Muscle state evaluation method based on multi-physiological-signal full-fabric sensing device

Abstract

The invention relates to a muscle state evaluation method based on a multi-physiological-signal full-fabric sensing device, and the method comprises the steps: collecting a plurality of physiological signals of a user at the same site through a time division multiplexing strategy and a full-fabric sensing device, the plurality of physiological signals comprise at least two of an electrical impedance signal, an electromyographic signal, a pressure signal and a temperature signal; performing signal processing on the plurality of physiological signals to obtain a target transmission signal corresponding to each physiological signal, and transmitting the target transmission signals to the terminal equipment; and performing data processing operation on the target transmission signal, and determining corresponding muscle physiological state information according to a data processing result so as to evaluate the muscle state of the target user through the muscle physiological state information. Therefore, the problems that at present, a human body pressure signal, a temperature signal, an electromyographic signal and a skin electrical impedance signal cannot be monitored at the same site, the device rigidity is large, the wearing comfort is poor, and the device is not suitable for long-term monitoring are solved.

Description

Technical Field

[0001] This application relates to the technical field of muscle state assessment, and particularly to a muscle state assessment method based on a multi-physiological signal all-fabric sensor device. Background Art

[0002] Skeletal muscle is the main executive organ of human movement. During the process of skeletal muscle contraction or relaxation, various physiological signals are generated or changed, including the generation of force muscle signals, the change of corresponding body surface skin temperature signals, the generation of electromyogram signals, and the change of skin surface impedance, etc.

[0003] When the human muscle contracts during exercise, a tiny volume change will occur, which will cause mechanical strain in the surrounding tissues and generate pressure signals. By attaching a pressure sensor on the skin surface, the pressure signals generated during muscle contraction can be measured to reflect the activity state of the muscle.

[0004] The normal body temperature of a human is usually maintained between 36.5°C and 37.5°C. The body temperature within this range helps the activity of enzymes, cell metabolism, and the coordinated operation of various systems. When the body temperature deviates from this range, it may lead to dysfunction of the body. Monitoring body temperature can effectively evaluate the health status of an individual and detect abnormalities in a timely manner. During human movement, the metabolic rate of muscles increases, resulting in more heat generation. Therefore, the muscle temperature usually rises. By measuring the skin surface temperature, the exercise intensity and the working state of the muscles can be evaluated.

[0005] When a muscle contracts, the electrical signals generated by motor neurons can be recorded through electrodes. Electromyogram (EMG) signals can provide information about muscle contraction intensity, frequency, duration, etc., which helps to evaluate the health status and function of muscles. Impedance signals can help monitor the body's hydration status and its electrolyte balance, and at the same time can help evaluate physiological parameters such as body fat percentage and muscle mass.

[0006] Existing pressure, temperature, electromyogram signal, and impedance sensor devices are mostly single-signal or dual-mode sensing, unable to measure four physiological signals at the same site, and unable to comprehensively evaluate the state of muscles. Moreover, the devices have high stiffness and low flexibility, resulting in low wearing comfort and are not suitable for long-term monitoring, as described below.

[0007] Currently, the technologies for measuring electromyography (EMG) signals are divided into non-invasive and invasive. Among them, non-invasive methods have the advantages of being non-invasive and comfortable. Researchers have developed a flexible sensor device capable of measuring surface electromyography (sEMG) signals. The substrate and packaging material use polyimide (PI), and the electrodes are made of Au with a serpentine mesh structure, which has a certain degree of stretchability. By analyzing the time-domain characteristics such as the amplitude of the sEMG signals extracted from grip strength tests at different force levels, the positive correlation between muscle strength and the time-domain characteristics of sEMG signals was revealed; the degree of muscle fatigue was evaluated by analyzing the frequency-domain characteristics of the signals.

[0008] However, the technology for measuring EMG signals only uses EMG signals, a single physiological signal, to evaluate the state (strength and fatigue level) of muscles, and does not extract multiple physiological signal parameters for a more comprehensive evaluation of the physiological state of muscles; in addition, although the above-mentioned measuring device uses polyimide (PI) flexible materials, it still has a certain degree of rigidity, with low wearability comfort and insufficient breathability where the PI film is covered.

[0009] Existing devices that integrate the detection of posture information, surface electromyography signals, and skin conductivity signals. The technical components of this device include a sensor group, a data processing mechanism, and a data transmission mechanism. The sensor group collects three physiological signals. The data processing mechanism analyzes the data to obtain information on the activity level of EMG signals and the median frequency information of the power spectrum. The data transmission mechanism transmits the posture information, skin conductivity information, and processed EMG information to an evaluation device. Subsequently, the evaluation device calculates the degree of muscle fatigue, providing data support for doctors to facilitate the formulation of more effective rehabilitation training plans for patients; however, this device can only collect posture signals, surface electromyography signals, and skin conductivity signals, and cannot collect force muscle signals and temperature signals. The physiological signal parameters selected for evaluating muscle status are not comprehensive enough; in addition, each signal acquisition sensor in the sensor group has a relatively large rigidity, resulting in low wearability comfort.

[0010] In addition, existing technologies can also measure the body impedance value of a user when holding a handle with a device for detecting the health of human muscles, which includes a handle and a base plate, to evaluate the muscle mass of the limbs, measure the pressure value when gripping the handle forcefully to evaluate the hand grip strength, and evaluate the lower limb strength through the pressure sensors on the base plate when the user performs squat-to-stand or sit-to-stand tests; in addition, the device can also measure the upper arm pulling force when the user performs a stretching test. These measurement results, combined with the user's age and gender, can comprehensively evaluate the muscle health status of the user. In addition, this device can also communicate with the portable device carried by the user to obtain the user's walking speed and / or distance, further improving the health assessment. The purpose of this patent is to provide a fast and convenient method for comprehensively evaluating the muscle health of users, aiming to improve the user experience, and is particularly suitable for individuals who need to pay attention to muscle health, such as the elderly or users with specific health needs.

[0011] However, this device is too large, complex to operate, costly, not wearable, and unable to collect temperature signals (related to fatigue level, etc.) and electromyography signals (related to muscle activation level and fatigue level), and unable to collect multiple physiological signals of the human body at the same site.

