283 results about "Electrode location" patented technology

The invention provides a lithium battery internal short circuit fault early warning and positioning method and system based on deep learning. The early warning and positioning method comprises the following steps: step S10, multi-dimensional data semantic acquisition and working condition self-adaptive preprocessing; step S20, collaborative extraction and alignment of cross-scale spatio-temporal features; step S30, performing dynamic threshold adaptive internal short circuit early warning and feedback optimization; s40, fault accurate positioning and verification of topology perception are carried out; and step S50, performing embedded collaborative optimization and self-diagnosis deployment. According to the invention, early weak signals of an internal short circuit fault can be found in time, and the efficiency and timeliness of battery safety monitoring are improved; the sensitivity of early warning is improved; the robustness in high-temperature, low-temperature and rapid charging and discharging environments is enhanced; and the positions of the single battery and the electrode with the fault can be accurately identified.

The invention discloses an underground anti-seepage structure leakage monitoring method and system based on discrete time, and relates to leakage detection. The method comprises the following steps: collecting transient electromagnetic response data generated by an excitation signal; according to the initial conductivity parameter and the electrode position parameter of the monitoring area, establishing a three-dimensional geophysical model of the monitoring area through a full waveform inversion algorithm; obtaining electromagnetic abnormal data by using a finite element forward modeling algorithm; according to the temperature data, a distributed temperature field analysis method is adopted to calculate the space gradient and the time change rate of the temperature, and temperature abnormal data are obtained; according to the pressure data and time sequence change characteristics of the pressure data, determining pressure abnormal data; fusing the electromagnetic abnormal data, the temperature abnormal data and the pressure abnormal data by using a Bayesian algorithm to obtain fused data; and inputting the fusion data into a pre-trained machine learning model to obtain a leakage detection result. Aiming at the low dynamic leakage monitoring precision of the underground anti-seepage structure, the dynamic monitoring precision is improved.

An apparatus and method for locating a position of an electrode on an organ model. The apparatus includes a memory communicatively connected to at least a processor, wherein the memory contains instructions configuring the at least a processor to receive an organ model configured to digitally represent an organ, receive a set of sensor data from at least a sensor including an ultrasound sensor, determine an electrode position within the organ model as a function of the set of sensor data using a position machine-learning module, wherein determining the electrode position includes determining a model position within the organ model as a function of the set of sensor data and determining the electrode position within the model position of the organ model as a function of the set of sensor data and add a visual marker onto the electrode position in the model position of the organ model.

The invention provides an emotion recognition method and system based on electroencephalogram signals, a storage medium and electronic equipment. The method comprises the following steps that the electroencephalogram signals and corresponding label information are obtained; the electroencephalogram signals are preprocessed based on the electrode positions of the electroencephalogram signals, and a three-dimensional brain feature map is obtained; forming an electroencephalogram signal data set based on the three-dimensional brain feature map and the label information; and training an emotion recognition depth model based on the electroencephalogram data set so as to realize emotion recognition based on the trained emotion recognition depth model. According to the emotion recognition method and system based on the electroencephalogram signals, the storage medium and the electronic equipment, accurate emotion recognition is achieved through the electroencephalogram signals on the basis of a mixed structure of the convolutional neural network and the Transform.

The invention relates to a P-type double-sided passivation selective contact TOPCon cell structure and a preparation method thereof, and belongs to the technical field of solar cells. According to the cell prepared by the invention, the short-circuit current and the photoelectric conversion photoelectric efficiency are improved, a polycrystalline silicon doping layer and a tunneling oxide layer in a non-metal contact region outside a front electrode position are removed through laser film opening, and a selective local contact structure is formed in a metal contact region at the electrode position; current parasitic absorption and contact recombination between metal and the surface of crystalline silicon are reduced; the PN junction is manufactured on the back face, front face light absorption is prevented from being affected, low-power laser is adopted to ensure that the back face PN junction is not damaged by the laser in a non-metal contact area outside the back face electrode position, and then back face current parasitic absorption is greatly reduced by etching and cleaning a back face tunneling oxide layer of the area.

