84 results about "Electro oculogram" patented technology

A method for diagnosis of a sleep-related condition of a patient having a thorax. The method includes receiving physiological signals from sensors coupled to the thorax of the patient, and analyzing the physiological signals, independently of any electroencephalogram (EEG) or electro-oculogram (EOG) signals, in order to identify sleep stages of the patient.

The invention discloses a sleep period separating method and system. The method is applied to a sleep period separating system. The system comprises a first measuring electrode, a second measuring electrode, a first reference electrode, a second reference electrode, an amplification collector and a period separating device. The first measuring electrode is used for being placed on the left side of the forehead or the temporal hair-free region on the left side of a testee, the second measuring electrode is used for being placed on the right side of the forehead or the temporal hair-free region on the right side of the testee, the first reference electrode is used for being placed on the periphery of the left ear of the testee, and the second reference electrode is used for being placed on the periphery of the right ear of the testee. The method comprises the steps that the first measuring electrode and the second measuring electrode are utilized for collecting electroencephalogram signals and electro-oculogram signals of the testee, the signal amplification collector is used for amplifying the electroencephalogram signals and the electro-oculogram signals and carrying out analog-digital conversion on the amplified signals. The period separating device determines the separated sleep periods according to the analog-digital converted electroencephalogram signals and electro-oculogram signals.

The invention discloses a brain electric features based emotional state recognition method. The method comprises the following steps of: data acquisition stage: under the condition of international emotional picture induction, extracting 64 brain electric data which is tested under the induction of different-happiness-level pictures; data pretreatment stage: carrying out four stages of reference electric potential variation, down sampling, band-pass filtering, electro-oculogram removal on the collected 64 brain electric data; feature extraction stage: extracting time domain features after signals after pretreatment are filtered by a common space model algorithm; and feature recognition: recognizing the features by using a support vector machine classifier, and differentiating different emotional states. According to the method, an OVR (one versus rest) common space model algorithm is used for removing the interference of background signals, and is used for the signal intensification of multiple types of emotion induced brain electricity; after the background signals are removed, the differences among different types of emotional brain electricity are intensified, the recognition accurate ratio of subjects is relatively ideal when the recognition is carried out by the time domain variance features, and the emotions of different happiness can be differentiated accurately.

The invention provides a method for rapidly and automatically identifying and removing ocular artifacts in an electroencephalogram signal and belongs to the technical field of biological information and the method is mainly applied to a process of acquiring and preprocessing the electroencephalogram signal. The method comprises the following specific steps of: carrying out discrete wavelet transformation on an acquired multi-channel electroencephalogram signal and an electro-oculogram signal to obtain multi-scale wavelet coefficients; using the wavelet coefficients connected in series as an input for analyzing an independent component, and rapidly acquiring the independent component by using a negative entropy criterion-based Fast ICA (Independent Component Analysis) algorithm; identifying the ocular artifacts through a cosine method, performing zero resetting on the independent component, and projecting the other components through ICA inverse transformation and returning to all electrodes of an original signal; and finally obtaining the electroencephalogram signal for removing the ocular artifacts through inversion of the wavelet transformation. By utilizing the method for rapidly and automatically identifying and removing the ocular artifacts in the electroencephalogram signal, the problems that an ICA method is poor in discrete effect and low in convergence rate when beingapplied to noisy electroencephalogram signals are solved, and the function of rapidly and automatically identifying and removing the ocular artifacts in the electroencephalogram signal is realized.

The invention discloses a fatigue detection method based on multi-source information fusion. Electroencephalogram signals, twinkling information and electrocardiosignals of a testee are synchronously collected by means of an electroencephalogram collecting device and an electrocardiogram collecting device respectively; electroencephalogram signal features including the relative energy of electroencephalogram rhythm waves alpha, beta, theta and delta, electro-oculogram information including twinkling frequency E and twinkling intensity F, and electroencephalogram features including heart rate values HR, LF and HF are extracted; by means of the logistic regression algorithm, the fatigue degrees are primarily divided into three classes, namely, the non-fatigue degree, the mild fatigue degree and the deep fatigue degree, and meanwhile features with large weights are screened according to logistic regression weights for feature fusion; fused feature vectors are classified again by means of the bagging algorithm based on a support vector machine, the processed feature vectors serve as input of the bagging algorithm, and the current fatigue degree of the testee is determined; different fatigue relieving methods are used according to classification results of the fatigue degree of the testee. The method has the advantages of being high in applicability, high in fatigue detection precision, good in improvement effect and the like.

