, such as for path nodes. Substituting into the formula, we get The corresponding pressure value at this time is shown in number 3 of Table 2. If the path node is Then the calculation yields The calculated time interval values ​​are marked with signs: a positive sign indicates that the target sequence lags behind, and a negative sign indicates that the target sequence leads. Values ​​in path order Store them sequentially into a vector space, for example, generate vectors. The results indicate that there is a delay in activation of the right-side muscle group during the initial stage of the movement, generating a unit phase difference vector.

[0032] Table 2: Pressure Phase Alignment Data for Bilateral Neck and Shoulder Muscle Groups Sampling sequence number Path baseline index ( ) Path target index ( ) Reference pressure value (normalized) Target pressure value (normalized) Phase difference (ms) State determination 1 10 10 156.5 152.0 0.0 synchronous 2 15 18 180.2 175.5 30.0 Delay 3 20 24 210.8 205.3 40.0 Delay 4 35 33 190.4 195.1 -20.0 Advanced 5 50 50 145.0 144.8 0.0 synchronous Table 2 lists the key node data extracted based on the dynamic time warping path, showing the index correspondence between the benchmark and target sequences at different times, the pressure amplitude, and the calculated phase time difference, which are used for subsequent phase classification and determination.

[0033] The phase classification and aggregation submodule extracts the symbol and interval data based on the unit phase difference vector, performs advance and delay state determination based on the zero-crossing benchmark, and writes the determination label and corresponding phase difference value into the sequence structure in unit order to generate a time-series phase parameter set. Based on the unit phase difference vector Set the zero-crossing reference interval as This interval is set based on the natural physiological response delay time controlled by the human neuromuscular system, and is used to accommodate normal measurement errors and minor physiological fluctuations, traversing each element in the vector. Execute status determination logic, if It is determined to be in a "delayed" state and a label is assigned. ,like It is determined to be in an "early" state and a label is assigned. If the value falls within If the value is within the specified range, it is determined to be in a "synchronous" state and a label is assigned. For example, regarding the third item of data in Table 2 ,because The fourth data item was determined to be "delayed". ,because If the condition is determined to be "early", the determination label is combined with the original phase difference value to construct a structured data pair. Statistically analyze the phase distribution characteristics throughout the entire action cycle and calculate the cumulative delay. ,in Let be the indicator function, taking the value 1 if the condition is met and 0 otherwise. Assume there are three lag terms in the vector. ,but Finally, the structure containing time index, phase difference, classification label and statistical accumulation is written into the system database in the order of unit physical location to generate a time-series phase parameter set.

[0034] Specifically, such as Figure 2 , 5 As shown, the force direction vector module includes: The coordinate difference calculation submodule calls the timing phase parameter set to perform component comparison between the spatial coordinates of the sensing unit and the coordinates of adjacent units, calculates the difference for the coordinate axes and performs sign verification, applies phase weights to the difference components and performs weighted integration to generate a spatial difference vector set. The generated timing phase parameter set is invoked, which stores the neck and shoulder taping areas. The phase synchronization status data of the sensing units in the array are used as the benchmark analysis object, with the sensing unit located in the middle of the trapezius muscle selected as the benchmark. For example, the index is... The unit reads its physical space coordinates. Simultaneously, it retrieves its right-side adjacent unit in the horizontal direction. Read coordinates The difference between the coordinate axis components is calculated by subtracting the horizontal coordinate of the reference unit from the horizontal coordinate of the adjacent unit to obtain the difference in the horizontal component. The difference between the vertical components is obtained by subtracting the vertical coordinates. Then, the phase difference between the two units is extracted from the parameter set. Assuming the record value is To establish a functional topological distance that includes the time dimension, a phase weight coefficient is set. for and the benchmark reference period for First, calculate the ratio of the phase difference to the reference period, i.e. Multiplying this ratio by the weighting factor yields Then the product result is compared with a constant. Adding them together gives the distance correction factor. The functional horizontal distance is calculated by multiplying the difference in the physical level components using this correction factor. The vertical component is calculated similarly and remains the same. The calculation process shows that the functional connection distance is stretched due to the presence of phase delay, affecting the array. This process is repeated for each element and its four-neighbor relationship. For boundary elements, only the existing neighborhood directions are calculated, and the calculated weighted coordinate difference vector is paired with its corresponding element index. Associative storage generates a spatial difference vector set containing functional topological information.

