141 results about "Triaxial accelerometer" patented technology

A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device. A learning module continuously improves system performance using reinforcement learning based on historical outcomes. The system supports predictive diagnostics, robotic repair, and automated optimization for long-term structural integrity.

The invention relates to the technical field of machining, and discloses a lathe tool wear self-inspection alarm system which comprises a multi-source sensing module, an intelligent analysis module, a dynamic response module, an interactive display module and a self-adaptive energy supply module. The multi-source sensing module synchronously acquires the surface abrasion loss, the vibration spectrum and the acoustic emission signal of the cutter through an optical sensor, a capacitive sensor and an MEMS triaxial accelerometer, and outputs the surface abrasion loss, the vibration spectrum and the acoustic emission signal to the intelligent analysis module; and the intelligent analysis module performs fusion analysis on the multi-source data by adopting a mixed feature extraction and double-model decision mechanism. High-precision monitoring and dynamic evaluation of lathe tool wear are realized through optical, vibration and acoustic emission sensors of the multi-source sensing module in combination with mixed feature extraction and a double-model decision mechanism of the intelligent analysis module. By means of the mode of combining multi-dimensional monitoring and intelligent analysis, machining defects and equipment failure risks caused by tool abrasion can be reduced.

The invention relates to the field of computer medical engineering, and discloses a blood pressure continuous measurement abnormity early warning method and system based on AI data analysis, and the method comprises the steps: collecting a pulse wave signal, triaxial accelerometer data, an ambient light intensity signal and a skin conductance signal through a sensor on a preset wearable device; generating multi-scale physiological features; systolic pressure and diastolic pressure are calculated, and blood vessel stiffness is calculated; calculating the main arteriosclerosis risk level; when the main arteriosclerosis risk level is higher than a preset risk level, a user is prompted through the wearable device. According to the invention, the pulse wave, the triaxial accelerometer, the ambient light intensity and the skin conductance signal are synchronously acquired and analyzed to obtain the systolic pressure, the diastolic pressure dynamic trend and the blood vessel stiffness, and the main arteriosclerosis risk level can be accurately quantified. In addition, a'physiological parameter-angiosclerosis-risk decision 'closed-loop management mechanism is established, and automatic and active health management of the user is realized.

The invention provides a weak current pipeline settlement monitoring system based on multi-source data fusion. The system comprises a ground sensor array which comprises a plurality of fiber bragg grating static level gauges, a strain sensing optical cable and a plurality of MEMS triaxial accelerometers and is used for collecting horizontal displacement, deformation stress and vertical settlement in sequence; the satellite remote sensing module comprises a synthetic aperture radar module and a GNSS module and is sequentially used for acquiring earth surface deformation data and elevation data of a monitoring area; and the data analysis platform is used for carrying out feature extraction on the data acquired by the ground sensor array, carrying out multi-source data fusion on the extracted features and the satellite remote sensing data acquired by the satellite remote sensing module by adopting a multi-source data fusion algorithm, and carrying out settlement monitoring and early warning based on a fusion result. According to the scheme, the problems that traditional single monitoring precision is insufficient and response lags are solved, the pipeline settlement early warning reliability can be remarkably improved, and the pipeline breakage risk is effectively prevented.

The MEMS triaxial accelerometer with the self-checking function comprises a cap layer, a structural layer and a substrate layer, the structural layer is clamped and packaged between the cap layer and the substrate layer, the structural layer comprises an X-axis acceleration detection array, a Z-axis acceleration detection array and a Y-axis acceleration detection array which have the self-checking function, and the X-axis acceleration detection array, the Z-axis acceleration detection array and the Y-axis acceleration detection array have the self-checking function. A Z-axis sensitive structure release groove is formed in the middle of the structural layer, the Z-axis acceleration detection array can move in the Z-axis direction along the Z-axis sensitive structure release groove, an X-axis sensitive structure release groove is formed in one side of the Z-axis acceleration detection array, and the X-axis acceleration detection array can move in the X-axis direction along the X-axis sensitive structure release groove. A Y-axis sensitive structure release groove is formed in the other side of the Z-axis acceleration detection array, and the Y-axis acceleration detection array can move in the Y-axis direction along the Y-axis sensitive structure release groove. The accelerometer provided by the invention has a self-checking function, can apply known signals, and is used for detecting the response of the sensor under different working conditions.

