43 results about "Nystagmus" patented technology

Approaches presented herein provide for the automated determination of a level of impairment of a person, as may be relevant to the performance of a task. A light and camera-based system can be used to determine factors such as gaze nystagmus that are indicative of inebriation or impairment. A test system can simulate motion of a light using a determined pattern, and capture image data of at least the eye region of a person attempting to follow the motion. The captured image data can be analyzed using a neural network to infer at least one behavior of the user, and the behavior determination(s) can be used to determine a capacity or level of impairment of a user. An appropriate action can be taken, such as to allow a person with full capacity to operate a vehicle or perform a task, or to block access to such operation or performance if the person is determined to be impaired beyond an allowable amount.

The invention discloses a portable eyeshade for positioning injured semicircular canals according to nystagmus, which relates to the field of clinical medicine and comprises an eyeshade body, a fixing plate and a high-speed camera. High-speed cameras are arranged on two sides in the eyeshade body, an infrared lighting module is arranged at one end of each high-speed camera, an inertial measurement unit is arranged in the eyeshade body on one side close to the two high-speed cameras, and a processor is arranged in the eyeshade body on the top of the inertial measurement unit; a fixing plate is movably installed at one end of the eyeshade body, connecting buckles are fixedly connected to the two sides of the eyeshade body, and a head band is movably installed on the outer sides of the connecting buckles. The high-speed camera, the infrared lighting module, the inertial measurement unit and the processor are integrated on the light-weight eyeshade body, the head band connected with the connecting buckle is matched to achieve wearable performance, large equipment is not needed, the nystagmus detection convenience and timeliness are improved, the head band is adjusted in an adaptive mode, the wearing oppression feeling of a patient can be reduced, and the examination experience is improved.

The invention discloses a vestibular function detection system, a data processing method, electronic equipment and a program product. The method comprises the following steps: acquiring an eye movement video of a subject in vestibular function detection; extracting an eye movement track of the subject from the eye movement video; the eye movement track comprises one or more of a horizontal direction eye movement track, a vertical direction eye movement track and a twisting direction eye movement track; acquiring auxiliary detection data of the subject; the auxiliary detection data comprises body position data of the subject in vestibular function detection and / or nystagmus characteristic parameters obtained from eye movement tracks; inputting the eye movement track and the auxiliary detection data into a trained neural network model, and identifying and outputting vestibular function data of the subject through the neural network model; wherein the eye movement track is associated with the auxiliary detection data through time synchronization. Compared with only considering eye movement video or eye movement track data, body position data or nystagmus characteristic parameters, the scheme of the application enables the evaluated vestibular function data to be more accurate.

The invention discloses a virtual reality dynamic field angle adjusting system and method, and relates to the technical field of virtual reality, and the system comprises a multi-source signal collection module which is used for collecting eye movement tracking data and head movement data of a user in a virtual reality environment in real time, and the head movement data comprises head angular velocity and angular acceleration information; the nystagmus signal extraction module is connected with the multi-source signal acquisition module; the vestibular mismatch index calculation engine is connected with the nystagmus signal extraction module and is used for calculating the nystagmus strength index; the self-adaptive field angle controller is connected with the vestibular mismatch index calculation engine; and the rendering pipeline adaptation module is connected with the adaptive field angle controller. By mining neglected nystagmus physiological signals in eye movement tracking data and combining multi-dimensional information fusion and personalized parameter adaptation, dynamic adjustment of a field angle is realized, and the problem of dizziness and individual difference adaptation caused by a fixed field angle in an existing virtual reality system are solved.