The invention provides a wearable portable device and method for analyzing eye movement. A flexible wearable electrode frame is used for acquiring a two-channel electro-oculogram (EOG) signal; after preprocessing, EOG in the vertical direction adopts a suggested blink processing algorithm based on wavelet transform-double-threshold processing to perform linear interpolation compensation on a blink signal, and conscious single-blink and double-blink components are separated; after median filtering is performed on horizontal and blink-removal EOG, digital filtering is performed through parameters obtained through a method based on self-adaptive filtering in training mode, two-dimensional position information of a target gazing by the human eye is decoded, and information of speed and accelerated speed of the object is obtained through a derivation module; all parameter information can be displayed through a screen or wirelessly transmitted to an external interactive device to perform coding control; and a user obtains a control result through visual feedback and performs next eye movement control so as to achieve man-machine interaction.

The invention discloses a man-machine interaction method supported by the multi-modal non-implanted brain-computer interface technology. The method comprises the following steps: 1) a user carries out all motion imaginations and all eye motions according to prompt signals, and the user's EOG signal and EEG signal are collected; 2) pre-treatment is carried out on the EOG signal and the EEG signal respectively; 3) an electroencephalogram classified result and an electro-oculogram classified result are obtained according to the EOG signal and the EEG signal; 4) when an external device is controlled, the user carries out the corresponding motion imagination and the corresponding eye motion according to the prompt signal, the user's current EOG signal and EEG signal are collected, and pre-treatment is carried out on the user's current EOG signal and the user's current EEG signal respectively; 5) computer control is carried out according to the user's current EOG signal, the user's current EEG signal, the electroencephalogram classified result and the electro-oculogram classified result after pre-treatment. The method can realize complex instruction output of the non-implanted brain-computer interface, and is strong in control capability on the external device.

The invention relates to an electro-oculogram control system and method based on correction/training. The system comprises an electro-oculogram signal acquiring and amplifying system, an electro-oculogram signal processing system and an intelligent control system. Sensors of the signal acquiring and amplifying system are arranged around eyes, and outputs of the sensors are connected to the signal processing system. The signal processing system is connected with the intelligent control system in a wireless transmission mode. The specific working process is that the acquiring and amplifying system acquires an electro-oculogram signal through the electro-oculogram sensors and performs gain amplification and filtering; the signal processing system acquires electro-oculogram signal characteristics, performs matching analysis to the electro-oculogram signal characteristics and eye gesture characteristic parameters stored in a correction/training mode, judges the eye gesture types and sends command codes to the intelligent control system in a wireless mode; and the intelligent control system outputs a control signal to achieve the control of a controlled device. The electro-oculogram control system and method based on correction/training is high in measuring accuracy, good in robustness, simple in operation and capable of helping disabled people to improve independent living ability, and can be further used in special dangerous working occasions or working occasions with severe conditions.

The invention relates to an electro-oculogram signal-based computer input control method which comprises the following steps of: 1, presetting a keyboard key selection area in a computer, wherein keys in the keyboard key selection area are arranged in a multi-row multi-column matrix; 2, circularly switching highlight selection area in the keyboard key selection area according to rows, acquiring and identifying an electro-oculogram and inputting the electro-oculogram serving as a control signal to the computer by an electro-oculogram acquisition transmission module, simultaneously stopping switching the highlight selection area according to the rows, and circularly switching highlight keys in the highlight selection area according to columns; and 3, acquiring and identifying the electro-oculogram again and inputting the electro-oculogram serving as the control signal to the computer by the electro-oculogram acquisition transmission module, and simultaneously stopping switching the highlight keys according to columns, wherein the highlight keys are used as the input control result of the computer. The method has the advantages that complex computer input control can be performed, and a user can use the computer without obstacles by using the method.

