143 results about "Saccadic eye movement" patented technology

The invention provides a depression virtual reality auxiliary diagnosis and treatment method fused with multi-modal data, and the method comprises the steps: obtaining the multi-modal data, the multi-modal data comprises the peripheral physiological data, such as heart rate, body temperature and skin electricity, monitored by a flexible sensor based on epidermal electrons; and switching to a personalized interactive virtual scene according to the emotional state of the patient in real time, and in the interaction process, obtaining eyeball movement data by the eye movement tracking instrument, and knowing attention distribution, psychological state and micro facial expression change of the user. In combination with multi-modal data of peripheral physiological data, eye movement data and micro-expression change, key features are automatically extracted from multi-modal input data, and emotion analysis and recognition are performed through a multi-modal deep learning method with an attention mechanism. Data can be collected and analyzed in real time, the emotional state of a patient is objectively reflected through the combination of peripheral physiological data and micro-expression analysis, the requirements of the patient are met in a personalized mode, and the treatment effect is improved.

The invention provides a visual fatigue relieving method based on ambient light self-adaption and an AI algorithm, and relates to the technical field of visual health protection. The visual fatigue relieving method based on ambient light self-adaption and the AI algorithm comprises the following specific steps: S1, data acquisition: acquiring a user eye image sequence in real time through a high-frame-rate camera; and S2, parameter extraction: when the user uses the eye for the first time, testing the eyes by combining the adjustable light source with ambient light. Multi-dimensional features (such as eyeball movement, blinking mode, pupil function and the like) of eyes are collected in real time through a high-frame-rate camera, an individualized base line is established and a fatigue rate value is dynamically calculated in combination with data of an ambient light sensor, and conversion from passive response to active prevention is realized. Through a hierarchical intervention strategy (such as brightness adjustment, blue light control and forced rest), the visual load is remarkably reduced, the intervention efficiency is improved, and the problem of insufficient adjustment hysteresis and individual adaptability in the prior art is solved.

The invention discloses a Parkinson's disease early diagnosis system based on eyeball movement characteristic analysis, and relates to the technical field of Parkinson's disease diagnosis. In order to solve the problems that although eye and face movement parameters possibly change in Parkinson's disease, the change of the parameters also possibly occurs in other neurodegenerative diseases or normal aging processes, and high-precision eye and face movement capture data is complex, so that early diagnosis characteristics of Parkinson's disease cannot be accurately captured, and the Parkinson's disease cannot be accurately diagnosed. And the accuracy and efficiency of diagnosis are influenced. By accurately capturing and analyzing eyeball movement data and facial expression video images of a patient, the Parkinson's disease can be effectively distinguished from other diseases possibly causing similar symptoms, misdiagnosis and missed diagnosis are reduced, the standardization and comparability of data are ensured by combining pupil distance information and diopter information, the consistency and reliability of diagnosis are improved, and the diagnosis accuracy is improved. Therefore, the patient can be diagnosed at the early stage of the disease and is treated as soon as possible, and the treatment effect and life quality are improved.

In example implementations, an apparatus is provided. The apparatus includes a display, an eye tracking sensor, and a processor. The eye tracking sensor is to capture eye movements of a user. The processor is in communication with the display and the eye tracking sensor. The processor is to identify a type of eye movement from the eye movements captured by the eye tracking sensor and activate a control that is shown in the display.

A system includes one or more processors and one or more memories having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations include receiving detected ocular landmarks in a subject, determining ocular parameters based on the detected ocular landmarks, and determining, based on the ocular parameters, a coarse calibration output. The operations include receiving, eyetracking data relating to an eye movement made by the subject, determining a landing position of the eye at the end of the eye movement, sending a signal to display a target at the landing position on a screen, and receiving, from the subject, an input including a response relating the landing position to a gaze parameter of the subject. The gaze parameter is associated with the eye movement. The operations include updating the coarse calibration output based on the input.