The invention provides a calibration method, system and device for measuring the pupil rotation angle and direction and a medium, and relates to the technical field of medical device.The method comprises the steps that after a testee wears nystagmus detection equipment, a reference image containing a scale is shot, and a real-time image containing eyeballs of the testee and a main camera is shot; performing superposition processing on the reference image and the real-time image to generate an actual distance from the eyeball to the main camera; acquiring a preset distance between the main camera and the plurality of LED indicating lamps, and when the LED indicating lamps are lightened in sequence, acquiring an eye image sequence when eyeballs watch the LED indicating lamps; extracting a pixel coordinate position when an eyeball watches the target LED indicator lamp in the eye image sequence; combining a preset distance and the actual distance to calculate a rotation angle when eyeballs watch a target LED indicator lamp; and establishing a calibration coefficient of the pixel displacement and the rotation angle in combination with the pixel coordinate position and the rotation angle. The technical effect of the invention is that the measurement precision is improved.

The invention provides a portable video nystagmus detection eyepiece, and relates to the technical field of medical equipment. The endoscope comprises an endoscope body, an image acquisition assembly and an analysis assembly, the endoscope body comprises an endoscope frame and a head band, and the head band and the endoscope frame are connected into a ring; the image acquisition assembly comprises an eyeball camera and a calibration camera, the eyeball camera and the calibration camera are both arranged on the side, close to the head band, of the glasses frame, the eyeball camera can acquire a motion video of a to-be-detected eyeball, and the calibration camera can shoot a calibration image containing the eyeball camera and the to-be-detected eyeball; the analysis assembly comprises a control panel and a display electrically connected with the control panel, the control panel and the display are both arranged on the glasses frame, the control panel can receive a motion video and a calibration image, and the control panel can firstly analyze the calibration image to obtain the distance between the eyeball camera and the eyeball to be detected; and the motion video is analyzed in combination with the distance, and an analysis result is sent to a display. According to the invention, the actual distance between the eyeball and the camera can be accurately measured, and the precision is high.

A mobile-assisted diagnostic platform and method for vertigo, belonging to the interdisciplinary field of computer vision and assistive medical care, includes a data acquisition module, a data preprocessing module, a data processing module, and a data management module. The data acquisition module collects nystagmus videos via a mobile application. The data preprocessing module uses a binary classification neural network to remove interference frames and achieves coarse pupil localization through centroid calculation. The data processing module enhances spatiotemporal, channel, and motion features through a multi-path excitation module, combines a VST architecture to achieve nystagmus type recognition, and uses a dual-branch deep learning association model to correlate nystagmus type with vertigo classification. The data management module utilizes WeChat cloud services and a WeChat cloud database, supporting multi-terminal adaptation. This invention supports remote collaborative diagnosis and treatment between doctors and patients; it requires no dedicated medical equipment, is convenient while ensuring diagnostic accuracy, significantly reduces medical costs, and is suitable for home health monitoring, primary healthcare, and remote diagnosis and treatment scenarios.

The application provides a portable video nystagmus detection eyepiece, and relates to the technical field of medical equipment. The portable video nystagmus detection eyepiece comprises a mirror body, an image acquisition assembly and an analysis assembly. The mirror body comprises a mirror frame and a headband, and the headband is connected with the mirror frame to form a ring shape. The image acquisition assembly comprises an eyeball camera and a calibration camera, both of which are arranged on one side of the mirror frame close to the headband. The eyeball camera can acquire a motion video of a to-be-measured eyeball, and the calibration camera can shoot a calibration image containing the eyeball camera and the to-be-measured eyeball. The analysis assembly comprises a control board and a display electrically connected with the control board. The control board and the display are both arranged on the mirror frame. The control board can receive the motion video and the calibration image. The control board can first analyze the calibration image to obtain the distance between the eyeball camera and the to-be-measured eyeball, and then analyze the motion video combined with the distance and send the analysis result to the display. The application can accurately measure the actual distance between the eyeball and the camera, and has the effect of high precision.

The application provides a kind of scaling method, system, equipment and medium for measuring pupil rotation angle and direction, it is related to medical equipment technical field, method includes: when the person to be measured wears nystagmus detection equipment, the reference image containing scale is photographed, and the real-time image containing the eyeball of the person to be measured and main camera is photographed;The reference image is superimposed with real-time image, and the actual distance of eyeball to main camera is generated;The preset distance between main camera and multiple LED indicator lights is obtained, when each LED indicator light is lit in turn, the eye image sequence when eyeball gazes at each LED indicator light is collected;The pixel coordinate position when eyeball gazes at target LED indicator light in eye image sequence is extracted;The rotation angle when eyeball gazes at target LED indicator light is calculated in combination with the actual distance and the preset distance;The scaling coefficient of pixel displacement and rotation angle is established in combination with pixel coordinate position and rotation angle.The application has the technical effect of improving the measurement accuracy.