The invention discloses a ship ladder braking and lift car leveling safety state monitoring system based on digital twinning, which relates to the technical field of mechanical and electrical engineering, and comprises a system integrated leveling monitoring module, which adopts a salt mist resistant fiber grating displacement sensor and a magnetic railing ruler-Hall array closed loop verification mechanism and is combined with an anti-corrosion stay wire encoder; high-precision leveling detection is realized; the vibration signal separation module effectively recognizes braking abnormity through a triaxial accelerometer and a self-adaptive signal processing technology; a dynamic twin adaptive engine is fused with the ship ladder dynamic model and a transfer learning algorithm, and control parameters are adjusted in real time; and the cross check logic module automatically reconstructs data when the sensor is abnormal, so that the reliability and the fault-tolerant capability of the system are ensured. According to the invention, the berthing position error of the lift car is controlled within a safety range under different loads, speeds and sea conditions of the ship ladder, so that the riding comfort and safety are improved.

The invention relates to the technical field of strip mine side slope slippage trend early warning, and particularly discloses a strip mine side slope slippage trend early warning system based on active micro-vibration excitation, which comprises the following components: an excitation unit which is composed of a frequency-adjustable micro-vibration exciter which periodically applies low-amplitude controllable mechanical disturbance signals to a side slope rock mass, the rock-soil medium structure response is excited, and the early warning sensitivity is improved; the sensing unit comprises a three-axis acceleration sensor, a displacement meter, a GNSS (Global Navigation Satellite System) sensor and a ground acoustic wave sensor, and is used for recording response change in a vibration disturbance signal propagation process and obtaining data; the analysis unit comprises an edge intelligent terminal, a slippage trend identification model built in the edge intelligent terminal and a lightweight neural network, and the slippage trend identification model performs sensing processing on the data and outputs a slippage trend label; and the communication control unit is used for ensuring that the data streams of the units are stable and cooperatively run with the modules.

The invention discloses a spatial sound effect test method and system for a sound system. The method comprises the following steps: S1, synchronously acquiring multi-modal sensing data of a test environment in a preset stage; s2, generating a three-dimensional sound pressure distribution thermodynamic diagram, and constructing an initial sound field model based on the three-dimensional sound pressure distribution thermodynamic diagram; s3, generating a corrected sound field model, and synchronously recording vibration data acquired by the triaxial accelerometer; s4, generating a sound image positioning trajectory diagram, and calculating a deviation angle between an actual sound image position and a theoretical position; and S5, determining the sound effect quality score of each test stage. According to the method, a closed-loop test framework of physical environment perception, sound field real-time modeling, man-machine interaction analysis and fault linkage traceability is constructed, a full-process test solution covering a hardware state, acoustic characteristics and human factor perception is provided for an immersive audio system, and the spatial sound effect reliability of digital playing equipment is remarkably improved.

The invention provides an intelligent vehicle paint thickness detection system and method based on gyroscope positioning, and relates to the technical field of vehicle detection. The system comprises a sensor module for acquiring three-dimensional point cloud and temperature data of a vehicle; the data preprocessing module extracts surface geometry and temperature information; the three-dimensional construction module establishes a three-dimensional model with a coordinate system; the thickness measurement module calculates the paint thickness by combining geometric characteristics and temperature compensation; the data integration module generates a spatialized thickness data set; and the data management module stores the data and outputs a thermodynamic diagram. Accurate positioning of the scanner is achieved through the MEMS gyroscope and the triaxial accelerometer, the measurement accuracy is improved through temperature compensation and curvature correction algorithms, the problems that traditional detection is low in efficiency, poor in accuracy and non-uniform in standard are solved, and the method is suitable for second-hand car evaluation, production line quality inspection and other scenes.

The invention relates to the technical field of security and protection equipment, and discloses a portable multi-mode intelligent alarm terminal based on Beidou positioning, which comprises a Beidou third-generation positioning module, a multi-mode communication module, a dual-mode power supply system, a physical key assembly, a central processing unit and a sensor array, the Beidou third-generation positioning module supports BDS / GPS / GLONASS multimode fusion positioning, the positioning precision is less than or equal to 1m (in an outdoor enhancement mode), and the multimode communication module integrates 4G / 5G data communication, Beidou short message transmission and Bluetooth LE near field communication functions. According to the invention, through Beidou third-generation / GPS / GLONASS multimode fusion positioning, the Kalman filtering algorithm and the signal-to-noise ratio dynamic weighting technology are combined, and the outdoor positioning precision of less than or equal to 1m is realized. When a satellite signal is shielded, an inertial navigation mode is automatically switched to, a trajectory is corrected by utilizing data of a triaxial accelerometer, and an accumulative error is controlled within 5m / min. Through actual measurement, the positioning success rate in the urban canyon environment reaches 98% and is improved by 40% compared with that of a traditional single-mode GPS terminal, and it is ensured that rescue force quickly and accurately arrives at the site.