The invention relates to an iris segmentation method using Purkinje reflection and a dynamic three-dimensional model, which comprises the following steps of: arranging a plurality of infrared light sources around a camera, and acquiring a plurality of frames of eye images with reflection points of a patient from a video sequence shot by the camera; calculating an eyeball center by using the position of the reflection point and establishing an initial three-dimensional eyeball model; according to changes of the positions of the inner canthus and the outer canthus, the three-dimensional coordinates and the posture of the eyeball center are correspondingly adjusted, and a three-dimensional eyeball model is updated; in the updated three-dimensional eyeball model, acquiring an iris radius according to an eyeball center, and establishing a three-dimensional iris circle equation; and projecting the three-dimensional iris circle to a two-dimensional image plane to obtain an iris ellipse parameter, and generating an iris segmentation result. Through constructing a dynamic three-dimensional model, eyeball model parameters including an eyeball center, an iris radius and an iris center are detected in combination with deep learning, a three-dimensional space optical axis and an iris ellipse are calculated, and iris segmentation adapted to head posture change and eyeball movement is realized.

The optical device for monitoring eye health includes a frame (1) in which ophthalmic lenses (2) coated with an infrared filter are mounted; infrared light emitters (7) that illuminate an inner face of the lenses (2), reflecting the light towards the eyes to create images by reflecting off the inner face of the lenses (2); cameras (3) that focus the images created by reflecting off the inner face of the lenses (2); and sensors (5) that detect, as data, the images recorded by the cameras (3); cameras (3) that focus the images created by the reflection of the inner face of the lenses (2); and sensors (5) that detect as data, such images of the eyes recorded by the cameras (3), sending the detected data to an external electronic device (9). It allows to determine from eye movement and other parameters, the eye health of a user's eyes to make an early detection of visual anomalies and other pathologies.

The invention relates to the field of music visual playing analysis, in particular to a music visual playing analysis system based on an eye movement tracking technology, which comprises an eye movement data acquisition module, a data preprocessing module, a visual feature extraction module, a music score synchronous mapping module, a performance evaluation module and a user feedback module. According to the scheme, a feature extraction method based on a video converter is adopted, eyeball movement data of a player is finely analyzed, and feature data of gaze point distribution, gaze time and a glancing path are extracted for subsequent deep analysis; the OCR technology is introduced to identify symbols in a music score image, and a dynamic mapping method is combined to accurately match eyeball movement data of a player with the symbols in the music score image, so that the method not only can monitor eye movement behaviors of the player in real time, but also can associate the behaviors with specific music score contents, thereby improving the accuracy of the music score. And teachers are helped to understand the visual playing process of students more deeply.

The invention discloses a depression diagnosis and treatment integrated humanoid robot based on multi-source information perception, and belongs to the field of medical instruments. The depression diagnosis and treatment integrated humanoid robot comprises a head module, a trunk module and a limb module which are worn outside a human body; a high-resolution camera, a small integrated microphone array, a gas sensor, a photoelectric sensor, a pressure sensor, an infrared sensor and a numerical control chip are arranged in the head module; the high-resolution camera is used for collecting facial recognition and eyeball movement features of a user; the small-sized integrated microphone array is used for dynamically collecting human body sound. According to the method, early warning, accurate diagnosis, personalized treatment and effective accompanying of depression can be realized, the accuracy and objectivity of depression diagnosis are improved, the illness state of a patient is comprehensively evaluated through multi-source information perception, all-weather emotion accompanying is provided, the psychological state of the patient is improved, the treatment compliance is improved, the problem of uneven distribution of medical resources is relieved, and the treatment effect is improved. And patients in remote areas can obtain high-quality diagnosis and treatment services.