The invention discloses a nerve regulation and control intervention system based on time domain interference electrical stimulation, and the system comprises a magnetic resonance image registration module which receives and registers an imported magnetic resonance image, and obtains a to-be-processed MRI image; the head model tissue segmentation module is used for performing head model tissue segmentation on the to-be-processed MRI image; the stimulation simulation module is used for performing stimulation simulation based on the tissue segmentation structure to obtain a front lead field matrix; the intervention coordinate selection module is used for determining a target brain region corresponding to a target spot brain region coordinate position needing stimulation intervention and putting the target brain region into a running sequence; the electrode position arrangement optimization module is used for verifying, optimizing and finely adjusting the electric field intensity of the target brain region under different electrode arrangement schemes to obtain an electrode configuration parameter result and displaying the electrode configuration parameter result; the parameter importing module is used for receiving the selected electrode configuration parameters and imported preset electrical stimulation parameters; and the electrical stimulation module is used for performing electrical stimulation on the target brain region of the target object. According to the application, the accuracy and the effectiveness of nerve regulation and control treatment can be realized.

The invention discloses a postoperative craniocerebral electrode trajectory determination method, device, system and equipment and a medium. The method comprises the following steps: acquiring a plurality of craniocerebral cross-sectional images of a target object after electrode implantation, and determining a plurality of target cross-sectional images containing electrodes from the plurality of craniocerebral cross-sectional images based on electrode implantation characteristics; and determining electrode positions in the plurality of target cross-sectional images according to electrode characteristics of electrodes in the target cross-sectional images. According to the electrode positions in the multiple target cross-sectional images and the position relation of the multiple target cross-sectional images, the electrode track in the brain of the target object is determined, postoperative medical images are automatically analyzed, manual intervention is not needed, the manual intervention cost is reduced, and meanwhile high robustness and reliability of determining the brain electrode track are guaranteed.

The invention discloses a decoupling vibration isolation composite beam frame structure shaped like a Chinese character'tian 'and a high-precision four-mass double-shaft micro-accelerometer thereof. The structure comprises at least four outer ring straight beam mechanisms and at least four decoupling vibration isolation rings. The accelerometer comprises a substrate layer and a device layer, and the device layer comprises the decoupling vibration isolation composite beam frame structure shaped like the Chinese character'tian ', an X-axis dual-mass sensing unit and a Y-axis dual-mass sensing unit. The problem of inter-axis cross coupling of double-axis acceleration detection is solved, isolation and vibration reduction of the MEMS accelerometer to the surrounding environment are achieved, and the influence of temperature and environment vibration on the measurement precision of a device is effectively restrained; by adopting a mode of crosswise arranging the electrode positions, the output error of the MEMS microstructure caused by process mismatch can be effectively inhibited, so that the output precision of the device is improved; each axial direction is designed in a combination mode that double mass sensing unit modules are connected in parallel, so that the detection sensitivity of the device is improved exponentially.

The invention discloses a brain-computer interface implantation accuracy judgment method based on combination of images and electroencephalogram signals, and belongs to the field of biological cross scientific research. By combining an image processing technology and fine electroencephalogram signal analysis, the accuracy of electrode implantation is evaluated from two independent and complementary angles. Compared with a traditional method depending on postoperative histological analysis, the method has the advantages that multiple real-time feedback mechanisms are provided, and the accuracy and reliability of electrode positioning in an operation are remarkably improved. The technical innovation not only shortens the operation time and reduces the operation risk, but also improves the success rate of the whole operation process. Through real-time image and signal analysis, an operation team can adjust an operation strategy in real time, an electrode implantation path is optimized, and it is ensured that an electrode accurately reaches a target brain area. Besides, the delay and uncertainty of relying on postoperative slice analysis are avoided, so that the correctness of the electrode position can be confirmed during the operation, and the overall safety and effect of the brain-computer interface operation are enhanced.

The invention discloses a high-precision detection method for a fault electrode of an electrolytic cell, and the method comprises the following steps: S1, carrying out the equipment layout, carrying out the infrared thermal imaging image collection, employing a high-resolution and large-field-angle lens collection device, improving the infrared image effect, improving the detection range, and installing uniformly-distributed current measurement devices, such as a Hall effect sensor, in the electrolytic cell; s2, image acquisition equipment is installed, the image acquisition equipment is installed through a visiting support and related assemblies, and meanwhile, the system adopts an automatic cruise and visiting mode to observe and troubleshoot field fault electrodes. According to the electrolytic cell fault electrode high-precision detection method and the positioning system, through infrared thermal imaging image acquisition, image splicing, deep learning algorithm convolutional neural network identification of a fault electrode plate and calling of a current matrix for analysis, through comparison of the two, a fault is determined through dual-mode fault detection; misjudgment is avoided; and the accuracy of fault pole plate positioning is improved.

