35 results about "Signal interpretation" patented technology

The invention discloses a pelvic floor assessment method and system combining pelvic floor myoelectricity and muscle force signals, and relates to the technical field of pelvic floor muscle assessment, and the method comprises the steps: synchronously collecting pelvic floor myoelectricity signals and pressure signals, and recording data of a pre-resting stage, a rapid contraction stage, a tension contraction stage, an endurance contraction stage and a post-resting stage; the pelvic floor electromyographic signals and the pressure signals are preprocessed, and statistical characteristics are extracted based on the preprocessed signals; constructing a pelvic floor evaluation model, wherein the pelvic floor evaluation model comprises a logistic regression model, a long-short term memory network based on a cross attention mechanism and a multi-layer perceptron classifier; and training the pelvic floor evaluation model by using an Adam optimizer and a cross entropy loss function, and optimizing parameters of the pelvic floor evaluation model through evaluation indexes. According to the pelvic floor evaluation model, the timing sequence features and the statistical features are combined, more comprehensive signal interpretation is achieved, the generalization ability of the pelvic floor evaluation model is improved, and the pelvic floor health condition can be recognized more accurately.

The invention discloses an electrocardiosignal visualization enhancement method and system, electronic equipment and a medium. The method comprises the steps that first electrocardiosignals of multiple leads in a preset time period are obtained; extracting a frequency characteristic, a multi-lead consistency characteristic, a dynamic characteristic and an enhanced signal characteristic of the first electrocardiosignal of the plurality of leads; mapping the frequency feature into a first pseudo-color map, mapping the multi-lead consistency feature into a second pseudo-color map, and mapping the dynamic feature and the enhanced signal feature into a third pseudo-color map; and constructing a three-dimensional trajectory diagram according to the first pseudo-color diagram, the second pseudo-color diagram and the third pseudo-color diagram. According to the method and the device, the electrocardiogram signal interpretation precision and efficiency can be improved, so that the electrocardiogram signal visualization effect is improved.

The invention relates to the technical field of self-learning underwater acoustic communication, and provides an intelligent self-adaptive underwater acoustic communication system. The multi-system transmitter comprises a data transmitting unit used for transmitting communication data, a system switching unit used for switching a transmitting signal modulation mode, and a transmitting signal modulation unit used for modulating a signal. The intelligent multi-system receiver comprises a synchronization unit, a Doppler estimation and compensation unit, an intelligent modulation mode identification unit, a data processing unit, an intelligent signal interpretation unit and a digital demodulation unit. Wherein the channel information identification unit is used for identifying the signal-to-noise ratio and the channel maximum time delay of an underwater acoustic channel and transmitting the signal-to-noise ratio and the channel maximum time delay to the system switching unit, and the system switching unit adjusts and switches a transmitting signal modulation mode according to the signal-to-noise ratio and the channel maximum time delay. The intelligent modulation mode identification unit employs a lightweight neural network to intelligently identify a signal modulation mode of an underwater acoustic channel signal, and the intelligent signal interpretation unit employs a deep learning neural network to intelligently interpret an underwater acoustic communication signal so as to recover communication data.

The invention belongs to the technical field of medical instrument detection, and particularly relates to a method for rapidly detecting EO residual quantity in a sterilized medical instrument, which comprises the steps of sample acquisition, rapid extraction, specific color development or signal reaction, signal interpretation and content quantification, process parameter control and the like. And parameters of each link are optimized according to the characteristics of different types of sterilized medical instruments, and meanwhile, perfect quality control and calibration measures are set, so that the EO residual quantity is rapidly, accurately and simply detected, the accuracy and reliability of a detection result are effectively improved, and the method has a wide application prospect.

One variation of a method includes: accessing an audio feed captured by an audio sensor integrated within a training apparatus deployed in an environment and configured to dispense units of a treat into a working field in the environment; detecting a bark event at a first time based on audible signals extracted from the audio feed; in response to detecting the bark event, based on environmental signals extracted from the audio feed, interpreting a set of environmental data representing conditions of the environment at the first time; selecting an intervention action, in a set of intervention actions, configured to mitigate the bark event; triggering the training apparatus to dispense units of the treat according to the intervention action; predicting an environmental trigger for the dog based on the bark event and the set of environmental data; and storing the environmental trigger in a dog profile generated for the dog.