The invention discloses a service-oriented movable manipulator system. The hand-eye coordinated movement of human vision and a movable manipulator is achieved for the target discovery and orientation of human contact movement and the process that arms approach a target and the target is aimed. The service-oriented movable manipulator system mainly comprises a head information collecting system 3, a man-machine interactive system 8, a movable manipulator decision control system 9, a human visual special orientation and position estimation system 10 and the like, wherein the man-machine interactive system 8 is composed of a picture signal collecting and processing module 8a, an electroencephalogram collecting and processing module 8b, an electro-oculogram collecting and processing module 8c and a head gesture signal collecting and processing module 8d. According to the human visual special orientation and position estimation system 10, the target discovery is formed with the characteristics of eye fixation points, the special orientation and position of a target object are estimated on the basis of electro-oculogram and head motion information, and accordingly motion planning and motion control of the movable manipulator are achieved, and the hand-eye coordinated movement of a human body and the movable manipulator is achieved.

The invention discloses an eye movement signal identification system and method based on a common spatial pattern. The eye movement signal identification system comprises an eye movement signal preprocessing module, a spatial filter training module and an eye movement signal identification module. The eye movement signal identification method comprises the steps of collecting eye movement data based on an electro-oculogram and preprocessing the eye movement data; dividing all the preprocessed data into training data and testing data; adopting a CSP algorithm to conduct spatial filtering on the training data, and using the result obtained after filtering as feature parameters which are input into an SVM classifier for SVM model training; using the CSP algorithm to conduct feature extraction on the testing data, feeding the result obtained after the feature extraction into the trained SVM classifier for identification, and finally obtaining the identification result of eye movement. The eye movement signal identification system and method have the advantages that the accuracy of eye movement signal identification is higher, the eye movement signal spreading and classification capability is higher, and the application potential is large.

A problem related to a known eyewear-type electro-oculogram measuring apparatus which detects the eye potential using a pair of electrodes positioned outside both the eyes of a user and a pair of electrodes respectively positioned above and below one eye is that the two pairs of electrodes have had an impact on the skins of users, and discomfort on them. Besides, the electrodes are not excellent in design. The present invention provides eyewear including: a frame; a pair of nose pads; and a first electrode and a second electrode respectively provided on the surface of the pair of nose pads, the first electrode and the second electrode detecting eye potential

The invention discloses a pair of sleep monitoring eye patches and a sleep monitoring method for electroencephalogram and electro-oculogram composite detection, and relates to the technical field of sleep monitoring. An electroencephalogram electrode and a left-eye electro-oculogram reference electrode are fixed to the inner side face of an eye patch main body, wherein the electroencephalogram electrode is located on a corresponding part of Fp2; and the left-eye electro-oculogram reference electrode is arranged on a corresponding par of EOG left (electro-oculogram left). A main circuit board and a power supply battery are fixedly arranged in an interlayer of the eye patch main body; a signal processing module, a signal separating module and a wireless transmission module, which are sequentially connected, are integrated on the main circuit board; the signal processing module is connected to the electroencephalogram electrode and the left-eye electro-oculogram reference electrode; the wireless transmission module is in wireless communication with an intelligent terminal outside; and a right leg driving electrode, which is located on a corresponding part of Fp1, exposed out of the eye patch main body and is connected to the signal processing module, is additionally fixed to the main circuit board. With the application of the sleep monitoring eye patches and the sleep monitoring method disclosed by the invention, the problem that electroencephalogram signals are canceled is solved, so that the validity of the acquired signals is guaranteed; and in addition, by conducting the electroencephalogram and electro-oculogram, the quality of sleep monitoring is enhanced.