[0035] The pressure difference vector extraction submodule performs normalization conversion on the pressure difference components based on the correspondence between the spatial difference vector set and the pressure difference execution components of adjacent units. It then calls the spatial difference vector set to perform direction mapping and scale correction on the conversion sequence, generating a pressure difference feature vector group. Based on the spatial difference vector set, traverse each vector pair and synchronously collect the pressure sampling values ​​of adjacent sensing units at the corresponding time, continuing in the manner described above. and Taking a unit as an example, read the pressure value of the reference unit. (about ), adjacent unit pressure value (about ), calculate the components of adjacent pressure differences Set the sensor saturation pressure threshold. for and nonlinear correction index for First, calculate the ratio of the pressure difference to the saturation threshold, i.e. Then, an exponential operation is performed on the ratio to calculate... of The normalized magnitude coefficient is obtained by exponentiation. Call the calculated weighted spatial difference vector The horizontal eigencomponents are calculated by multiplying each component of the vector by a normalized amplitude coefficient. Vertical component The vector direction is determined based on the sign of the pressure difference. If the adjacent pressure is greater than the reference pressure, the direction remains unchanged; otherwise, the direction is reversed. This operation is performed on the neighborhood relationship to obtain a series of vector data with clear magnitude and direction as shown in Table 3, generating a pressure difference feature vector group.

[0036] Table 3: Calculation Table of Pressure Gradient and Direction Vector in Neck and Shoulder Region Cell index pair (IDA-IDB) Physical distance (mm) Phase delay (ms) Pressure difference (Dig) Correction coefficient Result vector X component Resulting vector Y component 28-29(3，4-3，5) 7.5 25.0 302 0.020 0.180 0.000 28-20(3，4-2，4) 7.5 -10.0 -150 0.007 0.000 -0.057 28-36(3，4-4，4) 7.5 5.0 50 0.001 0.000 0.008 28-27(3，4-3，3) 7.5 0.0 0 0.000 0.000 0.000 Table 3 shows the pressure difference and corresponding characteristic vector components calculated for the central element (index 28) and its surrounding neighboring elements. The data demonstrates the tension distribution in the local area.

[0037] The direction field superposition generation submodule calls the pressure difference feature vector group and the positional relationship of the area unit to perform vector correspondence superposition, performs amplitude correction on the superposition result according to the superposition reference scale and performs direction consistency integration to generate force direction vector field data; The pressure difference feature vector group is invoked, and a local coordinate system is established for each independent sensing unit. Feature vectors in the neighborhood centered on that unit are retrieved, using the units in Table 3 as an example. For example, its associated feature vectors include those pointing to the right. Pointing upwards (corresponding to index 20, pointing inwards due to reduced pressure) Pointing downwards (corresponding to index 36, pointing to cell 36 due to increased pressure). And the left side Perform algebraic summation on the X-axis and Y-axis components of the above vector respectively to calculate the resultant vector X component. , Y component Set the reference scale for the output field strength. for and normalized damping coefficient for First, divide the component values ​​of the resultant vector by the damping coefficient to obtain the intermediate variable. , Next, the hyperbolic tangent function is performed on the intermediate variable to limit numerical divergence, and the calculation is performed. , Finally, the calculation result is multiplied by the reference scale. The X component of the final field vector is obtained. With Y component This result indicates that in the unit There exists a resultant tension force that is mainly directed to the right and slightly biased to the downward side, generating force direction vector field data.