[0012] In summary, the current inability to monitor human body pressure signals, temperature signals, electromyography signals, and skin impedance signals at the same site, as well as the large stiffness of the device, result in poor wearing comfort and are not suitable for long-term monitoring, which urgently needs to be solved. Summary of the Invention

[0013] This application provides a muscle state assessment method based on a multi-physiological signal all-fabric sensor device to solve the problems that currently, human body pressure signals, temperature signals, electromyography signals, and skin impedance signals cannot be monitored at the same site, and the large stiffness of the device leads to poor wearing comfort and is not suitable for long-term monitoring.

[0014] An embodiment of the first aspect of this application provides a muscle state assessment method based on a multi-physiological signal all-fabric sensor device, including the following steps: collecting multiple physiological signals of a target user at the same site by a preset time-division multiplexing strategy and a pre-constructed all-fabric sensor device, where the multiple physiological signals include at least two of impedance signals, electromyography signals, pressure signals, and temperature signals; performing signal processing operations on the multiple physiological signals to obtain target transmission signals corresponding to each physiological signal in the multiple physiological signals, and transmitting the target transmission signals to a preset terminal device; using the preset terminal device to perform data processing operations on the target transmission signals to obtain data processing results corresponding to the multiple physiological signals, and determining muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information.

[0015] Optionally, in an embodiment of this application, the step of collecting multiple physiological signals of a target user at the same site by a preset time-division multiplexing strategy and a pre-constructed all-fabric sensor device, where the multiple physiological signals include at least two of impedance signals, electromyography signals, pressure signals, and temperature signals, includes: collecting the pressure signal and the temperature signal of the target user at the same site based on the electrical signal conduction layer, pressure and temperature sensitive layer in the all-fabric sensor device; determining the application scenario requirements corresponding to the all-fabric sensor device, and allocating corresponding acquisition time windows and transmission time windows for the impedance signal and the electromyography signal according to the application scenario requirements and the time-division multiplexing strategy; collecting the impedance signal and the electromyography signal at the same site in sequence based on the electrical signal conduction layer, the acquisition time window, and the transmission time window, in combination with a preset time sequence.

[0016] Optionally, in an embodiment of the present application, the performing signal processing operations on the multiple physiological signals to obtain a target transmission signal corresponding to each physiological signal among the multiple physiological signals and transmitting the target transmission signal to a preset terminal device includes: performing signal amplification processing on the pressure signal and the temperature signal to obtain a pressure amplified signal and a temperature amplified signal; performing signal filtering and amplification processing on the impedance signal and the electromyogram signal to obtain an impedance amplified signal and an electromyogram amplified signal, and performing analog-to-digital conversion on the pressure amplified signal, the temperature amplified signal, the impedance amplified signal, and the electromyogram amplified signal to obtain corresponding digital signals; performing signal compression processing on the digital signals to generate target transmission signals corresponding to the pressure signal, the temperature signal, the impedance signal, and the electromyogram signal.

[0017] Optionally, in an embodiment of the present application, the using the preset terminal device to perform data processing operations on the target transmission signal to obtain a data processing result corresponding to the multiple physiological signals and determining muscle physiological state information corresponding to each physiological signal according to the data processing result to evaluate the muscle state of the target user through the muscle physiological state information includes: performing data processing operations on the pressure signal, the temperature signal, the impedance signal, and the electromyogram signal to generate corresponding data processing results; determining the muscle physiological state information of the target user according to the data processing results and transmitting the muscle physiological state information to a target display device to monitor and evaluate the muscle state of the target user, where the muscle physiological state information includes the mean value of the pressure signal, the mean value of the temperature signal, the mean value of the impedance signal, the time-domain characteristics, and the frequency characteristics of the electromyogram signal within a target time period of muscle activity.

[0018] An embodiment of the second aspect of the present application provides a muscle state evaluation device based on a multi-physiological signal all-fabric sensor device, including: an acquisition module, configured to acquire at least two physiological signals among impedance signals, electromyogram signals, pressure signals, and temperature signals of a target user at the same position by a preset time-division multiplexing strategy and a pre-constructed all-fabric sensor device; a signal processing module, configured to perform signal processing operations on the multiple physiological signals to obtain a target transmission signal corresponding to each physiological signal among the multiple physiological signals and transmit the target transmission signal to a preset terminal device; and an evaluation module, configured to use the preset terminal device to perform data processing operations on the target transmission signal to obtain a data processing result corresponding to the multiple physiological signals and determine muscle physiological state information corresponding to each physiological signal according to the data processing result to evaluate the muscle state of the target user through the muscle physiological state information.

[0019] Optionally, in an embodiment of the present application, the acquisition module includes: a first acquisition unit, configured to acquire the pressure signal and the temperature signal of the target user at the same position based on the electrical signal conduction layer, the pressure and temperature sensitive layer in the fully textile sensor device; a distribution unit, configured to determine the application scenario requirements corresponding to the fully textile sensor device, and allocate corresponding acquisition time windows and transmission time windows for the impedance signal and the electromyogram signal according to the application scenario requirements and the time division multiplexing strategy; a second acquisition unit, configured to sequentially acquire the impedance signal and the electromyogram signal at the same position based on the electrical signal conduction layer, the acquisition time window, and the transmission time window, in combination with a preset time sequence.

[0020] Optionally, in an embodiment of the present application, the signal processing module includes: a signal amplification unit, configured to perform signal amplification processing on the pressure signal and the temperature signal to obtain a pressure amplified signal and a temperature amplified signal; an analog-to-digital conversion unit, configured to perform signal filtering and amplification processing on the impedance signal and the electromyogram signal to obtain an impedance amplified signal and an electromyogram amplified signal, and perform analog-to-digital conversion on the pressure amplified signal, the temperature amplified signal, the impedance amplified signal, and the electromyogram amplified signal to obtain corresponding digital signals; a signal compression unit, configured to perform signal compression processing on the digital signals to generate target transmission signals corresponding to the pressure signal, the temperature signal, the impedance signal, and the electromyogram signal.