The invention provides an eyeball tremor identification method and system, and belongs to the technical field of medical auxiliary diagnosis, and the method comprises the steps: obtaining pupil data which comprises time sequence information and corresponding pupil position coordinate information; preprocessing the pupil data; segmenting the preprocessed pupil data to form a plurality of interval data segments; detecting a fast phase mode and a slow phase mode according to the speed characteristics of each interval data segment; when it is detected that the fast phase and slow phase alternating mode continuously appears for at least a preset number of times and the rhythm characteristic meets the rhythm requirement, it is judged that an eyeball tremor event occurs; wherein the rhythm characteristic is a speed variation coefficient. The method has the advantages that autonomous eye movement and pathological nystagmus can be accurately distinguished by combining phase features and rhythm analysis, the misjudgment rate is reduced, the method has the advantages of being high in recognition precision, high in anti-interference capacity and high in automation degree, an objective quantitative basis is provided for clinical diagnosis of nystagmus, and the method can be widely applied to clinical diagnosis of the ophthalmology department.

The invention relates to the technical field of disease diagnosis, and particularly discloses a diagnosis and treatment system for intelligent classified diagnosis of vertigo diseases based on deep learning, and the system comprises a nystagmus sample collection module which is used for obtaining training set data; the model training module is used for obtaining an eye seismic waveform range; the model diagnosis module is used for obtaining a dizziness diagnosis result of the patient; the diagnosis result confirmation module is used for evaluating whether the dizziness diagnosis result is accurate or not based on the dizziness diagnosis result of the single target person; misleading reason analysis: based on the inaccurate diagnosis signal, analyzing whether a single target person misleads the diagnosis model or not, and if misleading occurs, generating a type misleading signal; the model autonomous learning module is used for carrying out learning updating on a single target person in an eye seismic waveform range on the basis of the type misleading signal; according to the method, the diagnosis accuracy is remarkably improved, and the misdiagnosis or missed diagnosis phenomenon caused by individual differences is effectively reduced.

The invention discloses a drunkenness state detection method, system and device and a medium, and the method comprises the steps: obtaining the eye data of a driver in a preset time period, and enabling the eye data to comprise eyeball state data; performing time domain feature extraction on the eyeball state data to obtain time domain feature data; performing frequency domain feature extraction on the eyeball state data to obtain frequency domain feature data; fusing the time domain feature data and the frequency domain feature data to obtain eyeball tremor feature information; and based on the eyeball tremor characteristic data, utilizing a neural network model to detect the drunkenness state of the driver. Through fusion of frequency domain and time domain feature information, the eyeball tremor state of the driver is evaluated from multiple features, the robustness of data and the generalization ability of a model can be improved, and the drunk driving state detection precision is improved. And the judgment result can be fused with a drunkenness state detection result based on the physiological feature information of the driver and the vehicle state information, so that the accuracy of deducing the drunkenness state of the driver is further improved.

The invention relates to the technical field of nystagmus fast and slow phase detection, in particular to a nystagmus fast and slow phase recognition system based on eye movement signals and a phase recognition method thereof, and the phase recognition system comprises a data acquisition module, a signal processing module, a recognition module and an output module. The data acquisition module acquires an eyeball movement image sequence through an infrared camera; the signal processing module preprocesses each frame of image in the eyeball movement image sequence, including ROI drawing, image binaryzation, connected domain area calculation and eyeball positioning; the recognition module is used for extracting nystagmus features from the preprocessed eye movement signals and performing fast and slow phase recognition; and the output module is used for outputting identification and calculation results in a visual form. The system has the advantages that the system comprises the data acquisition module, the signal processing module, the identification module and the output module; therefore, automatic identification of the nystagmus fast and slow phase is realized, manual intervention is reduced, the diagnosis time is shortened, and the diagnosis efficiency is improved.