The invention belongs to the technical field of medical equipment. According to the dynamic target control method and system based on dual-band OCT cooperative imaging, a dual-band OCT cooperative scanning strategy is adopted, a patient is assisted in watching through a built-in fixation target during near-infrared preview, and fixation target parameters are recorded; a scanning target spot is generated during visible light preview adjustment, the position of the scanning target spot is adjusted through fixation target parameters, the exposure time of a patient under visible light is shortened, the dazzling feeling is reduced, and the comfort level of the patient is improved; in the formal scanning stage, the scanning light beam generates a dynamic scanning target spot and periodically stays at a fixed position to guide a patient to watch, the problem that visible light shields a built-in target is solved, and eyeball movement artifacts are effectively reduced.

Wearable nystagmus detection devices are provided. The wearable device comprises first and second sensors configured to sense eye movement of the subject, and circuitry operably coupled to the sensors and configured to detect horizontal and vertical eye movements based on signals from the first and second sensors and / or a transmitter configured to transmit signals sensed by the first and second sensors to remote circuitry configured to receive signals transmitted by the transmitter and to detect horizontal and vertical eye movement based on signals from the first and second sensors. Also provided are systems and kits that include the devices, as well as methods for using devices and systems to monitor eye movement of a subject. The devices, systems, methods and kits find use in a variety of different applications.

Presented herein are systems and techniques for using an external component / device to collect eye movement data that is complementary to neurological measures / measurements (e.g., EEG measurements, inner ear measurements, or other electrophysiological measurements) obtained by an implantable component / device. Recipient eye movement can be tracked directly (e.g., with smart glasses) and / or indirectly (e.g., using eye movement-related eardrum oscillations (EMREO) measurements). The systems and techniques presented herein can use an implantable component (e.g., a cochlear implant, an EEG implant, etc.) to obtain electrophysiological measurements from a recipient. According to aspects presented herein, the electrophysiological measurements and the eye movement measurements are analyzed together in order to, for example, diagnosis a medical condition, predict or characterize a medical event, etc.

The invention discloses a spectrum control axis adjusting method and system for assisting myopia prevention and control, and relates to the field of biomedical engineering.The method comprises the steps that a user uploads personal information, meanwhile, current illumination data and eyeball movement data of the user are monitored and collected, and the personal information, the current illumination data and the eyeball movement data of the user are preprocessed; establishing a user spectrum model based on the preprocessed personal information and the current illumination data of the user, predicting the optimal spectrum combination of the user, adjusting the specific gravity combination of each wave band in the LED light source according to the prediction result, monitoring the actual spectrum entering the eyes in real time, and comparing the actual spectrum with the optimal spectrum combination of the user, adjusting the spectrum output of the LED light source according to the difference; by establishing the user spectrum model, the spectrum combination can be dynamically adjusted according to the real-time environment condition of the user, and it is ensured that the light condition most suitable for the user is provided. And the visual comfort of the user and the myopia prevention and control effect are obviously improved.

To provide a wearable device and a display method that changes the content to be displayed as a line of sight moves.SOLUTION: A wearable device includes: a display unit which displays a real-world image and an augmented reality image; a first detection unit which detects a line of sight and eye movement; a second detection unit which detects motion of the head; and a determination unit which determines whether the eye movement is synchronized with the motion of the head. When the device determines that the eye movement is not synchronized with the motion of the head, the display unit displays the augmented reality image. The wearable device includes a processing unit configured to select, when the type of the eye movement indicates closed eyes, an information item gazed, out of a plurality of information items, and start, when the type of the eye movement indicates wink, execution of processing on the selected information item.SELECTED DRAWING: Figure 17

To provide a novel method for measuring movement of an eye by using a scanning imaging technique.SOLUTION: An ophthalmological data processing method receives a data set and time-series data. The data set is acquired by applying optical scanning to a subject's eye following a two-dimensional pattern including a series of cycles that intersect each other. The time-series data includes data representing time-series changes in the subject's head position. Alternatively, the method generates position history data representing time-series changes in the position of the subject's eye based on the received data set. Further alternatively, the method generates evaluation data based on the generated position history data and the received time-series data.SELECTED DRAWING: Figure 4B