A smart monitoring system including a processor configured to receive activity signals from a plurality of sensor devices including at least one near-field sensor device configured to detect signals from one or more wireless transmitter devices coupled to an individual in a home or facility. The activity signals include detected signals from the one or more wireless transmitter devices indicating a location of the individual. Sensor data indicates usage of appliances and fixtures, including a button press and a press duration that is representative of urgency unique to the appliances and fixtures. The system is further configured to interpret the activity signals as daily activities performed by the individual, generate a quality of life score for the individual based on the interpreted activities, and process a clinical analysis of the individual based on the quality of life score.

This invention provides an automated evaluation system for vibration monitoring signals of aerospace products, comprising: a raw signal parsing module, a data preprocessing module, a signal parameter configuration module, a signal interpretation and evaluation module, and an evaluation conclusion output module. The raw signal parsing module parses unreadable raw data packets into a program-readable data format; the data preprocessing module eliminates signal start-time errors and performs filtering; the signal parameter configuration module configures parameters for single and related signals, forming a parameter configuration library; the signal interpretation and evaluation module evaluates the waveform similarity of single signals based on a cross-correlation normalization algorithm and interprets the time sequence relationship of related signals; the evaluation conclusion output module displays the evaluation results on a software interface. This invention achieves automated evaluation of vibration monitoring signals of aerospace products, replacing manual interpretation, improving evaluation efficiency and reliability, and possessing good versatility and scalability.

The embodiment of the invention discloses a laryngeal electromyographic signal interpretation method and system based on self-supervision joint coding prediction, a medium and equipment. The method comprises the steps that a laryngeal electromyographic signal data set and a corresponding instruction label are acquired; decomposing the signal into low-frequency and high-frequency components through wavelet transform; randomly generating a mask component for masking to obtain a visible group and a mask group; respectively extracting visible component features, target signal component features and mask vector features; performing joint coding on the mask vector feature and the visible component feature to obtain a target signal component prediction feature, and performing joint coding on the target signal component feature and the visible component feature to obtain a mask vector prediction feature; training a signal encoder based on the predicted and real features; combining the trained signal encoder with a classification module to construct an interpretation model and performing fine tuning training; the to-be-interpreted electromyographic signals are input into the fine-tuned signal interpretation model, a classification result is output, efficient feature learning is achieved through self-supervised joint coding prediction, and the generalization ability of the model is improved.

The invention discloses a control instruction generation method based on a multi-mode electroencephalogram signal, and relates to the technical field of man-machine interaction. According to the method, eight paths of electroencephalogram signal detection and three-axis gyroscope attitude detection are creatively fused, and the method is realized through multi-modal signal fusion and a unique algorithm, so that the problems of signal interpretation limitation, control instruction limitation, single information dimension and the like existing in pure electroencephalogram signal control and single sensor control in the prior art are solved. According to the method, the intention of the user can be more comprehensively and accurately interpreted, richer and more accurate control instructions can be generated, the control precision and flexibility are improved, the application scene is expanded, the user experience is improved, the system robustness is enhanced, and the method has important practical significance and application value and has remarkable progress compared with the prior art.

This application relates to the field of molecular pathology diagnostic technology, specifically disclosing a bone marrow smear FISH detection kit and its application. The kit includes a rapid hybridization buffer, a stabilization pretreatment solution, room temperature hybridization probes, probe dilution buffer, low-salt washing buffer, high-salt washing buffer, counterstaining solution, positive control samples, and negative control samples. The room temperature hybridization probes include broken probe pairs targeting the BCR-ABL, PML-RARA fusion genes, and IgH gene rearrangements. The detection method of this kit includes sample pretreatment, probe denaturation, room temperature hybridization, washing and counterstaining, and signal interpretation. Through the synergistic effect of the rapid hybridization buffer and the short-chain low-Tm value probes, rapid hybridization at room temperature is achieved, eliminating the need for a dedicated isothermal hybridization instrument. The stabilization pretreatment solution can complete cell permeation and RNA removal in one step, resulting in a high degree of operational standardization.