The invention discloses a disturbance of consciousness electroencephalogram discrimination method and system adaptive to channel deletion. According to the method, on the basis of an electroencephalogram classification model of a deep network, automatic discrimination of disturbance of consciousness (MCS and UWS) is carried out with high accuracy according to resting-state electroencephalogram energy of a patient. The model utilizes a time domain double-branch CNN module and a space-time Transform module to learn features in electroencephalogram data hierarchically; and a model architecture with variable channel dimensions is introduced, an inter-channel association learning method fusing electrode position information and a training strategy of channel random discarding are introduced, so that the model can adapt to a scene in which part of channels are missing, and the clinical applicability of the method is improved.

The ablation system comprises ablation forceps, an ablation instrument and an operation part, the ablation forceps comprise a forceps holder assembly, an ablation assembly and an electrical connection assembly, and the forceps holder assembly comprises a far-end forceps holder and a near-end forceps holder which can be close to or away from each other; the ablation assembly comprises a far-end electrode set installed on the far-end forceps holder, a near-end electrode set installed on the near-end forceps holder and electrode marks arranged on the surface of the near-end forceps holder, the far-end electrode set and the near-end electrode set respectively comprise at least one electrode, and each electrode on the near-end forceps holder corresponds to one electrode mark. The ablation method comprises the steps that after target tissue is clamped by the forceps holder assembly, the positions of the electrodes corresponding to the electrodes are judged according to the electrode identifiers, the attaching states of the electrodes are judged according to local impedance data of the electrodes, and then the positions of the ablation forceps are adjusted or an ablation area is arranged. According to the invention, the safety and effectiveness of the operation are improved, the ablation effect is better, and the operation duration is shorter.

The invention discloses a motion posture recognition detection method based on transfer learning, belongs to the field of biomedical signal processing and machine learning, and aims at improving the robustness of a model under the condition of electrode position change by constructing an adversarial training mechanism and aligning data distribution before and after electrode offset in a feature space. The problem of data distortion caused by electrode displacement in the electrical impedance tomography EIT technology is solved, and the accuracy of posture recognition is improved.

The invention relates to the technical field of intelligent medical assistance, in particular to a skin disease treatment electrode positioning system based on potential distribution. The system comprises a potential gradient severe region identification module, a lesion minimum surrounding region identification module, a similar potential region grouping module, an optimal electrode position prediction module, an electric field distribution calculation module, a sweat gland dense region identification module, an optimal electrode placement point screening module, an enhanced feature generation module and a final electrode position determination module. By fusing multi-source information such as skin surface potential distribution, lesion geometric characteristics, tissue conductivity, historical treatment data and the like, systematic optimization is performed on electrode positioning in skin disease treatment, the effectiveness of electrode stimulation is maximized on the premise of ensuring the treatment safety, and the treatment efficiency is improved. An accurate electrode placement scheme is provided for treatment of different types of skin diseases, and the method is suitable for accurate determination of the electrode placement position in electrical stimulation treatment.

The invention discloses a refuse landfill geomembrane leakage detection method and system, and relates to the technical field of leakage detection.The method comprises the steps that a plurality of electrodes are arranged on the basis of the upper portion and the lower portion of a refuse landfill geomembrane, and a membrane upper electrode array and a membrane lower electrode array are constructed; constructing a detection electric field to obtain multiple groups of induction signal data; setting a reference signal, and identifying an abnormal sensing signal according to an analysis result; and mapping the abnormal sensing signal to the under-membrane electrode array according to abnormal data characteristics for positioning, determining electrode position information, and obtaining a leakage detection result. The technical problems that in the prior art, the positioning precision of the leakage point of the geomembrane of the refuse landfill is low, the leakage scale is difficult to evaluate, and the anti-seepage performance is not monitored in time are solved, and the technical effects that accurate positioning and scale evaluation of the leakage point of the geomembrane of the refuse landfill are achieved, and effective monitoring of the anti-seepage performance of the geomembrane is guaranteed are achieved.