[0021] Optionally, in an embodiment of the present application, the evaluation unit includes: a data processing unit, configured to perform data processing operations on the pressure signal, the temperature signal, the impedance signal, and the electromyogram signal to generate corresponding data processing results; a display unit, configured to determine the muscle physiological state information of the target user according to the data processing results, and transmit the muscle physiological state information to a target display device to monitor and evaluate the muscle state of the target user, where the muscle physiological state information includes the mean value of the pressure signal, the mean value of the temperature signal, the mean value of the impedance signal, the time domain characteristics, and the frequency characteristics of the electromyogram signal during the target time period of muscle activity.

[0022] An embodiment of the third aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to implement the muscle state evaluation method based on a multi-physiological signal fully textile sensor device as described in the above embodiments.

[0023] In the fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the above-mentioned muscle state evaluation method based on a multi-physiological signal all-fabric sensor device.

[0024] In the fifth aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and the computer program is executed to implement the above-mentioned muscle state evaluation method based on a multi-physiological signal all-fabric sensor device.

[0025] Therefore, the embodiments of the present application have the following beneficial effects:

[0026] The embodiments of the present application can collect multiple physiological signals of a target user at the same position by a preset time-division multiplexing strategy and a pre-constructed all-fabric sensor device. Among them, the multiple physiological signals include at least two physiological signals of impedance signal, electromyogram signal, pressure signal, and temperature signal; perform signal processing operations on the multiple physiological signals to obtain target transmission signals corresponding to each physiological signal in the multiple physiological signals, and transmit the target transmission signals to a preset terminal device; use the preset terminal device to perform data processing operations on the target transmission signals to obtain data processing results corresponding to the multiple physiological signals, and determine muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information. Through the all-fabric sensor device, the present application can measure the human pressure signal, temperature signal, electromyogram signal, and skin impedance signal at the same position, achieve a more comprehensive evaluation of the muscle state, and at the same time, the device has the breathable, flexible, and conformable characteristics of the fabric, thereby greatly improving the wearing comfort, enhancing the wearer's compliance, and making long-term wearing measurement possible. Thus, the problems that the current human pressure signal, temperature signal, electromyogram signal, and skin resistance signal cannot be monitored at the same position and the device has a large stiffness, resulting in poor wearing comfort and being not suitable for long-term monitoring are solved.

[0027] The additional aspects and advantages of the present application will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present application. Description of the Drawings

[0028] The above-mentioned and / or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0029] Figure 1 It is a flowchart of a muscle state evaluation method based on a multi-physiological signal all-fabric sensor device according to an embodiment of the present application;

[0030] Figure 2Schematic diagram of a patterned electrode arrangement structure provided by an embodiment of the present application;

[0031] Figure 3 Schematic diagram of an upper and lower electrode structure arrangement structure provided by an embodiment of the present application;

[0032] Figure 4 Schematic diagram of time-division multiplexing of myoelectric signal and impedance signal transmission provided by an embodiment of the present application;

[0033] Figure 5 Flow chart of multi-physiological signal parameter sensing and acquisition transmission provided by an embodiment of the present application;

[0034] Figure 6 Schematic diagram of a dual-temperature electrode provided by an embodiment of the present application;

[0035] Figure 7 Schematic diagram of a single-temperature electrode provided by an embodiment of the present application;

[0036] Figure 8 Schematic diagram of a temperature and pressure shared electrode provided by an embodiment of the present application;

[0037] Figure 9 Block diagram of data processing and data display provided by an embodiment of the present application;

[0038] Figure 10 Schematic diagram of the relationship between physiological signals and muscle physiological states provided by an embodiment of the present application;

[0039] Figure 11 Example diagram of a muscle state evaluation device based on a multi-physiological signal all-fabric sensor device according to an embodiment of the present application;

[0040] Figure 12 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application.

[0041] Among them, 10 - muscle state evaluation device based on multi-physiological signal all-fabric sensor device; 100 - acquisition module, 200 - signal processing module, 300 - evaluation module; 1201 - memory, 1202 - processor, 1203 - communication interface. Detailed implementation manners

[0042] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions from beginning to end. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application.

[0043] The muscle state assessment method based on a multi - physiological signal all - fabric sensor device according to an embodiment of the present application will be described below with reference to the accompanying drawings. In view of the problems in the prior art mentioned in the above - mentioned background art that it is impossible to measure four physiological signals at the same site, it is difficult to comprehensively evaluate the muscle state, and the device has a large stiffness, low flexibility, low wearing comfort, and is not suitable for long - term monitoring, the present application provides a muscle state assessment method based on a multi - physiological signal all - fabric sensor device. In this method, multiple physiological signals of a target user at the same site are collected by a preset time - division multiplexing strategy and a pre - constructed all - fabric sensor device. Among them, the multiple physiological signals include at least two of impedance signals, electromyography signals, pressure signals, and temperature signals; signal processing operations are performed on the multiple physiological signals to obtain a target transmission signal corresponding to each physiological signal in the multiple physiological signals, and the target transmission signal is transmitted to a preset terminal device; the preset terminal device performs data processing operations on the target transmission signal to obtain a data processing result corresponding to the multiple physiological signals, and determines the muscle physiological state information corresponding to each physiological signal according to the data processing result, so as to evaluate the muscle state of the target user through the muscle physiological state information. Through the all - fabric sensor device, the present application can measure human pressure signals, temperature signals, electromyography signals, and skin impedance signals at the same site, achieve a more comprehensive evaluation of the muscle state, and at the same time, the device has the breathable, flexible, and conformable characteristics of fabric, thus greatly improving the wearing comfort, enhancing the wearer's compliance, and making long - term wearing measurement possible. Thereby, the problems that the current human pressure signal, temperature signal, electromyography signal, and skin resistance signal cannot be monitored at the same site, and the device has a large stiffness, resulting in poor wearing comfort and not being suitable for long - term monitoring are solved.

[0044] Specifically, Figure 1 is a flowchart of a muscle state assessment method based on a multi - physiological signal all - fabric sensor device provided by an embodiment of the present application.