The invention relates to a pilot SA ability evaluation system based on eye tracking and spatial directional flight simulation, comprising a spatial directional flight simulator for simulating a real flight environment; an eye tracker for recording the eye movement trajectory of a pilot in real time in the simulated real flight environment to obtain eye tracking time series data and shoot a flight training video; a microprocessor evaluation module comprising a time series data processing module and a Ti-SA model; the time series data processing module obtains corresponding AOI gaze time series data based on the eye tracking time series data, the flight training video and a preset AOI subdivision area; the Ti-SA model predicts the pilot's current SA ability value based on the eye tracking time series data and the AOI gaze time series data, and determines whether the predicted SA ability value is lower than a preset SA threshold value, and if so, sends an early warning instruction to an early warning and voice broadcast module; and the early warning and voice broadcast module is used to issue an early warning when the SA ability value is lower than the preset SA threshold value.

An electronic device may have a display for displaying image content. Head-mounted support structures in the device may be used to support the display. The electronic device may have an eye monitoring system that detects eye saccades and eye blinks. Control circuitry in the electronic device may coordinate operation of the display with periods of suppressed visual sensitivity that are associated with the saccades and blinks. By making adjustments to display circuitry and image content during periods of suppressed visual sensitivity, potentially visually obtrusive changes to displayed images can be hidden from a user of the electronic device. Adjustments to display operation may help reduce burn-in effects, may help reduce power consumption, and may otherwise improve device performance.

A gaze-trajectory-based eye movement data visualization method and apparatus, and a storage medium. The method comprises: by means of collected eye movement data, obtaining a tested gaze point position, gaze point sequence, and gaze point trajectory (S110); according to the angle of a connecting line between two neighboring gaze points, mapping the connecting line between the two neighboring gaze points into a visualization graph (S130); and within the visualization graph, connecting the vertex of the connecting line corresponding to each angle, forming a visualization graph of eye movement glancing direction frequency (S140). The visualization graph of eye movement glancing direction frequency is used to provide an eye movement gaze trajectory algorithm, allowing for visually and accurately reflecting individual eye movement gaze features.

The invention relates to an eyeball movement training control method and system based on multi-mode light spot guidance, and the method employs the multi-directional distribution of light-emitting points, controls the light-emitting points to be lighted at a constant angular velocity in order through a control program or instruction, or is lighted based on a pseudo-random number algorithm, and the lighted light-emitting points actively guide the eyeball movement of a trainee. The purpose of eyeball movement training is achieved. The lamp beads are sequentially lightened at a constant angular speed to guide eyeballs to do smooth following motion, so that the continuous tension state of ciliary muscles is relieved, and the ciliary muscles are relaxed; a discontinuous light spot coordinate sequence is generated based on a pseudo-random number algorithm, eyeballs are guided to rapidly switch fixation points in the horizontal direction, the vertical direction and the oblique direction, the dynamic adjustment ability of ciliary muscles is trained, variable parallax is generated, and the lens adjustment sensitivity is enhanced. The light-emitting points are physical LED light or virtual dynamic sighting marks generated by running programs or instructions through computer equipment with a displayer, the positions of the light-emitting points do not need to be moved, the device does not need to be worn, and a user can use the device conveniently.

This invention relates to the field of image edge detection technology, specifically to an eyelid detection system for assessing the orbicularis oculi muscle movement function in patients with myasthenia gravis. The system includes a video frame acquisition module, an iris morphology reconstruction module, an interference level acquisition module, a gradient map correction module, and an eyelid edge detection module. By acquiring video frame data of the patient's eyes, the system corrects iris deformation in the iris region of the target image frame corresponding to eye movement. Based on the corrected iris region, the system analyzes the interference of iris morphology on eyelid edge detection, determines the degree of iris deformation interference, and then corrects the gradient values ​​of gradient points in the same area corresponding to the corrected iris region in the gradient map of the target image frame during eye movement, obtaining a corrected gradient map. Based on the corrected gradient map, the system determines the patient's eyelid edge detection result. This invention effectively improves the accuracy of eyelid edge detection for patients.