A test system includes a test container array including a plurality of test containers, and a plurality of electrodes integrated into the test container array. A test container contains a content. The test system further includes a plurality of drive-sense circuits coupled to the plurality of electrodes. When enabled, the set of drive-sense circuits transmit a set of electrode signals on the set of electrodes and generate a set of sensed signals. The test system further includes a processing module coupled to the plurality of drive-sense circuits that includes an analog reference signal generator operable to provide a set of analog reference signals to the set of drive-sense circuits, and a sensed signal processing unit operable to interpret the set of sensed signals as a set of impedance values. The set of impedance values are representative of electrical characteristics of the content.

The invention provides an electroencephalogram interpretation method based on Transformer of multi-granularity combination. The electroencephalogram interpretation method comprises the following steps: step 1, obtaining a differential entropy feature xe from an original electroencephalogram signal; step 2, using a spatial feature extraction Transform to obtain spatial features of the electroencephalogram region; 3, extracting time features of the electroencephalogram signals by using a shallow layer time feature extraction module; 4, extracting fine-grained time features by using a fine-grained convolution module; 5, optimizing the generated multi-level information by using self-attention (SA) and guidance attention (GA) to obtain an emotion label corresponding to the electroencephalogram activity; according to the method, the extraction of fine granularity and the utilization of the spatial features of the electrodes are remarkably improved, and by adding spatial feature extraction and time feature extraction operations, the algorithm efficiency is improved, the problems of insufficient utilization of the spatial features and the like are effectively solved, and the decoding accuracy is ensured.

A control device associated with an autonomous vehicle detects that a person is changing traffic on a road using a gesture signal. The control device determines an interpretation of the gesture signal. The control device transmits a gesture signal interpretation to a supervision server. The supervision server verifies the gesture signal interpretation and transmits instructions for navigating the autonomous vehicle in accordance with the verified gesture signal interpretation. The control device determines a suggested trajectory for the autonomous vehicle based on the interpretation of the gesture signal. The control device navigates the autonomous vehicle according to the suggested trajectory.

The invention belongs to the technical field of optical transmission, and particularly relates to a physical layer information hiding method based on time-frequency domain joint modulation. According to the invention, a ciphertext is modulated in a discrete multi-tone modulation mode and then is loaded on a pulse amplitude modulation signal, so that the signal shaped like pulse amplitude modulation is used for optical transmission; the method comprises the specific steps of signal modulation, signal transmission and signal interpretation. According to the method, amplitude information and frequency information are added during optical signal modulation, so that time-frequency domain joint modulation is realized; because the distribution of discrete multi-tone signals is Gaussian distribution, the observation receiving end constellation can only identify pulse amplitude modulation signals, and information hiding is realized. Meanwhile, the plaintext and the ciphertext are transmitted in a fusion manner, the signal-to-noise ratios between the two channels can be selected from each other, the application range is expanded, the method can be integrated into various existing communication systems and networks, and an optional scheme is provided for future network security and special application.

As a media program is aired to listeners, agents executed by a control system monitor actions by the creator or by listeners to ensure that the creator or the listeners comply with relevant policies and that the media program is aired as scheduled. The agents are programmed with sets of rules regarding content, language, advertising or other restrictions, and configured to process signals representative of actions taken by the creator or the listeners to determine whether such actions comply with such rules. The signals may represent spoken words, written messages, or interactions by listeners, among other actions. The agents interpret the signals to identify intended actions of creators or listeners, and to determine whether the intended actions would comply with each of the rules associated with the media program. The agents are also configured to identify and execute alternative actions as necessary.