The invention relates to the technical field of navigation, and particularly discloses a GNSS / INS integrated navigation dynamic error correction method and system, and the method comprises the steps: S1, receiving GNSS original data, and calculating multipath interference intensity; s2, three-axis accelerometer data and yaw velocity information are received, and corrected displacement is calculated; s3, a fuzzy C-means clustering algorithm is adopted, and the motion state is obtained according to the corrected displacement; s4, generating a signal quality threshold value and a motion state threshold value according to the motion state; s5, constructing an error decoupling matrix according to the multipath interference intensity, the corrected displacement, the signal quality threshold value and the motion state threshold value; and S6, performing navigation calculation after error compensation by using the error decoupling matrix. According to the method, accurate compensation of dynamic errors is realized through accurate decoupling analysis of the motion characteristics of the carrier, so that the adaptability and reliability of the GNSS / INS integrated navigation system in a complex environment are improved.

The invention discloses an intelligent livestock and poultry ear tag device based on edge calculation and lightweight reasoning, and the device comprises a dynamic sampling module which collects the motion behavior data of livestock and poultry through a three-axis acceleration sensor based on a low-power-consumption sampling mechanism. The local processing module carries out local real-time processing on the collected data by adopting feature screening and a light-weight behavior recognition algorithm based on a TinyML model, and the low-power-consumption transmission module processes the collected data based on a bitmap compression coding form to carry out internal communication transmission, so that wireless data transmission is carried out by a low-power-consumption transmission mechanism based on AI edge calculation; according to the method, a low-power-consumption sampling mechanism and a lightweight algorithm based on a TinyML model are matched with feature screening, so that the power consumption and the calculation amount can be greatly reduced; an AI edge computing architecture is utilized, only key events and features are uploaded, the wireless transmission frequency is reduced, the communication power consumption is reduced, and local intelligent operation in a network disconnection scene is supported.

The invention provides a vehicle-mounted nine-axis gyroscope, which comprises a nine-axis sensor unit, a control chip, a communication module, a power supply management unit and an input / output unit, and the nine-axis sensor unit comprises a triaxial accelerometer used for measuring linear accelerations of an object in X, Y and Z axial directions, the instant speed and the relative displacement of the object are calculated by detecting the force borne by the sensor in the three axial directions; the three-axis gyroscope is used for measuring the angular velocity of the object around three axes, directly reflecting the rotating state and the angular acceleration of the object and acquiring the rotating information of the object in unit time; and the three-axis geomagnetic instrument is used for detecting magnetic field components of an earth magnetic field in X, Y and Z directions and calculating a plurality of geomagnetic angles of the magnetic field relative to the sensor through vector operation in a three-dimensional coordinate system. Through a multi-sensor fusion technology, the accurate course, speed, acceleration and attitude of the vehicle are tracked and calculated in real time, so that reliable navigation in various complex environments is guaranteed.

The invention provides a substation settlement monitoring method and system, and relates to the technical field of settlement monitoring, and the method comprises the steps: deploying a bionic root system mesh array sensor network which comprises a plurality of monitoring nodes; collecting current phase data of a transformer substation bus in real time to calculate magnetic field interference, and performing inverse compensation on an original displacement signal of the magnetostrictive displacement sensor; carrying out vibration monitoring through a triaxial accelerometer, and carrying out data weight adjustment on a plurality of monitoring nodes; and performing settlement prediction on the transformer substation according to the displacement compensation data in combination with the weight parameters of the plurality of nodes, performing backtracking calibration on the bionic root system mesh array sensor network, and performing closed-loop monitoring on the settlement of the transformer substation according to a calibration result. The technical problem of inaccurate settlement monitoring caused by interference in a high-intensity magnetic field environment of the transformer substation in the prior art is solved, and accurate prediction and closed-loop monitoring of settlement of the transformer substation are realized by deploying a plurality of intelligent sensors and performing magnetic field interference compensation.