The invention relates to an InP-based back incidence coplanar electrode position sensitive detector, which belongs to the technical field of photoelectric detectors, and is characterized in that an array is formed by a plurality of back incidence PSD units, the upper layers of the back incidence PSD units share a cathode, and an innovative structure capable of generating a better photoelectric effect is adopted; a common cathode layer, a P-type heavily doped layer for ohmic contact, a high-resistance silicon substrate layer and an InP dioxide substrate layer are sequentially arranged along the direction of incident light, a photosensitive area, a frame area and an isolation area are sequentially arranged on the lower portion of the high-resistance silicon substrate layer from inside to outside, and metal anodes are implanted in the positions of four end points of the InP dioxide substrate in contrast with the frame area. The structure greatly reduces the PSD array gap, eliminates the sampling blind area, has the advantages of simple signal processing, higher detection rate, high integration level, low cost, simple process and the like, and can be widely applied to the fields of wavefront detection, pose detection and the like to meet the various requirements of manufacturing super-large target surface, high-speed and high-density detectors and the like.

A transducer apparatus for delivering tumor treating fields to a subject's body, the transducer apparatus including: an array of electrodes, the array configured to be positioned over the subject's body with a front face of the array facing the subject's body, the array comprising electrode elements positioned in existing electrode positions arranged around a centroid of the array; an anisotropic material layer electrically coupled to the array of electrodes and located on a front side of the front face of the array; and at least one void space in the array of electrodes capable of enclosing an areal footprint equivalent to at least a portion of an areal footprint of at least one existing electrode position, and superimposable on at least a portion of at least one existing electrode position by rotation of the array around the centroid.

The invention provides a device and system implanted outside epidural under ultrasonic guidance for temporary electrode stimulation of spinal cord, and the device comprises a risk assessment module which carries out the comprehensive assessment of a patient through a multi-modal risk assessment model, and outputs a risk level or probability; the configuration selection module is used for analyzing the parameter information of the patient according to the parameter information of the patient when the evaluation result is passed, and setting guide configuration requirements; the probe guiding module guides the temporary electrode through an ultrasonic thermodynamic diagram; the effect test module is used for testing electrode functions by using a stimulator and adjusting electrode positions; the fixing and closing module fixes the electrode to avoid displacement; and the recording and monitoring module is used for recording electrode implantation depth, stimulation parameters and patient response. The system can reduce invasiveness and ultrasonic guidance accurate positioning, reduces errors and complications, is easy to popularize and apply, is relatively simple to operate, and is suitable for being popularized and applied in more medical places.

An elongate electrode is configured to flex and generate plasma to incise tissue. An electrical energy source operatively coupled to the electrode is configured to provide electrical energy to the electrode to generate the plasma. A tensioning element is operatively coupled to the elongate electrode. The tensioning element can be configured to provide tension to the elongate electrode to allow the elongate electrode to flex in response to the elongate electrode engaging the tissue and generating the plasma. The tensioning element operatively coupled to the flexible elongate electrode may allow for the use of a small diameter electrode, such as a 5 μm to 20 μm diameter electrode, which can allow narrow incisions to be formed with decreased tissue damage. In some embodiments, the tensioning of the electrode allows the electrode to more accurately incise tissue by decreasing variations in the position of the electrode along the incision path.

The invention provides an emotion recognition method, device and equipment based on electroencephalogram signals and a medium. The emotion recognition method based on the electroencephalogram signals comprises the steps that original electroencephalogram signals under all electrode positions are obtained; electroencephalogram characteristic data are extracted according to the original electroencephalogram signals; extracting frequency band and spatial features from the electroencephalogram feature data to obtain a space-frequency feature map; a bidirectional Mama network is adopted to extract time sequence characteristics of the space-frequency characteristic pattern in each time period, and a time sequence characteristic sequence is obtained; fusing each time sequence feature in the time sequence feature sequence on a time period dimension to obtain a fused time sequence feature; and recognizing the fusion time sequence features by using a feedforward neural network to obtain an emotion recognition result. According to the emotion recognition method and device based on the electroencephalogram signals, the equipment and the medium, deep feature fusion can be achieved, hidden features related to emotion changes in the electroencephalogram can be fully mined, and the accuracy of emotion recognition is improved.