The invention relates to a quantitative detection method for tiny difference of specific DNA sequence copy numbers and a primer group. The method comprises the following steps: 1) extracting sample DNA as a detection template; 2) preparing a digital PCR reaction premixed solution; (3) preparing micro-droplets; 4) performing PCR reaction; 5) detecting the amplification product by using a biochip analyzer, and judging the copy number of the target gene amplified by the primer composition; the method meets the requirement of six-color 10-order signal reading, hundreds of times of signal interpretation can be realized by improving amplification specificity, the quantitative detection requirement on tiny difference of specific DNA sequence copy numbers is met, the method is not influenced by complex components in a sample, and the accuracy of a detection result and the detection efficiency can be remarkably improved.

The invention relates to the technical field of industrial automation equipment detection and maintenance, in particular to a portable industrial equipment detection method and device with a charging function. The method comprises a power supply mode switching step, an equipment connection and configuration step, a signal processing and conversion step and a result presentation and diagnosis step. According to the invention, the method flow is standardized, dispersed operations depending on personal experience are integrated into a standardized flow covering power supply, wiring, testing and diagnosis, and the reliability and efficiency of detection are greatly improved. The method of switching power supply through a built-in battery thoroughly gets rid of the dependence on a field fixed power supply, and equipment detection at any place and under any working condition is realized. Complex signal interpretation and conversion work is automated, an engineering value is automatically displayed, a standard signal is output, the technical threshold is remarkably reduced, and man-made misjudgment is avoided.

The invention is applied to the technical field of geological exploration, and particularly discloses a geological radar collected signal collection and interpretation system, which comprises a computer, a power supply module, a storage module, a signal collection module and a signal interpretation module, and is characterized in that the computer is connected with the signal collection module and the signal interpretation module. According to the signal collection and interpretation system collected by the geological radar, the collected radar signals are transmitted to the signal interpretation module for interpretation of the radar signals, and before the radar signals are interpreted, a plurality of data preprocessing modules are arranged to carry out interpretation preprocessing on the radar data, including background noise removal and direct current offset removal. The method has the advantages that the radar signal quality is improved to the greatest extent by means of filtering processing and gain adjustment, the interpretation efficiency of the radar image can be improved, the interpreted radar image is classified and stored through the convolutional neural network, and subsequent interpretation of the radar image is assisted.

One variation of a method includes: accessing an audio feed captured by an audio sensor integrated within a training apparatus deployed in an environment and configured to dispense units of a treat into a working field in the environment; detecting a bark event at a first time based on audible signals extracted from the audio feed; in response to detecting the bark event, based on environmental signals extracted from the audio feed, interpreting a set of environmental data representing conditions of the environment at the first time; selecting an intervention action, in a set of intervention actions, configured to mitigate the bark event; triggering the training apparatus to dispense units of the treat according to the intervention action; predicting an environmental trigger for the dog based on the bark event and the set of environmental data; and storing the environmental trigger in a dog profile generated for the dog.

A timing controller suitable for providing image data and control signals to a display panel includes at least one dedicated controller configured to instruct the display panel to perform a specific operation; and a dedicated processor configured to store at least one communication-dedicated instruction, interpret, according to a communication signal designating an operation area of a communication-dedicated instruction received from an external or internal general processor, the communication-dedicated instruction within the operation area, sequentially transmit communication request signals to the corresponding dedicated controller, sequentially receive communication completion signals from the dedicated controller, and transmit an operation completion signal to the general processor when a communication completion signal for the communication-dedicated instruction of the operation area is finally received.

The invention discloses a strip mine wide-area deformation field monitoring method based on flexible photonic crystal coding, and belongs to the technical field of strip mine slope safety monitoring. A'sandwich 'heterostructure is adopted, the flexibility, environmental tolerance and long-term stability of the sensor are improved, the problems that a traditional optical fiber sensor is prone to damage and high in cost are solved, and the sensor is suitable for complex working conditions of strip mines. By adopting a roll-to-roll micro-nano imprinting large-scale production process, high-efficiency and low-cost batch production of the sensing belt is realized, which is far lower than that of a traditional fiber grating sensor, and the sensor has economical efficiency of large-scale application. A'spectrum-space 'dual coding mechanism is adopted, high-precision space positioning and temperature self-compensation are realized, measurement errors caused by temperature are reduced, and the anti-interference capability and data reliability of the system are improved. A multi-physics coupling deformation-optical interpretation model and an extended Kalman filtering processing flow are established by using a signal interpretation algorithm, and collaborative decoupling of multiple factors such as strain, temperature and stress is realized.