A method for determining a type of characteristic eye movement of the eyes of a patient (P) comprises the steps of providing the patient (P) with an optokinetic stimulus (OS) for the characteristic eye movement, generating a medical image (BD) of the brain of a patient (P) also including the eyes (E) of the patient (P). The method also includes the steps of determining an amount (A-DP) of a displacement of an optic nerve (ON) of the patient (P) based on the medical image (BD) and determining a type of a characteristic eye movement based on the velocity of eye movement for the determined amount (A-DP) of displacement of the optic nerve (ON). Besides, a method for training an artificial intelligence based algorithm (A) for determining an amount (A-DP) of a displacement of an optic nerve (ON) of a patient (P) based on at least one medical image (BD) is described. Further, an eye movement-determination device (10) is described. Furthermore, a medical imaging system (1) is characterized.

The application protects an iris segmentation method using Purkinje reflection and dynamic three-dimensional model, which comprises the following processes: a plurality of infrared light sources are arranged around a camera, and a plurality of frames of eye images with reflection points are obtained from a video sequence captured by the camera; the eye center is calculated by using the position of the reflection points, and an initial three-dimensional eye model is established; the three-dimensional coordinates and posture of the eye center are adjusted according to the change of the inner and outer canthus positions, and the three-dimensional eye model is updated; in the updated three-dimensional eye model, the iris radius is obtained according to the eye center, and a three-dimensional iris circle equation is established; the three-dimensional iris circle is projected onto a two-dimensional image plane to obtain iris ellipse parameters, and an iris segmentation result is generated. By constructing a dynamic three-dimensional model, combining with deep learning to detect eye model parameters including the eye center, the iris radius and the iris center, calculating the three-dimensional space optical axis and the iris ellipse, the iris segmentation adapting to the head posture change and the eye movement is realized.

The present invention relates to an eye movement function quantitative evaluation system based on an eye tracker, which can realize automatic quantitative evaluation of three eye functions: fixation, saccade and smooth pursuit, and provide support for eye disease diagnosis and eye rehabilitation effect evaluation. The system includes an eye tracker, an evaluation interface generation module, a data processing module, a motor function evaluation module and an evaluation result display interface. The computer processes the acquired eye movement data, calculates the eye movement data characteristics, designs the eye movement function quantitative rating index, and automatically gives the quantitative rating result, so that the diagnosis result is more accurate, intuitive and convenient, reduces the workload of doctors, provides doctors with more accurate eye movement diagnosis information, and helps doctors understand the patient's eye movement function status, so as to better diagnose and treat. Starting from the clinical needs of ophthalmology, this system realizes automatic quantitative evaluation and grading of eye movement function, provides reference for eye disease diagnosis and eye rehabilitation effect evaluation, and is of great significance.

1. The name of the design product: eye movement assembly of human eye movement simulation device. 2. The use of the design product: the whole product is used to simulate the movement of human eyes, suitable for medical education, eye movement tracking test, optical product quality inspection, AR\VR device evaluation field; locally used for eye movement assembly of human eye movement simulation device. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design. 6. Other circumstances that need to be explained: this patent application protects the local design: the part protected in design 1, design 2 and design 3 is the part drawn in solid line, the part drawn in dotted line in the view does not constitute the part protected by the local appearance.

An oculography method, in particular a smart-glasses oculography method for pairs of augmented reality smart glasses and / or for pairs of virtual reality (VR) smart glasses / VR headsets. The method includes at least one oculography step in which at least one eye movement of an eye, in particular an eye of a smart-glasses user, is ascertained, in particular tracked, by a subset of laser feedback interferometry sensors of an LFI sensor array which is associated with the eye. In at least one selection step, which precedes the oculography step in time, a selection of at least one LFI sensor provided for performing the oculography step, which follows in time, is made based on a parameter comparison of test measurements of multiple LFI Sensors of the LFI sensor array.