The invention relates to the technical field of medical image processing, in particular to a BPPV automatic auxiliary diagnosis method based on an eye movement video, and the method comprises an image collection module which is used for collecting the eye movement video of a patient; the iris segmentation and positioning module is used for extracting an iris region from the eye movement video and positioning the inner and outer contours of the iris region; the three-dimensional nystagmus detection module is used for generating eye movement data in horizontal, vertical and torsional dimensions based on the iris information; and the classification diagnosis module is used for classifying BPPV types according to the three-dimensional eye movement data. According to the invention, by adopting a multi-task end-to-end iris segmentation and positioning strategy, iris segmentation mask prediction and internal and external contour parameter extraction are integrated in the same network, so that deep collaboration and mutual promotion of two tasks are realized; according to the design, the process complexity and manual design errors caused by dependence on a large number of post-processing steps in a traditional method are avoided, and accurate segmentation results and positioning parameters can be directly output from the original eye movement video image.

The present invention relates to the field of medical devices, and in particular to an intelligent control system for electric stimulation of nystagmus, comprising: a data acquisition unit configured to collect nystagmus data and related data; a data analysis unit configured to determine a first electric stimulation parameter according to the nystagmus data; a parameter adjustment unit configured to determine an influencing factor of the first electric stimulation parameter according to a preset electric stimulation parameter adjustment strategy and related data, and determine a second electric stimulation parameter according to the first electric stimulation parameter and the influencing factor. The electric stimulation parameters given by the system of the present invention combine the influence of nystagmus patterns and individual differences, and determining the second electric stimulation parameters according to the first electric stimulation parameters and the influencing factors can achieve a more accurate and effective electric stimulation effect for the target user.

Provided are antisense agents, RNAi agents, pharmaceutical compositions, and methods of use for reducing the amount or activity of PLP1 RNA in a cell or subject, and in certain instances reducing the amount of proteolipid protein 1 in a cell or subject. In certain embodiments, also provided herein are oligomeric compounds and oligomeric duplexes for reducing the amount or activity of proteolipid protein 1 (PLP1) RNA in a cell or subject, and in certain instances reducing the amount of proteolipid protein 1 in a cell or subject. Such compounds, methods, and pharmaceutical compositions are useful to ameliorate at least one symptom or hallmark of a leukodystrophy. Such symptoms and hallmarks include hypotonia, nystagmus, optic atrophy, respiratory distress, delay in motor function development, cognitive dysfunction, speech dysfunction, spasticity, ataxia, seizures, choreiform movements, and death. Such leukodystrophies include Pelizaeus-Merzbacher disease.

The invention discloses a vestibular function detection system, a data processing method, electronic equipment and a program product. The method comprises the following steps: acquiring an eye movement video of a subject in vestibular function detection; extracting an eye movement track of the subject from the eye movement video; the eye movement track comprises at least one of a horizontal direction eye movement track, a vertical direction eye movement track and a twisting direction eye movement track; acquiring auxiliary detection data of the subject; the auxiliary detection data comprises body position data of the subject in vestibular function detection; inputting the eye movement track and the auxiliary detection data into a trained neural network model, and identifying and outputting vestibular function data of the subject through the neural network model; wherein the eye movement track is associated with the auxiliary detection data through time synchronization. Compared with only considering eye movement video or eye movement track data, body position data or nystagmus characteristic parameters, the scheme of the application enables the evaluated vestibular function data to be more accurate.

The invention relates to a method for detecting and evaluating pupil movements of a living body, in particular a human, preferably for detecting and analyzing nystagmus, comprising the following steps: creating (1) a video record by means of a mobile device, in particular by means of a smartphone or tablet, wherein the video record contains at least a portion of an eye-containing region of the face of the organism; extracting (2) still images from the video record at defined time intervals; a pupil center is defined (4) in each still image using a neural network, in particular a convolutional neural network, preferably a u-net convolutional neural network.