The invention relates to the field of brain-computer interfaces, in particular to a motor imagery recognition method based on three-dimensional electroencephalogram signal representation and Mama, which comprises the following steps: collecting electroencephalogram data, storing the electroencephalogram data in a two-dimensional matrix form according to electrode positions, intercepting the electroencephalogram data according to a set time step length, and stacking the intercepted electroencephalogram data along a time dimension to form three-dimensional electroencephalogram data; in the first Mama module, processing each time slice of the three-dimensional electroencephalogram data in sequence, and stacking the three-dimensional electroencephalogram data along the time dimension at the outlet end to obtain first three-dimensional feature data; respectively segmenting the first three-dimensional feature data according to rows and columns in the form of a two-dimensional matrix, respectively inputting the first three-dimensional feature data into a second Mama module and a third Mama module, adding the output of the second Mama module and the output of the third Mama module to obtain a fused feature, and performing classification by using the feature; compared with the prior art, the method has the advantages that efficient and low-calculation-cost motor imagery classification of the EEG data is realized.

The invention belongs to the field of electrocardiosignal acquisition, and relates to an electrocardioelectrode position detection device and a detection method thereof. The device comprises a main control unit, an electrode detection unit, a signal detection processing unit and an output unit, the main control unit is respectively in circuit connection with the electrode detection unit, the signal detection processing unit and the output unit, and the main control unit is a control unit of the device. The electrode detection unit is used for detecting and judging the electrocardiosignal acquisition sensitivity of the device and detecting and judging the connection state of an electrode plate during electrocardiosignal acquisition; the signal detection processing unit is used for detecting and judging whether the connection position of the electrode slice is correct during electrocardiosignal acquisition; according to the electrocardio lead connection simulation training device, a trainee can carry out simulation training on various types of electrocardio lead connection situations, the operation skill of the trainee is improved, and errors in actual operation are avoided.

The ablation forceps comprise a forceps holder assembly, an ablation assembly and an electrical connection assembly, the forceps holder assembly comprises a far-end forceps holder and a near-end forceps holder, and the far-end forceps holder and the near-end forceps holder can be close to each other or away from each other. The ablation assembly comprises a far-end electrode set installed on the far-end forceps holder, a near-end electrode set installed on the near-end forceps holder and electrode marks arranged on the surface of the near-end forceps holder, the far-end electrode set and the near-end electrode set respectively comprise at least one electrode, and each electrode on the near-end forceps holder corresponds to one electrode mark. Electrode positions corresponding to the electrode marks are judged through the electrode marks, the electrodes on the forceps holder assembly are connected with the electrical connection assembly through wires, and the electrical connection assembly is connected with the ablation instrument. An operator can master the positions of the ablation electrodes during treatment, the positions of the ablation forceps are adjusted or ablation areas are arranged according to the positions and the attaching conditions of the electrodes, the safety and effectiveness of an operation are improved, the ablation effect is better, and the operation duration is shorter.

To provide a solder junction structure with an excellent joint quality, a touch sensor for a steering wheel, and a method for manufacturing a solder junction structure while suppressing or preventing damages of a net-like conductive material.SOLUTION: The solder junction structure is formed by joining a plate-like electrode and a net-like conductive material by a solder to form a laminate. The solder junction structure has a solder site having a solder joint layer formed by joining the plate-like electrode and the solder with each other in an electrode position which corresponds to a part of openings of the net-like conductive material, and also has an electrode exposure site in which the plate-like electrode is exposed in the electrode positions which correspond to the other openings.SELECTED DRAWING: Figure 2

The embodiment of the invention discloses an electrode direction recognition method, device and equipment, a medical system, a medium and a product, and the method comprises the steps: obtaining an original CT image and an X-ray plane image which comprise a target object; identifying electrode position information of a target electrode in the original CT image, and replacing a region at least comprising the target electrode in the original CT image with a corresponding electrode template according to the electrode position information to obtain a reference electrode template CT image; the target electrode is a directional electrode implanted in a target object; adjusting the electrode direction of an electrode template in the reference electrode template CT image, and obtaining CT image coronal projection images corresponding to the reference electrode template CT image in a plurality of electrode directions; and according to the similarity between the CT image coronal projection image and the X-ray plane image in each electrode direction, determining the electrode direction of the directional electrode implanted into the target object. According to the embodiment of the invention, the orientation of the implanted electrode can be automatically identified.