[0038] Specifically, such as Figure 2 , 6 As shown, the bonding path adaptation module includes: The vector field analysis submodule detects the position direction component based on the force direction vector field data, compares the difference between adjacent direction components, filters data with a difference greater than the direction change threshold, makes a consistency judgment based on the change amplitude, and generates the regional direction change rate value. Access the force direction vector field data, which includes the area within the neck and shoulder taping region. The force direction vector at each monitoring point in the grid, expressed in coordinates. Vector at location For example, first calculate its direction angle using the arctangent function. Set the preset sampling window to be centered on this point. Neighborhood, traversing the rest within the window For each neighboring vector, calculate the absolute value of the direction angle difference with the center vector. For example, for the right neighboring point... The vector angle is The difference If the set of adjacent differences within the window is Perform statistical analysis on the set and calculate the mean. Calculate the standard deviation: ; Based on the normal distribution confidence interval principle, the mean and standard deviation of the directional components are discretized into intervals, and the normal fluctuation interval is set as follows: The upper limit of the interval, i.e., the threshold for direction change, is calculated. Then, the directional differences at the center points were filtered and compared to find the current maximum difference. Less than the threshold However, in another high-stress area... At that point, the calculated difference is And its corresponding local threshold is If the difference exceeds the threshold, it is determined that there is a drastic change in direction at that point. Consistency is judged based on the magnitude of the change, and the exceedance ratio is calculated. ,like If more than half of the points in the neighborhood show a trend of deflection in the same direction, then the region is confirmed as an area of ​​abnormal twisting of muscle fiber direction. This ratio is used as a quantitative indicator to generate the region direction change rate value.

[0039] The path deviation calculation submodule calls the regional direction change rate value and obtains the direction component of the coordinate point based on the preset path coordinate point. It calculates the angle with the direction component at the same position of the vector field, filters the angles that are greater than the angle amplitude threshold and performs a judgment to obtain the path deviation angle value. Call the region direction change rate value and load the preset set of coordinate points for the neck trapezius muscle taping path. Select the first one Key coordinate points (physical location) (), obtain the ideal tangent direction component of the point planned in the preset rehabilitation plan. (angle (i.e., horizontally to the right), while simultaneously indicative of the actual force direction component at the same location in the index vector field. (angle The original deviation angle is obtained by performing angle calculation. To determine whether the deviation falls within the abnormal range requiring intervention, a preset path length range is considered (e.g., the entire area covered by the bandage). The deviation angle data of the sampling points (length) are statistically analyzed to construct a system containing... The cumulative distribution sequence of the samples is shown in Table 4. The sequence is divided into quantile intervals, and the effective control interval is set as the cumulative probability. The coverage area is determined by extracting the angle value corresponding to the quantile as the boundary value of the angle interval, i.e., the angle amplitude threshold. The deviation angle of the current point With threshold Screening and comparison were conducted because The point was determined to have a significant risk of taping path failure. This deviation means that the original path failed to effectively cover the actual main muscle line. The difference was then calculated. The corresponding position index is retained, and this process is repeated for points on the path to generate the path deviation angle value.

[0040] Table 4: Data Table of Adhesion Path Direction Deviation Detection Path node index Preset orientation angle (°) Measured field orientation angle (°) Deviation Angle (°) 80th percentile threshold (°) Judgment result 1 0.0 -2.5 2.5 12.0 normal ... ... ... ... ... ... 15 0.0 -20.5 20.5 12.0 abnormal deviation 16 5.0 -8.0 13.0 12.0 abnormal deviation ... ... ... ... ... ... 50 45.0 42.0 3.0 12.0 normal As shown in Table 4, the preset and measured directional data of key nodes on the path are listed. By comparing the statistical thresholds, abnormal nodes that need to be adjusted are identified.