[0045] As Figure 1 shown, the muscle state assessment method based on a multi - physiological signal all - fabric sensor device includes the following steps:

[0046] In step S101, multiple physiological signals of a target user at the same site are collected by a preset time - division multiplexing strategy and a pre - constructed all - fabric sensor device. Among them, the multiple physiological signals include at least two of impedance signals, electromyography signals, pressure signals, and temperature signals.

[0047] Those skilled in the art should understand that the existing relevant signal sensors have a large stiffness, it is difficult to combine multiple flexible materials to achieve the collection of four physiological signals at the same site, and the flexibility of the device decreases after the integration of each component, and it is impossible to monitor pressure signals, temperature signals, electromyography signals, and impedance signals at the same site.

[0048] In the embodiments of the present application, a fully textile sensor device capable of monitoring human pressure signals, temperature signals, electromyogram signals, and skin impedance signals at the same site can be constructed first, so as to realize highly comfortable wearable measurement of multiple physiological signal parameters of the human body.

[0049] Optionally, in an embodiment of the present application, multiple physiological signals of a target user at the same site are collected by a preset time-division multiplexing strategy and a pre-constructed fully textile sensor device. Among them, the multiple physiological signals include at least two of impedance signals, electromyogram signals, pressure signals, and temperature signals, including: based on the electrical signal conduction layer, pressure and temperature sensitive layer in the fully textile sensor device, collecting the pressure signal and temperature signal of the target user at the same site; determining the application scenario requirements corresponding to the fully textile sensor device, and allocating corresponding acquisition time windows and transmission time windows for the impedance signal and electromyogram signal according to the application scenario requirements and the time-division multiplexing strategy; based on the electrical signal conduction layer, acquisition time window, and transmission time window, and in combination with the preset time sequence, sequentially collecting the impedance signal and electromyogram signal at the same site.

[0050] As a feasible implementation, the fully textile sensor device in the embodiments of the present application can adopt a three-layer structure, with the upper and lower layers being base layers printed with electrodes respectively. Among them, a pair of electrodes on the uppermost layer can be used for measuring electromyogram signals and impedance signals, and the middle layer and the lower layer electrodes (i.e., the pressure and temperature sensitive layer combined with the pressure and temperature signal conduction layer) are respectively used for measuring pressure signals and temperature signals, as Figure 2 shown; in addition, those skilled in the art can also construct a fully textile sensor device according to the shape of the customized electrode, or adopt an upper and lower electrode structure, as Figure 3 shown.

[0051] For the materials of the all-fabric sensor device, the all-fabric sensor device in the embodiments of the present application is divided into the materials of the pressure and temperature sensitive layer, the material of the base layer, and the material of the electrical signal conduction layer. Among them, the base layer can be obtained by electrospinning an insulating material with certain tensile properties, such as Thermoplastic Polyurethane Elastomer (TPU), Polyvinylidene Fluoride-Hexafluoropropylene (PVDF-HFP), etc.; different ionic gel systems can be selected for electrospinning the pressure and temperature sensitive layer materials, such as using poly(vinylidene fluoride-hexafluoropropylene) copolymer (P(VDF-HFP)) as the matrix, and its ionic component is 1-ethyl-3-methylimidazolium bis(fluorosulfonyl)imide ([EMIM][TFSI]), using polyvinyl alcohol (PVA) as the matrix, and the ionic component is 1-ethyl-3-methylimidazolium triflate ([EMIM][OTF]); the electrical signal layer material is a conductive material, such as conductive silver paste or aqueous graphene, etc.

[0052] In terms of the processing technology of the all-fabric sensor device, the embodiments of the present application can use the electrospinning process to electrospin a nanofiber membrane as the base layer, electrospin an ionic nanofiber membrane as the pressure and temperature sensitive layer, and use the screen printing process to print the electrical signal conduction layer.

[0053] It should be noted that the embodiments of the present application utilize three flexible material technologies of flexible conductive materials, flexible temperature and pressure sensitive materials, and flexible insulating materials, and design a three-layer structure to integrate them. Among them, the electrical signal conduction layer and the pressure and temperature signal conductive layer use flexible conductive materials; the pressure and temperature signal sensitive layer uses flexible pressure and temperature signal sensitive materials; the base layer uses flexible insulating materials; at the same time, the embodiments of the present application utilize the relatively mature electrospinning process to electrospin the main structural layers of the all-fabric sensor device, greatly improving the flexibility and wearing comfort of the device.

[0054] In the embodiments of the present application, the electrospinning process can be used to electrospin the base layer, temperature and pressure sensitive layers in the all-fabric sensor device. At the same time, stretchable conductive silver paste is used as the electrical signal conduction layer, and the three-layer structure of the sensor is encapsulated by hot pressing in one body to realize the co-site measurement of pressure, temperature, electromyogram and impedance signals. Since the three main structures are all fabrics and all components are flexible materials, the all-fabric sensor device in the embodiments of the present application has the advantages of high flexibility and high wearing comfort, and is suitable for long-term wearing physiological signal measurement.

[0055] In the actual implementation process, the embodiments of the present application can use the electrospinning process to convert each part of the sensor into a flexible fabric. The pressure signal and the temperature signal can be measured by the same ion nanofiber layer combined with the electrical signal conduction layer. Among them, the pressure signal measurement is related to the capacitance value of the ion fiber layer-electrode interface, and the temperature is related to the resistance value of the ion fiber layer. The electromyogram signal and the impedance signal can be measured by the same pair of electrodes, and finally the co-site measurement of four physiological signals is realized.

[0056] Figure 4 For the all-fabric sensor device of the embodiments of the present application, signal acquisition and transmission are realized by time division multiplexing when measuring electromyogram signals and impedance signals.

[0057] It should be noted that the acquisition and transmission of electromyogram signals and impedance signals in the embodiments of the present application can be realized by time division multiplexing (Time Division Multiplexing, TDM), as Figure 4 shown, and the acquisition and transmission time windows of the two signals are allocated according to the requirements of different application scenarios. The electromyogram signal and the impedance signal are allocated to two time periods in each TDM frame, so that the electromyogram signal and the impedance signal are sequentially and alternately acquired and transmitted in a predetermined time order.