The invention discloses a weak laryngeal electromyographic signal interpretation method and device based on cascade wavelet decomposition. The weak laryngeal electromyographic signal interpretation method comprises the steps that a weak laryngeal electromyographic signal set and a real instruction set are obtained; constructing a cascade wavelet transform weak laryngeal electromyographic signal enhancement network and a view perception differential weak laryngeal electromyographic signal interpretation network; taking the electric signal set as a training set, taking the real instruction set as a label set, training a cascade wavelet transform weak laryngeal electromyographic signal enhancement network and a view perception difference weak laryngeal electromyographic signal interpretation network, and taking the two trained networks as a cascade wavelet decomposition-based weak laryngeal electromyographic signal interpretation model; a weak laryngeal electromyographic signal T to be interpreted is obtained; and inputting the weak laryngeal electromyographic signal into a weak laryngeal electromyographic signal interpretation model based on cascade wavelet decomposition to obtain an interpretation result. According to the method, the problems of poor feature extraction capability and insufficient decoding precision of weak laryngeal electromyographic signals in the prior art can be solved.

The invention provides a multi-signal interpretation and detection assembly combined system control method, which comprises the following steps: S1, power-on self-test: firstly, carrying out self-test initialization, and then carrying out self-test on the validity of input and output signals and a short-distance detection instruction; s2, binding in corresponding modes: carrying out mode binding through serial port communication, wherein selectable binding modes comprise a close-range response mode, a trigger response mode and a non-mode; s3, instruction identification; and S4, signal identification. According to the invention, by optimizing the power-on mode of the detection assembly and the interpretation mode of the short-distance detection instruction, the problem that the system outputs energy in advance due to the influence of false alarm, fault or electromagnetic interference during short-distance detection in the prior art is solved; and the system control with high reliability, self-adaptability and safety is realized.

The invention discloses a preparation method of a diagnostic fluorescent probe adaptive to multiple detection. According to the method, a nano-carrier with a reactive functional group on the surface is used as a framework material, Alexa Fluor 488 and Alexa Fluor 568 are covalently constructed on the same nano-carrier to form a double-fluorescence ratio type coding structure, and biological recognition molecules are coupled in a modular manner, so that the diagnosis fluorescent probe capable of outputting a fluorescence intensity ratio signal is obtained. A ratio type signal interpretation mechanism is adopted, so that the influence of probe dosage fluctuation, exciting light drift and sample matrix difference on a detection result is effectively reduced; through stabilizing treatment such as surface passivation, colloid stabilization and biological activity protection, the dispersity and signal consistency of the fluorescent probe in the storage and use process are improved. The prepared fluorescent probe has good stability, universality and anti-interference capability, and is suitable for various in-vitro diagnosis application scenes such as immunoassay, flow cytometry and multi-channel imaging.

The application relates to the technical field of intelligent detection, and specifically discloses a multi-attribute unsupervised clustering mud film identification method based on ground penetrating radar real-time monitoring, which is based on real-time monitoring ground penetrating radar data and pressure data, first builds a unified time reference for the test process with the aid of time markers, then limits the real horizon range through key stratification interface anchor points and phase axis tracking, extracts signal characteristic attributes and dielectric constant parameters and constructs a multi-attribute characteristic space on this basis, then combines the interface anchor points to perform unsupervised clustering division of the characteristic data with space constraints, finally identifies the interface evolution track, the mud film state and the time node according to the clustering result, and jointly verifies the pressure mutation inflection point, so that the mud film identification is changed from a single signal interpretation depending on artificial experience into an automatic identification process facing multi-source data and taking into account the time sequence constraints and physical meanings, and the stable and accurate identification of the mud film stratification structure and state evolution is realized.