The invention provides an automobile fault identification method and a detection system. The method comprises the following steps: acquiring running state data of the automobile seat through a multi-mode sensor network; wherein the multi-mode sensor network comprises a current sensor, a temperature sensor, a triaxial accelerometer and a displacement sensor, and the operation state data at least comprises a current signal, a vibration signal, a temperature signal and a displacement signal; generating a seat state mapping matrix based on the multi-modal data; inputting the seat state mapping matrix into a preset hybrid diagnosis model to execute fault recognition; and according to a fault identification result output by the hybrid diagnosis model, carrying out fault early warning and generating a fault risk quantification report. Through the method provided by the invention, the fault of the automobile seat can be effectively identified.

A system for monitoring medical conditions including pressure ulcers, pressure-induced ischemia and related medical conditions comprises at least one sensor adapted to detect one or more patient characteristic including at least position, orientation, temperature, acceleration, moisture, resistance, stress, heart rate, respiration rate, and blood oxygenation, a host for processing the data received from the sensors together with historical patient data to develop an assessment of patient condition and suggested course of treatment, including either suspending or adjusting turn schedule based on various types of patient movement. The sensor can include bi-axial or tri-axial accelerometers, as well as resistive, inductive, capacitive, magnetic and other sensing devices, depending on whether the sensor is located on the patient or the support surface, and for what purpose.

The invention relates to a method for correcting an output value of cold atom interference measurement equipment under a motion condition. The method comprises the following steps: acquiring attitude information of an inertial navigation system and acceleration information measured by a triaxial accelerometer; calculating # imgabs0 and # imgabs1 # on the basis of the attitude information and the acceleration information to represent a unit vector of a rotating shaft z axis of the cold atom interference measurement equipment in an initial state, omega represents a real-time rotating speed of the cold atom interference measurement equipment, delta v represents a speed difference between an atom and an accelerometer, and delta r'represents a position vector from the atom to the accelerometer; compensating the output value of the cold atom interference measurement equipment by using the values of a1 and a2; the environmental adaptability of the cold atom interference measurement equipment can be remarkably improved under the condition of no stable platform and no vibration isolation device, so that the cold atom interference measurement equipment outputs a correct measurement value in a complex rotation and vibration coexistence measurement environment.

The invention relates to a parameter self-adaptive dynamic tilt angle sensor measuring system, which is used for realizing accurate and reliable attitude detection under a long-time vibration working condition, and comprises a triaxial accelerometer used for detecting and outputting X-axis, Y-axis and Z-axis acceleration data; the gyroscope is used for detecting and outputting angular velocity data of X, Y and Z axes; and the attitude resolving module is used for performing EKF attitude fusion of parameter adaptive adjustment on the acceleration data and the angular velocity data to obtain attitude angle data. Compared with the prior art, the device has the advantages of being suitable for long-time vibration working conditions, reliable and accurate in detection, rapid in adjustment and the like.

The invention relates to the technical field of biological recognition, in particular to a multi-scene-oriented dynamic voiceprint recognition updating method, which comprises the following steps: synchronously acquiring voice signals through a 16-channel MEMS microphone array and a throat three-axis acceleration sensor, and constructing a three-dimensional data set containing acoustic scene fingerprints, semantic contexts and emotional characteristics; extracting features by adopting a scene adaptive dual-mode processing architecture, and extracting semantic features and emotional state coding vectors to form a multi-dimensional feature set; based on the multi-dimensional feature set, calculating a matching degree by using a Gaussian mixture model, monitoring a scene mutation index, and triggering an online clustering reconstruction mechanism to optimize a feature weight; deploying a three-level pipeline architecture for real-time processing; and generating a scene adaptation factor according to the MFCC-PLP mixed feature matrix and the environmental parameters to perform multi-feature joint matching. According to the invention, the adaptability of voiceprint recognition in a complex scene can be improved.