[0058] In the specific implementation process, the acquisition of electromyogram signals and impedance signals in the embodiments of the present application can share a pair of electrodes. The electrodes are respectively connected to the electromyogram signal sensing module and the impedance signal sensing module through a time division multiplexing module, as Figure 5 shown; the time division multiplexing module polls and switches the channels of the two signal sensing modes in time order, including the electromyogram signal sensing channel and the impedance signal sensing channel.

[0059] In addition, those skilled in the art can combine the four physiological signals according to the actual situation, such as pressure signal and electromyogram signal, pressure signal and impedance signal, temperature signal and electromyogram signal, temperature signal and impedance signal, etc., so as to realize the co-site measurement of multiple physiological signals as required.

[0060] The structure of the all-fabric sensor device of the present application will be described below through a specific embodiment in conjunction with the drawings.

[0061] In a specific embodiment of the present application, the specific structure of the all-fabric sensor device for detecting pressure signals, temperature signals, electromyogram signals, and electrical impedance signals at the same site includes:

[0062] (1) Substrate layer

[0063] The substrate layer can be electrospun with an ultra-thin TPU film or PVDF-HFP film by electrospinning technology as the substrate layer, and at the same time as an insulating material to isolate the upper electrode and the ionic nanofiber membrane.

[0064] (2) Ionic fiber nano layer (pressure and temperature signal measurement layer)

[0065] The ionic fiber nano layer can be electrospun with an ionic nanofiber membrane obtained by electrospinning a PVDF-HFP mixed [EMIM][TFSI] solution or a PVA mixed [EMIM][OTF] system as the pressure and temperature sensitive layer; the pressure signal sensing is realized based on the electric double layer principle. An EDL capacitor is formed at the contact interface between the ionic nanofiber membrane and the lower electrode. When pressure is applied, the fibers inside the fiber membrane bend and deform, causing the duty cycle to change. The contact area between the electrode and the conductive ionic nanofiber membrane at the interface increases, and the EDL capacitor increases. The pressure signal to be measured is obtained by measuring the EDL capacitance value and back-calculating through the capacitance-pressure curve obtained by pre-calibration.

[0066] The temperature signal is measured based on the change in the resistance value of the ionic nanofiber membrane. When the temperature changes, the internal resistance of the fiber membrane changes, and the temperature of the part to be measured is obtained by back-calculating through the resistance-temperature curve obtained by pre-calibrating using the temperature gold standard method.

[0067] (3) Electrical signal conduction layer

[0068] Both the upper and lower electrical signal conduction layers are realized based on the screen printing conductive silver paste technology. As Figure 6 shown, the conductive silver paste selected is stretchable silver paste; among them, the lower electrode is patterned and is a comb-shaped counter electrode; when measuring the electromyogram signal, no current needs to be applied; while when measuring the electrical impedance signal, the circuit will apply alternating currents of different frequencies. At low frequencies, the resistance of the skin dominates, and at high frequencies, the capacitive effect of the skin becomes more significant.

[0069] Among them, the contact part between the temperature signal conduction electrode and the ionic nanofiber membrane and the corresponding part of the upper substrate layer are pre-pressed to fit tightly to ensure that the measured resistance value is not affected by external pressure changes and is only affected by temperature changes.

[0070] Except that the above temperature signal conduction electrodes are a pair of independent electrodes, single independent electrodes can also be used for temperature conduction, and the signal conduction of the other electrode can reuse the pressure signal conduction electrode, as Figure 7As shown. In addition, the temperature signal conduction electrode can also be fully multiplexed with the pressure signal conduction electrode, such as Figure 8 shown.

[0071] It can be understood that compared with existing physiological signal monitoring devices, the fully fabric-based device of the embodiments of the present application has the characteristics of flexibility, breathability, and high wearable comfort. It fits more closely to the human skin, can not only achieve single-point human wearable measurement, but also use the easy-to-cut feature of the fabric to make sensing arrays of different sizes for multi-point measurement. At the same time, the physical parameters to be measured can be custom-selected according to different physiological signal measurement requirements, so that the sensor size can be customized according to specific demand scenarios, signal interference is reduced, the comfort of wearable measurement is improved, and long-term monitoring of signals can be directly achieved by integrating into daily clothing.

[0072] Therefore, in the embodiments of the present application, by using flexible electronic material technology to convert all components of the fully fabric-based sensor device into fabric, the flexibility of the device is improved, which is conducive to the combination of different signal measurement components, thereby realizing the co-site measurement of four physiological signals, effectively solving the disadvantages of existing sensing technologies that use hard components for signal conduction and mostly collect single signals or dual signals.

[0073] In step S102, signal processing operations are performed on multiple physiological signals to obtain a target transmission signal corresponding to each physiological signal among the multiple physiological signals, and the target transmission signal is transmitted to a preset terminal device.

[0074] Furthermore, in the embodiments of the present application, signal processing operations can also be performed on multiple physiological signals such as impedance signals, electromyography signals, pressure signals, and temperature signals to obtain a target transmission signal corresponding to each physiological signal, and transmit it to a terminal device such as a preset PC, so as to collect and transmit pressure signals, temperature signals, electromyography signals, and impedance signals through a customized signal acquisition circuit.

[0075] Optionally, in an embodiment of the present application, performing signal processing operations on multiple physiological signals to obtain a target transmission signal corresponding to each physiological signal among the multiple physiological signals and transmitting the target transmission signal to a preset terminal device includes: performing signal amplification processing on the pressure signal and the temperature signal to obtain a pressure amplified signal and a temperature amplified signal; performing signal filtering and amplification processing on the impedance signal and the electromyography signal to obtain an impedance amplified signal and an electromyography amplified signal, and performing analog-to-digital conversion on the pressure amplified signal, the temperature amplified signal, the impedance amplified signal, and the electromyography amplified signal to obtain corresponding digital signals; performing signal compression processing on the digital signals to generate target transmission signals corresponding to the pressure signal, the temperature signal, the impedance signal, and the electromyography signal.