A transducer device for delivering a tumor treatment field to a subject's body, the transducer device comprising: an electrode array configured to be positioned over the subject's body with a front face of the array facing the subject's body, the array comprising electrode elements positioned in existing electrode locations arranged about a centroid of the array; a layer of anisotropic material electrically coupled to the electrode array and located on an anterior side of the front face of the array; and at least one void space in the electrode array capable of enclosing at least a portion of an area footprint equivalent to an area footprint of the at least one existing electrode location and capable of being superimposed on at least a portion of the at least one existing electrode location by rotating the array about the centroid.

The invention provides a hardware multi-point welding control method and device based on machine vision and a medium. The hardware multi-point welding control method comprises the steps that original welding images, with a welding time sequence, of multiple welding point positions of hardware are obtained, and the original welding images are locally and globally amplified under multiple different amplification factors; obtaining a local detail image and a global position image with welding time sequence marks; associating the local detail image with the global position image through a multi-scale feature fusion algorithm according to the welding time sequence mark to obtain molten pool morphological features and electrode position features; establishing a dynamic mapping relation between the molten pool morphological characteristics and the electrode position characteristics in a time sequence dimension to generate a welding state evaluation result; constructing a welding parameter adjustment decision tree according to a welding state evaluation result, and determining welding parameter adjustment requirements and adjustment directions of the welding point locations according to defect risk levels and characteristic deviation modes; and a current adjusting instruction is generated based on the welding parameter adjusting requirement and the adjusting direction, and welding adjusting operation is executed according to the current adjusting instruction.

1. A transducer device for delivering a tumor treatment field to a body of a subject, the transducer device comprising: an array of electrodes configured to be placed on a body of a subject with a front surface of the array facing the body of the subject, the array including electrode elements positioned at existing electrode locations positioned about a center of gravity of the array; an anisotropic material layer electrically coupled to the array of electrodes and positioned in front of the front surface of the array; and at least one void space within the array of electrodes capable of encompassing an areal footprint equal to at least a portion of the areal footprint of at least one existing electrode location and superimposable onto at least a portion of at least one existing electrode location by rotation of the array about the center of gravity.

The present application relates to a kind of silicon carbide power devices of floating junction thickness gradually changes, comprising: N+ silicon carbide substrate layer;N- silicon carbide epitaxial layer is located on N+ silicon carbide substrate layer;A layer P-type silicon carbide floating junction layer is arranged in the N- silicon carbide epitaxial layer in vertical direction, each P-type silicon carbide floating junction layer includes B P-type silicon carbide floating junction structure, P-type silicon carbide floating junction structure is symmetrical along central axis and is the structure of thickness gradually changes;Back electrode is located in the lower surface of N+ silicon carbide substrate layer;Front electrode is located on N- silicon carbide epitaxial layer.The present application makes the thickness of floating junction gradually increase from the center of floating junction to the edge of floating junction, thereby reducing the electric field peak value of corresponding electrode position higher at the center of floating junction when device is in reverse working state, while the epitaxial layer drift region between floating junction is more sufficient, makes the electric field peak value of floating junction interval center and edge position be lifted.

According to an aspect of the present inventive concept there is provided a system for determining an estimate of an anatomy of neural tissue of a subject. The system comprises an electrode arrangement comprising a plurality of electrodes, wherein different electrodes in the plurality of electrodes are configured to be arranged in different electrode locations adjacent the neural tissue, wherein the plurality of electrodes is configured to receive a plurality of stimulation signals, a sensor arrangement configured to generate indications of changes in at least one of a neural activity or a physiological activity in response to the stimulation signals and a processing unit, configured to receive data representing relations between the plurality of stimulation signals and the indications of changes in the neural activity or physiological activity, wherein the processing unit is configured to generate the estimate of the anatomy of the neural tissue of the subject.