The invention discloses a track height unevenness detection system, a track height unevenness detection method and a track height unevenness measurement calibration method. Comprising a control system, a power supply module, a first three-axis accelerometer, a second three-axis accelerometer, a first pressure sensor, a second pressure sensor and a non-contact displacement detection device. A detection train comprises a train body, a bogie and wheels, and the wheels comprise the front wheel and the rear wheel. The vehicle body is connected with the bogie through a secondary suspension system, and the bogie is connected with the wheels through a primary suspension system; the triaxial accelerometer I and the pressure sensor I are respectively arranged at the top and the bottom of a spring of the front wheel primary suspension system; the triaxial accelerometer II and the pressure sensor II are respectively arranged at the top and the bottom of a spring of the rear wheel primary suspension system; the non-contact displacement detection device is arranged at the position of a center shaft of the bogie. According to the invention, more accurate detection of the irregularity of the track can be realized, and online metering calibration of an original track detection system can be realized.

The invention relates to a dual-mass-block three-axis acceleration sensor and a processing method thereof. The sensor comprises an X-axis and a Y-axis which are arranged on a first mass block, and a Z-axis which is independently arranged on a second mass block. The X-axis movable comb tooth structure and the Y-axis movable comb tooth structure are arranged outside the first mass block; the movable comb tooth structure of the Z axis is arranged in a central area between the first mass block and the second mass block, and an included angle of 135 degrees or 45 degrees is formed between the extension direction of the movable comb tooth structure of the Z axis and the extension directions of the movable comb tooth structures of the X axis and the Y axis; the first elastic supporting piece is connected to the first mass block and the substrate and used for sensing the X-axis acceleration and the Y-axis acceleration. The second elastic supporting piece is connected to the second mass block and the substrate and used for sensing the Z-axis acceleration. The fixed comb tooth structures of the X axis, the Y axis and the Z axis are fixed to the substrate through anchor points and arranged in a staggered mode with the movable comb tooth structures. The X-axis, the Y-axis and the Z-axis are arranged on different mass blocks, the comb tooth structure forms an included angle, the cross-axis sensitivity is reduced, and the size is reduced.

The invention provides a backpack multi-sensor data fusion-based motion attitude anomaly real-time detection method, which comprises the following steps of: acquiring multi-channel original data through a backpack-type integrated triaxial accelerometer, a gyroscope, a magnetometer and a barometer, implementing synchronous sampling and time-space alignment, and constructing a standardized time sequence data stream through wavelet denoising and multi-dimensional normalization preprocessing; high-dimensional features representing motion differences are extracted, nonlinear dimensionality reduction is achieved through principal component and Laplacian feature mapping, and a motion mode prototype library is generated; according to the method, a new motion situation can be continuously and adaptively learned, and the motion recognition accuracy, the system robustness and the attitude anomaly detection capability in a complex scene are effectively improved.

The invention discloses a uterine contraction detection method based on multi-modal signal fusion reconstruction, which comprises the following steps of: 1, synchronously acquiring an abdominal surface uterine electromyographic signal in real time through a high-density electrode array, acquiring a uterine contraction pressure signal in cooperation with a fundus pressure sensor, synchronizing a triaxial accelerometer signal to acquire a maternal motion signal, and preprocessing; 2, performing time sequence alignment and resampling on the data, and constructing a quality mask to form a multi-mode uterine contraction signal data set; 3, constructing a reconstruction network based on multi-modal feature fusion; 4, constructing a total loss function of the multi-modal feature fusion reconstruction network; and 5, training a reconstruction network of multi-modal feature fusion, wherein the reconstruction network is used for fusion reconstruction of the multi-modal uterine contraction data. According to the invention, through multi-modal signal fusion and deep feature correlation analysis, accurate monitoring and prediction of uterine contraction and premature delivery risks in the pregnant and birth period can be realized.

The invention discloses an urban and rural pavement maintenance monitoring system based on intelligent well lid data linkage, and the system comprises a data collection module which detects the acceleration data, angular motion data and inclination angle change data of a well lid in real time through a three-axis acceleration sensor, a gyroscope and an inclination angle sensor which are disposed on the well lid; the edge calculation module is used for calculating a vibration value of the well lid according to the acceleration data, the angular motion data and the inclination angle change data of the well lid and correcting the vibration value; the cloud data center obtains a risk index of a road surface where the well lid is located through a pre-constructed association model according to the corrected vibration value and the position of the well lid corresponding to the vibration value; and the maintenance decision terminal module performs maintenance decision on the road surface where the well lid is located according to the risk index of the road surface where the well lid is located. According to the invention, the well lid on the road surface is taken as the basis of data acquisition, and the maintenance condition of urban and rural road surfaces is detected in real time by acquiring the data on the well lid, so that the maintenance condition can be accurately obtained in real time.