[0041] The path coordinate correction submodule adjusts the coordinates based on the path deviation angle value and the preset path coordinate points, superimposes the adjustment amount with the original coordinate points, calls the regional direction change rate value to judge the rationality of the superimposed coordinates, and generates a tape path control instruction set. Based on the path deviation angle value And based on preset path coordinates Initiate coordinate correction logic, adjust coordinates based on offset angle, and set spatial adjustment coefficient. Calculate the corrected displacement The correction direction is determined to be perpendicular to the preset path direction and pointing towards the measured force field direction, i.e., along... Offset in the negative axis direction to construct an adjustment vector The adjustment amount is superimposed on the original coordinate points to calculate the candidate corrected coordinates. At this point, the region direction change rate value is used to determine the rationality of the superimposed coordinates and to retrieve candidate positions. Rate of change of direction at ,like This indicates that the location is at the center of extreme stress instability, and direct application would result in poor adhesion or excessive stimulation. Therefore, a damping factor is introduced. Reduce the adjustment amount and update the adjustment vector as follows: The final corrected coordinates were determined to be... ,like Then maintain the original adjustment amount and calculate the final coordinate deviation. The control pulse count of the servo motor or the deflection command of the laser projector is converted into a set of bonding path control commands.

[0042] Specifically, such as Figure 2 , 7 As shown, the support control module includes: The pressure difference calculation submodule calculates the difference and extracts the absolute value based on the target pressure threshold and real-time pressure feedback value in the taping path control instruction set. It then performs a quantization compression action based on the single-value data after the absolute value is extracted to generate the pressure difference value. The target pressure threshold is generated by calibration based on the thickness parameters of the patching material and the original pressure statistics of the patching area, and is imported before patching is performed; Based on the key node locations determined in the taping path control instruction set, the preset target pressure threshold parameters corresponding to those locations are invoked. First, the target pressure threshold calibration generation process is executed. This process calculates based on the physical properties of the selected high-elasticity taping material and the static baseline pressure distribution in the patient's neck and shoulder taping area, and sets the material thickness parameters. and the material stiffness coefficient measured by tensile testing Simultaneously, the raw statistical average pressure of the area in the unapplied state was collected. (ADC sampled values), using the linear enhancement model formula Calculate the target threshold in this formula. Representing the basic pressure reference, the product term represents the additional tension gain introduced by material thickness and stiffness, which is obtained by substituting into the numerical calculation. This value serves as an ideal reference for subsequent closed-loop control. The sensor acquisition logic is then activated to obtain the current real-time pressure feedback value. Perform interpolation Extract the absolute value from the original difference. To eliminate the influence of high-frequency noise from the sensor on minute pressure fluctuations and to compress the dynamic range, a nonlinear quantization compression operation is performed based on the absolute data, using a logarithmic compression formula. ,in Set the system noise floor standard deviation to The advantage of this formula is that it enhances the sensitivity to low-amplitude pressure deviations through natural logarithmic transformation, while suppressing control overshoot caused by large-amplitude deviations. Substituting this into numerical calculations... If the real-time pressure is (In an overly tight state) Calculations yielded The calculated compressed single-value data As the core control variable of the system, it generates the pressure difference.

[0043] The support instruction generation submodule calls the pressure difference and the correction path parameters obtained from the parsing of the patching path control instruction set, performs a weighted operation on the two to construct directional and force components, and performs a combined operation based on the directional and force components to obtain the support adjustment instruction vector. The calculated pressure difference value is called. Simultaneously, it analyzes the correction path parameters in the tape path control instruction set and extracts the coordinate adjustment vector for the current node. To construct physically meaningful mechanical commands, a weighted operation is performed on both. First, the direction component is calculated based on the correction vector. Using the vector normalization formula Calculate the modulus ,but This unit vector clarifies the geometric direction in which the external support force should be applied, and then the force components are constructed. Gain adjustment formula is used ,in Set the force-to-pressure conversion gain coefficient to , Based on holding force set as The advantage of this formula lies in its ability to transform the dimensionless pressure difference into a mechanical amplitude recognizable by the actuator through linear mapping, which can then be substituted into numerical calculations. Finally, a combined operation is performed based on the direction and force components, multiplying the scalar force amplitude by the direction unit vector to obtain the final support adjustment command vector. This result indicates that the system needs to apply pressure in the vertically downward direction. The auxiliary support force is used to correct the taping effect. The calculation results under different pressure differences are summarized in Table 5, and a support adjustment command vector is generated.