[0076] It should be noted that the embodiments of the present application can perform signal amplification processing on pressure signals and temperature signals, and perform signal filtering and amplification processing on impedance signals and electromyography signals to obtain corresponding amplified signals, and perform analog-to-digital conversion on the pressure amplified signal, temperature amplified signal, impedance amplified signal, and electromyography amplified signal through a preset analog-to-digital conversion module to obtain corresponding digital signals, such as Figure 5 shown; thereafter, the embodiments of the present application can use the central microcontroller module to receive and perform preliminary processing and compression on the digital signals to generate target transmission signals corresponding to the pressure signal, temperature signal, impedance signal, and electromyography signal, thereby providing reliable technical and data support for subsequent wireless transmission.

[0077] In step S103, a preset terminal device is used to perform data processing operations on the target transmission signals to obtain data processing results corresponding to multiple physiological signals, and determine the muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information.

[0078] Furthermore, the embodiments of the present application also need to transmit the target transmission signals corresponding to the pressure signal, temperature signal, impedance signal, and electromyography signal to a preset terminal device, such as the data processing module of a PC, through a Bluetooth wireless transmission module to perform data processing operations such as feature extraction on the above four physiological signals, evaluate the muscle physiological state information determined by the data processing results, and present the muscle state of the target user in the data display module, such as Figure 9 shown.

[0079] Thus, the embodiments of the present application can realize the measurement of four physiological signals of pressure, temperature, electromyography, and impedance at the same position, which is beneficial to a more comprehensive multi-angle and comprehensive evaluation of the physiological state of human muscles, including force, electricity, and blood supply conditions.

[0080] Optionally, in an embodiment of the present application, using a preset terminal device to perform data processing operations on the target transmission signals to obtain data processing results corresponding to multiple physiological signals, and determining the muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information, includes: performing data processing operations on the pressure signal, temperature signal, impedance signal, and electromyography signal to generate corresponding data processing results; determining the muscle physiological state information of the target user according to the data processing results, and transmitting the muscle physiological state information to the target display device to monitor and evaluate the muscle state of the target user, where the muscle physiological state information includes the mean value of the pressure signal, the mean value of the temperature signal, the mean value of the impedance signal, the time-domain characteristics and frequency characteristics of the electromyography signal within the target time period of muscle activity.

[0081] In the actual implementation process, after the data processing module of this application processes four physiological signals, it can not only present the real-time values of the four physiological signals, but also extract the corresponding muscle physiological state information. For example, the mean value of the pressure signal, the mean value of the temperature signal, the mean value of the impedance signal, the time-domain characteristics and frequency characteristics of the electromyogram signal (time-domain characteristics: amplitude; frequency characteristics: median frequency, weighted average frequency, etc.) within a specific period of muscle activity, and transmit the muscle physiological state information to the target display devices such as mobile phones / PC display terminals through Bluetooth, so that the wearer can master the real-time parameters of their own muscle state, and at the same time, doctors can also clinically evaluate the muscle state of patients undergoing exercise rehabilitation according to these parameters and optimize the rehabilitation training plan.

[0082] Among them, as Figure 10 shown, the relationships between the four physiological signals and the muscle physiological state in the embodiments of this application are as follows:

[0083] 1. Pressure signal:

[0084] It reflects the magnitude and change of muscle strength, and continuous monitoring can monitor the degree of muscle fatigue;

[0085] 2. Temperature signal:

[0086] It reflects the exercise intensity and the blood circulation of the muscle, etc.;

[0087] 3. Electromyogram signal:

[0088] (1) Time-domain characteristics: Amplitude - muscle activity intensity, Waveform Length WL - muscle activation duration;

[0089] (2) Frequency-domain characteristics: Median Frequency MDF of the power spectrum, Weighted Average Frequency MNF - reflecting the degree of muscle fatigue (fatigued muscles usually show a trend of decreasing frequency);

[0090] 4. Impedance signal:

[0091] It reflects muscle mass (muscles have high water content and relatively low impedance; adipose tissue has poor conductivity and high impedance), can reflect the change of blood circulation (insufficient local blood supply may lead to an increase in tissue impedance), and reflects the degree of muscle fatigue (muscle activity will cause changes in local temperature and blood flow, which can trigger changes in impedance).

[0092] It should be noted that, in the actual implementation process, for the assessment of muscle status, those skilled in the art can also collect PPG signals by using photoplethysmography according to the actual situation to view the congestion status of the muscle (transmission type / reflection type, reflecting the size of blood flow), or use the method of taking ultrasonic images to view the thickness of the muscle, the muscle fiber angle / length, and the myofascial curvature, or use myokinesis (MMG) to record the vibration signal transmitted from muscle contraction to the skin surface to reflect the muscle hardness / tension, so as to comprehensively and accurately evaluate the muscle status.

[0093] It can be understood that the multi-physiological signal all-fabric sensor device of the embodiment of the present application is not simply the superposition of four physiological signal measurement technologies, but based on flexible material technology, organically combines the four signal measurements at the same site, and can realize a more comprehensive monitoring and evaluation of the muscle physiological state (including size, bioelectrical signal, and blood supply).

[0094] According to the muscle status assessment method based on the multi-physiological signal all-fabric sensor device proposed in the embodiment of the present application, multiple physiological signals of the target user at the same site are collected by a preset time-division multiplexing strategy and a pre-constructed all-fabric sensor device, where the multiple physiological signals include at least two physiological signals of impedance signal, electromyogram signal, pressure signal, and temperature signal; perform signal processing operations on the multiple physiological signals to obtain a target transmission signal corresponding to each physiological signal in the multiple physiological signals, and transmit the target transmission signal to a preset terminal device; use the preset terminal device to perform data processing operations on the target transmission signal to obtain data processing results corresponding to the multiple physiological signals, and determine the muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle status of the target user through the muscle physiological state information. Through the all-fabric sensor device, the present application can measure the human body pressure signal, temperature signal, electromyogram signal, and skin impedance signal at the same site, realize a more comprehensive assessment of the muscle status, and at the same time, the device has the breathable, flexible, and conformable characteristics of the fabric, thus greatly improving the wearing comfort, enhancing the wearer's compliance, and making long-term wearing measurement possible.

[0095] Secondly, refer to the drawings to describe the muscle status assessment device based on the multi-physiological signal all-fabric sensor device proposed in the embodiment of the present application.