Blood circulation assist systems include a ventricular assist device (VAD), a remote accelerometer, and a controller that controls operation of the VAD based on output of the remote accelerometer. A blood circulation assist system includes a VAD, a controller, and a remote accelerometer. The VAD includes an impeller. The remote accelerometer is configured to generate a remote accelerometer output indicative of accelerations measured by the remote accelerometer. The implanted controller controls a rotation speed of the impeller based on the remote accelerometer output.

An anti-kinetosis device for a motor vehicle includes a triaxial accelerometer, a display means, and a control unit. The triaxial accelerometer detects accelerations of the vehicle along three axes emits a corresponding acceleration signal. The display means includes light markers forming a first horizontal plane. The control unit includes an acceleration signal input, a processor, and a memory. The control unit receives the acceleration signals emitted by the accelerometer at the acceleration signal input. The memory stores instructions configured to cause the processor to align the first horizontal plane perpendicular to a gravitation vector by driving the means for displaying light markers and configured to cause the processor to align the first horizontal plane with a physical parameter of a first person seated in the motor vehicle. The first horizontal plane is positioned just beside the first internal surface and just in front of the second internal surface.

The invention provides an angle calculation method and system based on a triaxial accelerometer, and relates to the technical field of inertial navigation, and the method comprises the steps: obtaining an acceleration signal and preprocessing the acceleration signal to obtain an effective acceleration component, constructing a nonlinear error feature vector, carrying out the real-time parameter identification through a recursive least square method, and building a nonlinear error compensation model. And performing dynamic correction by adopting a self-adaptive sliding time window, and finally calculating a pitch angle and a roll angle. The non-linear error of the accelerometer can be effectively inhibited, the angle calculation precision is improved, and the method has the characteristics of good real-time performance and strong adaptability.

The present application provides a method and device for evaluating the stability of cover plate pressing, which relates to the technical field of cover plate pressing. The method includes: loading a calibrated test workpiece onto a target fixture and fixing it with a cover plate; controlling the machine tool to start and perform machining; reading monitoring data in real time and normalizing the contact two-dimensional standard force field into a time-series grayscale image; establishing a feature recognition result for the time-series grayscale image; synchronously obtaining the acquisition information of a triaxial accelerometer arranged on the fixture and using the micro-vibration signal as the first verification signal; monitoring the key points of the workpiece and using the time-series displacement of the workpiece as the second verification signal; performing stability verification on the feature recognition result and outputting a stability verification evaluation result. Through the present application, the technical objectives of multi-dimensional fusion modeling and stability intelligent evaluation based on the workpiece structure characteristics and the machining dynamic process can be achieved, and the technical effects of improving the recognition accuracy of pressing stability, reducing the misjudgment rate, and enhancing the adaptability of the system to complex machining environments can be achieved.

The invention relates to intelligent wearable bioelectronic equipment for monitoring and treating temporal muscle and masseter dysfunction and a control method, and belongs to the technical field of medical equipment. The device comprises a circuit board, a core processing unit MCU is arranged on the circuit board, the core processing unit MCU is respectively connected with an ACC triaxial accelerometer, a digital isolator and an NFC wireless communication and charging patch, the ACC triaxial accelerometer is connected with a surface myoelectricity electrode patch through an analog front end, the digital isolator is connected with a stimulation electrode patch through an electrical stimulation driving module, and the NFC wireless communication and charging patch is connected with an NFC wireless communication and charging module. And the NFC wireless communication and charging patch is connected with a reference electrode patch. According to the invention, efficient, safe and comfortable treatment of functional TMD is realized.

The invention discloses a step counting method and device of a hearing aid system, a hearing aid, a medium and a product, and relates to the technical field of hearing aids, the disclosed step counting method of the hearing aid system is applied to the hearing aid, the hearing aid comprises a gyroscope and a triaxial accelerometer, and the step counting method of the hearing aid system comprises the following steps: obtaining first data through the triaxial accelerometer, the first data is data collected by the triaxial accelerometer, and the second data is data collected by the gyroscope; taking data corresponding to the z axis in the first data as first target data; detecting a peak value in the first target data, and taking an acquisition moment corresponding to the peak value as a target moment; and taking data corresponding to the target moment in the second data as second target data, and calculating the step number according to the second target data. The technical scheme of the invention aims to solve the technical problem of how to improve the accuracy of the step counting function in the hearing aid.