The present invention discloses a nystagmus video classification method and system based on spatio-temporal feature fusion, belonging to the technical field of video classification in medical image processing. It includes encoding and mapping the nystagmus video, obtaining spatial dimension features and temporal dimension features through a Spatial Transformer module and a Temporal Transformer module; passing them through a spatio-temporal feature fusion module to obtain fused spatio-temporal features; then inputting them into the Temporal-Spatial Transformer to continue feature extraction to obtain a feature map; and finally obtaining a classification result through a fully connected layer and a classification function. The present invention adopts a novel spatio-temporal feature fusion Transformer framework, without the need for manual feature extraction, and can well extract features of nystagmus videos, improving the classification accuracy.

The embodiment of the present invention discloses a method for identifying nystagmus type based on optical flow method, including: step 1: collecting nystagmus video of the patient through an infrared camera; step 2: extracting video frames of the nystagmus video every other frame; step 3: removing the closed-eye frames; step 4: using the transfer learning method to segment the iris part of the retained video frame; step 5: calculating the optical flow of continuous video frames, and cropping to obtain an optical flow map; step 6: inputting the obtained optical flow map into the trained ResNet+LSTM network model in sequence, and automatically identifying the nystagmus type through the network model. The present invention combines the optical flow method and deep learning to identify the nystagmus type, and can effectively and accurately identify rotational nystagmus.

The utility model discloses a dual-working-mode electronic otoscope suitable for a portable nystagmus view instrument. The dual-working-mode electronic otoscope comprises a primary otoscope cavity shell, a secondary otoscope cavity shell and an electronic otoscope, the first light-transmitting cover and the second light-transmitting cover are arranged on the mounting holes in the two sides of the main mirror cavity shell respectively; the magnifying lens is arranged on a mounting hole in the front end of the main lens cavity shell; the LED lamp ring is arranged on a mounting hole in the rear end of the main mirror cavity shell; the in-ear conical head shell is mounted at the rear end of the primary mirror cavity shell in a matched manner; the track camera is arranged in the in-ear conical head shell; the hand shifting roller a is arranged on a mounting hole in the side wall of the in-ear conical head shell and is meshed with a rack vertically arranged on the track camera, so that the track camera can be driven to move up and down when the hand shifting roller a is rotated; one end of the bendable cable is connected with the signal output end of the track camera and the power supply circuit, and the other end of the bendable cable is connected with the external display interaction device and the battery.

The application discloses a drug screening device and method based on microsaccade and pupil nystagmus analysis, comprising: an information acquisition module for acquiring the multi-modal original video stream of the tester's eye, obtaining multi-modal original data; an anti-interference processing module for denoising and enhancing the multi-modal original data to obtain a high-fidelity pure image sequence; a feature extraction module for multi-dimensional feature extraction and quantitative analysis of the high-fidelity pure image sequence to obtain a standardized multi-dimensional physiological feature vector; a research and judgment module for performing drug-related risk intelligent judgment according to the standardized multi-dimensional physiological feature vector to obtain a qualitative conclusion of drug-related risk; a human-computer interaction module for providing operation control, state display and result feedback in the detection process. The screening device is non-contact, non-invasive and fast in response, has strong on-site anti-interference ability and portability, significantly reduces the missed detection rate, and improves the efficiency and accuracy of public safety detection.

The invention discloses determining an operational capability of a manual operating system and control application. The methods presented herein may automatically determine a level of injury to a person, which may relate to execution of a task. A light and camera-based system may be used to determine a factor indicative of drunkenness or injury, such as gaze tremor. The test system may simulate motion of the light using the determined pattern and capture image data of at least an eye region of the person attempting to follow the motion. The captured image data may be analyzed using a neural network to infer at least one behavior of the user, and behavior determination may be used to determine a level of competence or impairment of the user. Appropriate measures may be taken, such as allowing a person with full ability to operate the vehicle or perform a task, or preventing access to such operation or execution if it is determined that the degree of damage to the person exceeds the allowable degree.