[0096] Figure 11 It is a block diagram of the muscle status assessment device based on the multi-physiological signal all-fabric sensor device of the embodiment of the present application.

[0097] As Figure 11 shown, the muscle status assessment device 10 based on the multi-physiological signal all-fabric sensor device includes: a collection module 100, a signal processing module 200, and an assessment module 300.

[0098] Among them, the acquisition module 100 is used to acquire multiple physiological signals of a target user at the same position by a preset time-division multiplexing strategy and a pre-constructed fully textile sensor device, where the multiple physiological signals include at least two physiological signals among impedance signals, electromyography signals, pressure signals, and temperature signals.

[0099] The signal processing module 200 is used to perform signal processing operations on the multiple physiological signals to obtain target transmission signals corresponding to each physiological signal among the multiple physiological signals, and transmit the target transmission signals to a preset terminal device.

[0100] The evaluation module 300 is used to perform data processing operations on the target transmission signals by using the preset terminal device to obtain data processing results corresponding to the multiple physiological signals, and determine muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information.

[0101] Optionally, in an embodiment of the present application, the acquisition module 100 includes: a first acquisition unit, an allocation unit, and a second acquisition unit.

[0102] Among them, the first acquisition unit is used to acquire the pressure signal and the temperature signal of the target user at the same position based on the electrical signal conduction layer, the pressure and temperature sensitive layer in the fully textile sensor device.

[0103] The allocation unit is used to determine the application scenario requirements corresponding to the fully textile sensor device, and allocate corresponding acquisition time windows and transmission time windows for the impedance signal and the electromyography signal according to the application scenario requirements and the time-division multiplexing strategy.

[0104] The second acquisition unit is used to sequentially acquire the impedance signal and the electromyography signal at the same position based on the electrical signal conduction layer, the acquisition time window, and the transmission time window, and in combination with a preset time sequence.

[0105] Optionally, in an embodiment of the present application, the signal processing module 200 includes: a signal amplification unit, an analog-to-digital conversion unit, and a signal compression unit.

[0106] Among them, the signal amplification unit is used to perform signal amplification processing on the pressure signal and the temperature signal to obtain a pressure amplified signal and a temperature amplified signal.

[0107] The analog-to-digital conversion unit is used to perform signal filtering and amplification processing on the impedance signal and the electromyography signal to obtain an impedance amplified signal and an electromyography amplified signal, and perform analog-to-digital conversion on the pressure amplified signal, the temperature amplified signal, the impedance amplified signal, and the electromyography amplified signal to obtain corresponding digital signals.

[0108] A signal compression unit for performing signal compression processing on digital signals to generate target transmission signals corresponding to pressure signals, temperature signals, impedance signals, and electromyogram signals.

[0109] Optionally, in an embodiment of the present application, the evaluation unit 300 includes: a data processing unit and a display unit.

[0110] The data processing unit is configured to perform data processing operations on the pressure signal, temperature signal, impedance signal, and electromyogram signal to generate corresponding data processing results.

[0111] The display unit is configured to determine the muscle physiological state information of the target user according to the data processing results and transmit the muscle physiological state information to the target display device to monitor and evaluate the muscle state of the target user, where the muscle physiological state information includes the mean value of the pressure signal, the mean value of the temperature signal, the mean value of the impedance signal, the time-domain characteristics, and the frequency characteristics of the electromyogram signal during the target time period of muscle activity.

[0112] It should be noted that the foregoing explanation of the embodiment of the muscle state evaluation method based on the multi-physiological signal all-fabric sensor device is also applicable to the muscle state evaluation device based on the multi-physiological signal all-fabric sensor device of this embodiment, and will not be elaborated here.

[0113] The muscle state evaluation device based on the multi-physiological signal all-fabric sensor device proposed according to the embodiment of the present application includes an acquisition module 100 for acquiring at least two physiological signals of a target user at the same site from a preset time-division multiplexing strategy and a pre-constructed all-fabric sensor device, where the at least two physiological signals include impedance signals, electromyogram signals, pressure signals, and temperature signals; a signal processing module 200 for performing signal processing operations on the multiple physiological signals to obtain target transmission signals corresponding to each physiological signal in the multiple physiological signals and transmitting the target transmission signals to a preset terminal device; an evaluation module 300 for performing data processing operations on the target transmission signals by using the preset terminal device to obtain data processing results corresponding to the multiple physiological signals and determining the muscle physiological state information corresponding to each physiological signal according to the data processing results to evaluate the muscle state of the target user through the muscle physiological state information. Through the all-fabric sensor device, the present application can measure the human pressure signal, temperature signal, electromyogram signal, and skin impedance signal at the same site, achieve a more comprehensive evaluation of the muscle state, and at the same time, the device has the characteristics of breathability, flexibility, and conformability of the fabric, thereby greatly improving the wearing comfort, enhancing the wearer's compliance, and making long-term wearing measurement possible.

[0114] Figure 12 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. The electronic device may include:

[0115] A memory 1201, a processor 1202, and a computer program stored on the memory 1201 and executable on the processor 1202.

[0116] When the processor 1202 executes the program, it implements the muscle state evaluation method based on the multi-physiological signal full-fabric sensor device provided in the above embodiments.

[0117] Furthermore, the electronic device further includes:

[0118] A communication interface 1203 for communication between the memory 1201 and the processor 1202.

[0119] The memory 1201 is used to store a computer program executable on the processor 1202.

[0120] The memory 1201 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0121] If the memory 1201, the processor 1202, and the communication interface 1203 are independently implemented, the communication interface 1203, the memory 1201, and the processor 1202 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 12 only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0122] Optionally, in a specific implementation, if the memory 1201, the processor 1202, and the communication interface 1203 are integrated on a chip, the memory 1201, the processor 1202, and the communication interface 1203 can communicate with each other through an internal interface.

[0123] The processor 1202 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0124] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the above-mentioned muscle state evaluation method based on a multi-physiological signal all-fabric sensor device.

[0125] An embodiment of the present application also provides a computer program product, including a computer program, and when the computer program is executed, it is used to implement the above-mentioned muscle state evaluation method based on a multi-physiological signal all-fabric sensor device.

[0126] In the description of this specification, the description with reference to terms such as "an embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0127] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically and clearly defined.