The invention discloses a flexible strain sensor based on embedded 3D printing and a preparation method thereof, and belongs to the field of flexible electronic manufacturing. The method comprises the following steps: firstly, preparing a support matrix with a specific rheological gradient and oily conductive slurry; then integrally forming a two-dimensional or three-dimensional sensing structure, especially a three-dimensional non-communication structure capable of realizing multi-directional force decoupling, in the matrix through an embedded 3D printing process; and finally, performing intelligent processing and identification on the multi-channel resistance signal output by the sensor in combination with machine learning. According to the method, the problems of structure collapse, interface instability and complex signal interpretation in soft material printing are effectively solved, and the manufactured sensor has high precision, high stability and intelligent sensing capacity and can be widely applied to the fields of man-machine interaction, health monitoring, soft robots and the like.

An apparatus (100) includes a high voltage amplifier (120) to amplify a burst signal (115), and is coupled to a driver circuit (128) to drive a piezoelectric actuator (150). During the on-time of the burst signal, a feedback circuit (190) may compensate for non-idealities in the system and may equalize the signal at the actuator and the output of the high voltage amplifier. During the turn-off time of the burst signal, a signal conditioning circuit (160) may sense a difference signal between the signal at the actuator and the signal at the output of the high voltage amplifier, and interpret the difference signal as a pressure applied to the piezoelectric actuator.

A method includes selecting, by a processing module, a drive-sense circuit to be a transmit drive-sense circuit at different times. At each time of the different times, the method further includes providing, by the processing module, a reference signal having a first frequency to the selected transmit drive-sense circuit, transmitting, by the selected transmit drive-sense circuit, an electrode signal to a corresponding selected test container electrode of a test container of a test container array of a test system and generating, by other drive-sense circuits, a set of sensed signals. The test container contains a content. The method further includes interpreting a plurality of sets of sensed signals as a plurality of impedance values and generating an impedance map based on the plurality of impedance values and with respect to positioning of the set of test container electrodes. The impedance map is representative of electrical characteristics of the content.

The invention discloses an intelligent inspection system for equipment in a hospital supply room, relates to the technical field of safety detection of medical equipment in the hospital supply room, and aims to solve the technical problems of insufficient result accuracy, difficulty in pollution tracing and conflict between equipment calibration and emergency treatment detection requirements in endoscopic pathogen detection in the current hospital supply room. The multi-pathogen parallel detection module is used for carrying out multi-pathogen parallel detection on endoscope surface eluent; the material adaptation analysis module is used for acquiring endoscope material information and judging the suitability of the detection reagent and the endoscope material; the AI interpretation module is used for receiving the detection signal and the adaptive result, carrying out detection signal interpretation and pathogen concentration prediction and generating a detection report; and the data linkage module is used for binding full-process data of the endoscope. The method has the advantages that the detection result is accurate and reliable, the pollution source can be positioned, the process can be optimized, and the requirements of equipment calibration and emergency treatment detection can be balanced to guarantee the clinical efficiency.

The invention belongs to the technical field of molecular biology in-situ detection, and particularly relates to a protein and RNA multiple in-situ detection method based on a nucleic acid coupling antibody and in-situ hybridization. According to the method, firstly, an antibody coupled with a specific nucleic acid tag is combined with a target protein, then the nucleic acid tag carried by the antibody is detected through a fluorescence in-situ hybridization technology, and in-situ detection of nucleic acid molecules is synchronously achieved; in the aspect of signal interpretation, a unique signal coding and interpretation mode is used, and high-throughput space co-detection of protein and nucleic acid on a single sample is realized. The method effectively breaks through the limitation of secondary antibody species sources in traditional immunodetection, overcomes the technical bottleneck that multiple in-situ analysis of protein and nucleic acid is difficult to perform in the same sample, and can synchronously obtain spatial distribution and expression information of target protein and nucleic acid in a single sample. The invention provides a powerful technical tool for life science research, disease pathological diagnosis, drug screening and treatment guidance.