The present invention discloses a flexible pressure sensor for detecting nystagmus. The sensor comprises an encapsulation layer, a non-woven fabric@Au-Ag nanofiber membrane, and interdigital electrodes stacked in sequence from top to bottom. The stacked encapsulation layer, non-woven fabric@Au-Ag nanofiber membrane, and interdigital electrodes are encapsulated, and the ends of the interdigital electrodes are connected to external testing equipment via wires. The flexible pressure sensor for detecting nystagmus solves the problem in the prior art of using non-contact eye movement video or recording for eye movement analysis, which cannot accurately detect eye tremors. The present invention also discloses a method for preparing the flexible pressure sensor for detecting nystagmus.

The present disclosure relates to medical imaging testing, and specifically to methods, devices, and apparatuses for testing imaging quality for nystagmus patients.

Provided are a nystagmus analysis device and a program, with which nystagmus in a subject can be analyzed with high accuracy. Also provided is an analysis system using the analysis device and the program. The present invention is provided with: a data acquisition means (corresponding to processing in step S101) for acquiring waveform data representing a change in the line of sight of a subject over time; and an analysis means (corresponding to processing in steps S103 to S106) for analyzing the acquired waveform data to determine the occurrence timing of each of a plurality of times of nystagmus symptoms that occur within a prescribed period to be analyzed.

Provided are compounds, methods, and pharmaceutical compositions for reducing the amount or activity of PLP1 RNA in a cell or subject, and in certain instances reducing the amount of proteolipid protein 1 in a cell or subject. Such compounds, methods, and pharmaceutical compositions are useful to ameliorate at least one symptom or hallmark of a leukodystrophy. Such symptoms and hallmarks include hypotonia, nystagmus, optic atrophy, respiratory distress, motor delays, cognitive dysfunction, speech dysfunction, spasticity, ataxia, seizures, choreiform movements, and death. Such leukodystrophies include Pelizaeus-Merzbacher disease.

The present disclosure relates to medical imaging testing, and specifically to methods, devices, and apparatuses for testing imaging quality for nystagmus patients.

The utility model discloses an adjustable video acquisition device of a portable nystagmus view instrument, which comprises a shell A, three threaded holes in the outer wall of the shell A are respectively provided with a focal length adjusting knob, a horizontal direction angle adjusting knob and a vertical direction angle adjusting knob; the support frame is arranged in the shell A; the supporting table is arranged on the supporting frame, and a cylindrical convex rod on the supporting table is inserted into a round hole in the center of the supporting frame; the camera module mainboard is clamped on the supporting table; the module mainboard base is inserted into the camera module mainboard; the optical filter is arranged on the central hole in the module mainboard base; the lens base is inserted into the module mainboard base, an inner dustproof and anti-light ring on the lens base is assembled in an outer dustproof and anti-light ring in the center of the module mainboard base, and meanwhile the two ends of the lens base are connected with the two ends of the supporting frame.

The invention belongs to the field of computer-aided diagnosis, and relates to a method for judging the affected side of terrestrial horizontal tubulous benign paroxysmal positional vertigo, which combines artificial intelligence with a bending and supine test and a rolling test, and performs simple and effective affected side judgment on the horizontal tubulous benign paroxysmal positional vertigo by utilizing a nystagmus incubation period. The method comprises the steps of creating an affected side judgment model, testing and collecting nystagmus data, preprocessing the nystagmus data, conducting affected side judgment, combining a neck bending test, a sitting and lying position test and a 180-degree rolling test, collecting the nystagmus data through collecting equipment, and inputting the nystagmus data into the affected side judgment model for affected side judgment. The method disclosed by the invention is scientific and reasonable, simple and coherent in operation steps, low in operation cost, high in efficiency, small in interference and high in practicability, optimizes the determination method of the nystagmus incubation period, meets the clinical convenience requirement, and is suitable for large-scale popularization and application.