[0128] Any process or method description in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or N executable instructions for implementing a customized logical function or process, and the scope of the preferred embodiments of the present application includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in the reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the art of the embodiments of the present application.

[0129] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definable sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion (electronic device) having one or N wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0130] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), and the like.

[0131] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0132] In addition, each functional unit in various embodiments of the present application may be integrated into a processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0133] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A muscle state assessment method based on a multi-physiological signal full-fabric sensor device, characterized in that: The following steps are involved: A preset time-division multiplexing strategy and a pre-built fully fabricated sensor device are used to collect multiple physiological signals of the target user at the same location, wherein the multiple physiological signals include at least two physiological signals of an electrical impedance signal, an electromyographic signal, a pressure signal, and a temperature signal; Performing signal processing operations on the multiple physiological signals to obtain a target transmission signal corresponding to each of the multiple physiological signals, and transmitting the target transmission signal to a preset terminal device; The preset terminal device is used to perform data processing operations on the target transmission signal to obtain data processing results corresponding to the multiple physiological signals, and the muscle physiological state information corresponding to each physiological signal is determined according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information.

2. The method according to claim 1, characterized in that The preset time division multiplexing strategy and the pre-built fully fabricated sensor device collect multiple physiological signals of the target user at the same location, wherein the multiple physiological signals include at least two physiological signals of electrical impedance signals, electromyographic signals, pressure signals and temperature signals, including: Based on the electrical signal conducting layer and the pressure and temperature sensitive layer in the fully woven sensor device, collecting the pressure signal and the temperature signal of the target user at the same location; Determine the application scenario requirements corresponding to the fully woven sensor device, and allocate corresponding acquisition time windows and transmission time windows for the electrical impedance signal and the electromyographic signal according to the application scenario requirements and the time division multiplexing strategy; Based on the electrical signal conduction layer, the acquisition time window and the transmission time window, and in combination with a preset time sequence, the electrical impedance signal and the electromyographic signal of the same point are sequentially acquired.

3. The method according to claim 1, characterized in that The performing of signal processing operations on the multiple physiological signals to obtain a target transmission signal corresponding to each of the multiple physiological signals, and transmitting the target transmission signal to a preset terminal device, includes: Amplifying the pressure signal and the temperature signal to obtain an amplified pressure signal and an amplified temperature signal; Performing signal filtering and amplification processing on the electrical impedance signal and the electromyographic signal to obtain an electrical impedance amplified signal and an electromyographic amplified signal, and performing analog-to-digital conversion on the pressure amplified signal, the temperature amplified signal, the electrical impedance amplified signal and the electromyographic amplified signal to obtain corresponding digital signals; The digital signal is subjected to signal compression processing to generate target transmission signals corresponding to the pressure signal, the temperature signal, the electrical impedance signal and the electromyographic signal.

4. The method according to claim 1, characterized in that: The method of performing a data processing operation on the target transmission signal by using the preset terminal device to obtain data processing results corresponding to the multiple physiological signals, and determining muscle physiological state information corresponding to each physiological signal according to the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information, includes: Performing data processing operations on the pressure signal, the temperature signal, the electrical impedance signal, and the electromyographic signal to generate corresponding data processing results; The muscle physiological state information of the target user is determined according to the data processing result, and the muscle physiological state information is transmitted to the target display device to monitor and evaluate the muscle state of the target user, wherein the muscle physiological state information includes the pressure signal average, temperature signal average, electrical impedance signal average, electromyography signal time domain characteristics and frequency characteristics within the target time period of muscle activity.

5. A muscle state assessment device based on a multi-physiological signal all-fabric sensor device, characterized in that: include: A collection module, used for collecting multiple physiological signals of the target user at the same location by a preset time division multiplexing strategy and a pre-built fully fabricated sensor device, wherein the multiple physiological signals include at least two physiological signals of an electrical impedance signal, an electromyographic signal, a pressure signal and a temperature signal; A signal processing module, configured to perform signal processing operations on the multiple physiological signals to obtain a target transmission signal corresponding to each of the multiple physiological signals, and transmit the target transmission signal to a preset terminal device; An evaluation module is used to perform data processing operations on the target transmission signal using the preset terminal device to obtain data processing results corresponding to the multiple physiological signals, and determine the muscle physiological state information corresponding to each physiological signal based on the data processing results, so as to evaluate the muscle state of the target user through the muscle physiological state information.

6. The device according to claim 5, characterized in that The acquisition module comprises: A first acquisition unit is used to collect the pressure signal and the temperature signal of the target user at the same location based on the electrical signal conducting layer and the pressure and temperature sensitive layer in the fully-woven sensor device; An allocation unit, used for determining the application scenario requirements corresponding to the fully woven sensor device, and allocating corresponding acquisition time windows and transmission time windows for the electrical impedance signal and the electromyographic signal according to the application scenario requirements and the time division multiplexing strategy; The second acquisition unit is used to sequentially acquire the electrical impedance signal and the electromyographic signal of the same point based on the electrical signal conduction layer, the acquisition time window and the transmission time window and in combination with a preset time sequence.

7. The device according to claim 6, characterized in that The signal processing module comprises: A signal amplification unit, used for performing signal amplification processing on the pressure signal and the temperature signal to obtain a pressure amplification signal and a temperature amplification signal; an analog-to-digital conversion unit, configured to perform signal filtering and amplification processing on the electrical impedance signal and the electromyographic signal to obtain an electrical impedance amplified signal and an electromyographic amplified signal, and perform analog-to-digital conversion on the pressure amplified signal, the temperature amplified signal, the electrical impedance amplified signal, and the electromyographic amplified signal to obtain corresponding digital signals; A signal compression unit is used to perform signal compression processing on the digital signal to generate a target transmission signal corresponding to the pressure signal, the temperature signal, the electrical impedance signal and the electromyographic signal.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the muscle state assessment method based on a multi-physiological signal full-fabric sensor device as described in any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the muscle state assessment method based on a multi-physiological signal full-fabric sensor device as described in any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the muscle state assessment method based on a multi-physiological signal full-fabric sensor device as described in any one of claims 1 to 4.

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