The invention relates to a generation method for automatically generating an eyeball movement data set (30) for training artificial intelligence (100) to classify a digital eyeball movement video (110), comprising the following steps:-providing an eyeball movement model (20) simulating a biological correlation between at least one input parameter (22) and an eyeball movement induced thereby, at least one influence parameter (24) is taken into account,-setting at least one influence parameter (24) relating to a certain medical defect (MD) for the provided eyeball movement model (20),-setting at least one input parameter (22) relating to a certain eyeball movement test for the provided eyeball movement model (20),-determining the eyeball movement model (20) according to the set influence parameter (24) and the input parameter (22). The method comprises the following steps:-generating an eyeball movement data set (30) using an eyeball movement model (20),-storing the generated eyeball movement data set (30) together with medical defects (MD) associated with influencing parameters (24) as tags in an eyeball movement database (40),-repeating the steps of inputting, generating and storing, and altering the at least one influence parameter (24) and / or the at least one input parameter (22).

The invention provides a Parkinson's disease freezing gait prediction method and device based on eye movement characteristics, equipment and a medium. The method comprises the following steps: acquiring target information corresponding to a target object; the target information comprises target demographic data, target clinical features and target eyeball motion parameters collected at a certain time point, and / or target demographic data, target clinical features and target eyeball motion parameters continuously collected according to a preset frequency within a preset time; and inputting the target information into the target frozen gait prediction model, so that the frozen gait prediction model analyzes and processes the target information to obtain a static frozen gait risk assessment result and / or a dynamic frozen gait risk assessment result corresponding to the target object. According to the scheme, through multi-dimensional integration and collaborative verification of traditional clinical phenotypes and objective indexes of eye movement, non-invasive efficient evaluation of frozen gait risks is achieved, and objective basis and key technical support can be provided for early diagnosis and early treatment of disease subtypes.

The present invention discloses an early screening device and screening system for Parkinson's disease based on eye movement, which belongs to the technical field of Parkinson's behavioral feature recognition. The early screening device and screening system for Parkinson's disease based on eye movement include a shell, one side of the upper end of the shell is provided with an operating screen for a built-in screening system, one side of the interior of the shell is provided with a storage cavity, and the lower end of the storage cavity is provided with a telescopic rod. The present invention solves the problem that the existing early screening system for Parkinson's disease has poor adaptability to different patients during the screening process. The second support arm of the present invention can drive the fixed frame at the front end to rotate after being driven by a motor, and adjust the fixed frame to face the seat cushion and the movable cavity respectively. A patient sitting in a wheelchair can move directly to the seat cushion position. Finally, the rotation of the fixed frame can cope with patients sitting on the upper end of the seat cushion and patients lying on the bed and close to the movable cavity position.

Systems and methods are provided that assess eye movement in multiple sclerosis (MS) patients receiving different drugs (e.g., dimethyl fumarate, fingolimod, clababine, ofarmumab) or treatments that (a) alleviate inflammation that may cause a symptom of multiple sclerosis and prevent nerve injury that may cause a symptom of multiple sclerosis); (b) testing sphingosine-1-phosphate receptor modulators that chelate lymphocytes in the lymphocyte nodes, preventing them from causing an autoimmune response); (c) checking for immunosuppressants acting on the lymphocyte pathway); and (d) analyzing the effect of the monoclonal antibody in inhibiting activation of lymphocyte B.

The invention relates to a method of processing data representative of a person's binocular motricity, the method comprising the following steps: —stimulating the binocular motricity of a person by means of a binocular motricity stimulation device (21) configured to specifically stimulate saccades, vergences or a combination of both or of a reading test (22); physical stimuli in 3D real space seen with both eyes naturally (without artifices); acquiring the movement of the right eye (RE) and left eye (LE) of a person (P) during said stimulation and, if applicable, a stimulation signal from the binocular motor stimulation device; the method comprising the following steps implemented in a processing unit (3); determination from the movement of the left eye (LE) and the right eye (RE), of an effective trajectory (Tr1) of the eyes in response to each stimulation, an effective trajectory corresponding to a saccade and / or a vergence movement of the eyes.