[0044] Table 5: Data Table for Generation of Taping Support Force Command Test case number Target pressure (ADC) Real-time pressure (ADC) Difference Force Components (N) Correction direction vector Output instruction vector (X, Y)N 1 1800 1650 2.77 14.35 [0，-1] [0，-14.35] 2 1800 1750 1.79 9.45 [0，-1] [0，-9.45] 3 1800 1800 0.00 0.50 [0，0] [0，0] 4 1800 1950 2.77 14.35 [0，1] [0，14.35] Table 5 shows the magnitude and direction of the support force generated by the algorithm under different real-time pressure feedback conditions, demonstrating the mapping relationship from pressure deviation to mechanical command.

[0045] The stability verification submodule calls the support adjustment command vector and the real-time pressure feedback value, performs an amplitude comparison based on the directional component and the real-time pressure feedback value and obtains the comparison value, performs an interval judgment on the comparison value and the target pressure threshold, and generates a stable bonding support state. Invoke support adjustment command vector After the actuator completes the mechanical loading action, the real-time pressure feedback value at that location is collected again. The stability verification process is executed, and the amplitude is compared with the real-time pressure feedback value based on the directional component to calculate the approximation index after pressure correction. The relative error complement formula is used. ,in The advantage of this formula is that it transforms the absolute error of pressure control into... to Standardized similarity scores between them, substituted into numerical calculations, absolute error relative error ,but Subsequently, a range judgment was performed on the comparison quantity and the target pressure threshold, and three stability judgment ranges were set: stable region Adjustment area Failure Zone Calculation results Compared with the interval boundary, because The current patch support is determined to be in a "stable" state if the newly collected pressure value is... ,but If the pressure falls into the "adjustment zone", a new round of pressure difference calculation and instruction update will be triggered. Conversely, if it is in a stable state, the current support parameters will be locked and a confirmation signal will be output to generate a stable binding support state.

[0046] Please see Figure 8 The pressure-sensor-based cervical and shoulder rehabilitation taping adaptation control method is implemented based on the aforementioned pressure-sensor-based cervical and shoulder rehabilitation taping adaptation control system, and includes the following steps: S1: The pressure signal of the neck and shoulder muscle group is collected by the piezoresistive array sensor. The pressure amplitude and timestamp of the sensing unit are obtained. Combined with the spatial coordinates, a pressure time-space data set is formed. The Kalman filter algorithm is used to filter and remove noise, and the pressure time series is output. S2: Call the pressure time series, use the dynamic time warping algorithm to calculate the phase difference of signals from adjacent sensing units, extract phase advance and delay parameters, perform phase difference classification, and form a time-series phase parameter set; S3: Call the timing phase parameter set, combine the spatial coordinates of the sensing unit to calculate the pressure difference and position relationship between adjacent units, derive the pressure change direction and amplitude vector of the stressed area, perform vector superposition operation, and output the stress direction vector field data; S4: Combining the force direction vector field data, calculate the deviation angle between the taping path and the force direction of the muscle group based on the vector field characteristics, correct the preset path coordinate points, form a taping path adjustment instruction set, and transmit it to the support control module; S5: Call the tape path control instruction set, calculate the electronic support adjustment instruction by comparing the target pressure threshold in the instruction set with the real-time pressure feedback value, control the tape support structure actuator to adjust the support direction and force along the correction path, and perform cyclic verification of the support adjustment instruction based on the pressure feedback signal to output a stable tape support state.

[0047] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A pressure-sensing-based cervical and shoulder rehabilitation taping adaptation control system, characterized in that, The system includes: The pressure acquisition module acquires the taping pressure signal of the neck and shoulder muscles through a piezoresistive array sensor, obtains the pressure amplitude and timestamp of the sensing unit, and combines it with spatial coordinates to form a pressure time-space data set. The Kalman filter algorithm is used to filter and remove noise, and outputs the pressure time series, which is then transmitted to the time-phase analysis module. The timing phase analysis module calls the pressure time series, uses the dynamic time warping algorithm to calculate the phase difference of signals from adjacent sensing units, extracts phase advance and delay parameters, performs phase difference classification, forms a timing phase parameter set, and transmits it to the force direction vector module. The force direction vector module calls the time phase parameter set, calculates the pressure difference and position relationship between adjacent units by combining the spatial coordinates of the sensing unit, derives the pressure change direction and amplitude vector of the force area, performs vector superposition operation, outputs the force direction vector field data, and transmits it to the taping path adaptation module. The taping path adaptation module, in conjunction with the force direction vector field data, calculates the deviation angle between the taping path and the force direction of the muscle group based on the vector field characteristics, corrects the preset path coordinate points, forms a taping path adjustment instruction set, and transmits it to the support control module.

2. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 1, characterized in that, The pressure time series includes a filtered pressure amplitude sequence, a corresponding timestamp sequence, and a set of spatial coordinates. The time-series phase parameter set includes the phase difference value between adjacent sensing units, phase advance, phase delay, and phase difference category label. The force direction vector field data includes the pressure change direction vector, pressure change amplitude vector, and regional vector superposition field of the force area. The taping path control instruction set includes the deviation angle value between the path and the force direction and the corrected path coordinate point sequence.

3. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 1, characterized in that, The pressure acquisition module includes: The array acquisition submodule acquires the electrical signals of the piezoresistive array sensor in the taping area of ​​the neck and shoulder muscles. It performs amplitude conversion and records the timestamp based on the resistance change of the sensing unit. It performs sequential arrangement and indexing of amplitude and timestamp, corrects abnormal jump items, and establishes the original quantity of pressure amplitude time sequence. The coordinate registration submodule performs coordinate extraction based on the original pressure amplitude time series and the array layout table, calls the timestamp to match the amplitude and coordinates, corrects missing coordinates and abnormal spatial offsets, and obtains the pressure spatiotemporal mapping set. The filter output submodule constructs state prediction and measurement update quantities based on the pressure spatiotemporal mapping set, performs prediction residual calculation and gain correction according to the Kalman filter recursive relationship, performs smoothing and out-of-bounds removal on the time amplitude, and performs time sequence reorganization to generate a pressure time series.

4. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 1, characterized in that, The timing phase analysis module includes: The pressure sequence alignment submodule calls the pressure time series, collects pressure sampling points of the sensing unit, constructs a distance matrix based on the pressure difference of the sampling points, matches the corresponding relationship of the sampling points according to the path with the minimum cumulative difference, rearranges the sequence time index, and generates a time alignment offset sequence. The phase difference extraction submodule obtains the pressure value of adjacent sensing units at the corresponding position on the registration path based on the time alignment offset sequence, performs time interval calculation according to the registration path index difference, marks the interval with symbols and arranges them in the path order to generate a unit phase difference value vector. The phase classification and aggregation submodule extracts the symbol and interval data based on the unit phase difference vector, performs advance and delay state determination based on the zero-crossing reference, and writes the determination label and corresponding phase difference value into the sequence structure in unit order to generate a time-series phase parameter set.

5. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 1, characterized in that, The force direction vector module includes: The coordinate difference calculation submodule calls the time-series phase parameter set to perform component comparison between the spatial coordinates of the sensing unit and the coordinates of adjacent units, calculates the difference for the coordinate axes and performs sign verification, applies phase weights to the difference components and performs weighted integration to generate a spatial difference vector set. The pressure difference vector extraction submodule performs normalization conversion on the pressure difference components based on the spatial difference vector set and the corresponding pressure difference components of adjacent units. It then calls the spatial difference vector set to perform direction mapping and scale correction on the conversion sequence to generate a pressure difference feature vector group. The direction field superposition generation submodule calls the pressure difference feature vector group and the positional relationship of the area unit to perform vector correspondence superposition, performs amplitude correction on the superposition result according to the superposition reference scale and integrates the direction consistency to generate force direction vector field data.

6. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 1, characterized in that, The taping path adaptation module includes: The vector field analysis submodule detects the position direction component based on the force direction vector field data, compares the difference between adjacent direction components, filters data whose difference is greater than the direction change threshold, makes a consistency judgment based on the change amplitude, and generates the regional direction change rate value. The path deviation calculation submodule calls the regional direction change rate value and obtains the direction component of the coordinate point based on the preset path coordinate point. It performs angle calculation with the direction component at the same position of the vector field, filters angles greater than the angle amplitude threshold, and performs judgment to obtain the path deviation angle value. The path coordinate correction submodule adjusts the coordinates based on the path deviation angle value and the preset path coordinate points, superimposes the adjustment amount with the original coordinate points, calls the regional direction change rate value to make a reasonable judgment on the superimposed coordinates, and generates a bonding path control instruction set.

7. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 6, characterized in that, The direction change threshold is based on the original statistical results of the direction components of the force direction vector field data within a preset sampling window. It is obtained by dividing the mean and standard deviation of the direction components within the preset sampling window into discrete intervals, resulting in the upper limit of the interval. The angle amplitude threshold is based on the original statistical results of the direction components of the preset path coordinate points within the preset path length range. It is obtained by dividing the cumulative distribution of the change angle of the direction components within the preset path length range into quantile intervals to obtain the angle interval boundary value.

8. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 1, characterized in that, The support control module calls the taping path adjustment instruction set, calculates the electronically controlled support adjustment instruction by comparing the target pressure threshold in the instruction set with the real-time pressure feedback value, controls the taping support structure actuator to adjust the support direction and force along the correction path, and performs cyclic verification of the support adjustment instruction according to the pressure feedback signal, and outputs a stable taping support state. The stable taping support state includes the target pressure threshold setting value, real-time pressure feedback signal value, electronic support adjustment command parameters, final support direction, final support force, and closed-loop verification pass mark.

9. The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to claim 8, characterized in that, The support control module includes: The pressure difference calculation submodule calculates the difference and extracts the absolute value based on the target pressure threshold and real-time pressure feedback value in the patching path control instruction set. It then performs a quantization compression action based on the single-value data after the absolute value is extracted to generate the pressure difference amount. The support instruction generation submodule calls the pressure difference and the correction path parameters obtained by parsing the patching path control instruction set, performs a weighted operation on the two to construct directional and force components, and performs a combination operation based on the directional and force components to obtain the support adjustment instruction vector. The stability verification submodule calls the support adjustment command vector and the real-time pressure feedback value, performs an amplitude comparison based on the directional component and the real-time pressure feedback value and obtains the comparison value, performs an interval judgment on the comparison value and the target pressure threshold, and generates a stable bonding support state.

10. A method for adjusting the fit of cervical and shoulder rehabilitation taping based on pressure sensing, characterized in that, The neck and shoulder rehabilitation taping adaptation control system based on pressure sensing according to any one of claims 1-9 includes the following steps: S1: The pressure signal of the neck and shoulder muscle group is collected by the piezoresistive array sensor. The pressure amplitude and timestamp of the sensing unit are obtained. Combined with the spatial coordinates, a pressure time-space data set is formed. The Kalman filter algorithm is used to filter and remove noise, and the pressure time series is output. S2: Call the pressure time series, use the dynamic time warping algorithm to calculate the phase difference of signals from adjacent sensing units, extract phase advance and delay parameters, perform phase difference classification, and form a time-series phase parameter set; S3: Call the time-phase parameter set, combine the spatial coordinates of the sensing unit to calculate the pressure difference and positional relationship between adjacent units, derive the pressure change direction and amplitude vector of the stressed area, perform vector superposition operation, and output the force direction vector field data; S4: Combining the force direction vector field data, calculate the deviation angle between the taping path and the force direction of the muscle group based on the vector field characteristics, correct the preset path coordinate points, form a taping path adjustment instruction set, and transmit it to the support control module; S5: Call the patching path control instruction set, calculate the electronic support adjustment instruction by comparing the target pressure threshold in the instruction set with the real-time pressure feedback value, control the patching support structure actuator to adjust the support direction and force along the correction path, and perform cyclic verification of the support adjustment instruction according to the pressure feedback signal to output a stable patching support state.

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