The invention discloses an electro-oculogram collecting method and a Bluetooth mouse system based on electro-oculogram control; through the electro-oculogram processing method, the method can recognize the eye's actions of looking leftwards, rightwards, downwards, upwards and blinking twice, and define different mouse operations corresponding to different eye's actions. The Bluetooth mouse system based on the electro-oculogram control comprise an electro-oculogram collecting electrode, an electro-oculogram collecting module, an analog-digital converter, a digital signal processor, a Bluetooth module and a power module. The Bluetooth mouse system is used for realizing different operations of a user by controlling the mouse through the eye's actions, thereby helping patients with deficiency of both arms to surf the internet by an electronic device as an ordinary person. The Bluetooth mouse system is simple in circuit structure, small in volume, convenient to carry, strong in antijamming capability, and can be widely applied to the mobile medical treatment, household patient nursing and other fields.

The invention discloses a factor analysis based ocular artifact removal method. The method mainly includes: performing basic processing on electroencephalogram data and extracting a synchronously-recorded electro-oculogram (EOG); then extracting all factors in an electroencephalogram by means of factor analysis; combining with correlation analysis to solve a correlation coefficient of each factor with the synchronously-recorded electro-oculogram, and finding out the factor (determined as an ocular artifact factor) with the maximum correlation coefficient; after the ocular artifact factor is removed, restoring to obtain an electroencephalogram with ocular artifacts removed. By the method, the problem that ocular artifact components are judged artificially and subjectively in a traditional independent component analysis method is solved, and the maximum correlation coefficient is directly utilized to determine the ocular artifact factor; meanwhile, compared with the independent component analysis method, the method has the advantages that the electro-oculogram correlated factors can be found out better, the ocular artifacts can be removed better, and the method is of great significance to electroencephalogram analysis technology.

The invention discloses a man-machine interactive type two-dimensional locating method based on a human eye-glanced signal, which comprises the following steps of: extracting and identifying a characteristic of electro-oculogram (EOG) data detected by repeated test to disclose a mapping law between the movement angle of an eyeball and the characteristic of the EOG statistical signal, building an EOG signal-based basic model for locating a two-dimensional plane target, and correcting the parameter of the basic locating model by considering the individual difference to be detected during the practical application to be capable of fast obtaining a practical locating model which is applicable to each object to be detected. The real-time on-line detection of a detection signal can be realized by an endpoint detection technology when the model is built, so that the method lays a foundation for realizing an on-line interactive type system. A coordinate converting relationship between an eye and a bionic mechanical arm can be fast built by a certain field calibration method. The interactive type two-dimensional precision position control between the eye and the bionic mechanical arm can be realized by the system.

The invention discloses a portable electroencephalogram collection system which comprises a collection electrode and a signal processing system. The signal processing system comprises a microcontroller, an input filter, a static protection unit, an instrument amplifier, an analog-digital converter, a storage module, a radio frequency transceiver, a power source management system and a display operation module, the power source management system comprises a power source module, a program storage unit and an induction eddy current charging circuit, and a display input module comprises a state display lamp and a button configuration unit. Electrodes are placed at foreheads of Fp1, FpZ and Fp2, and interference caused by hair is avoided, so that medical pasted wet electrodes are used, and interference of electrode contact impedance is avoided. A low-power-consumption device is adopted mainly, and the power source management system is arranged, so that state of a power source can be monitored, noise can be removed effectively, and elimination of electro-oculogram noise is based on an improved algorithm of discrete wavelet transformation and self-adaptive noise offset.

The invention provides an extraction method and an extraction device for the direction of eye movement based on electro-oculogram signals. The method sequentially comprises a training phase a and a testing phase b; the training phase a comprises the following steps of: (a1) arranging an electrode; (a2) beginning to collect electro-oculogram signals; (a3) pre-treating; (a4) carrying out smoothing treatment; (a5) extracting the characteristic vectors of the directions of eye movement; (a6) projecting the electro-oculogram signals in different directions to the characteristic vector in the same direction; (a7) carrying out differential treatment on a projecting result; and (a8) preserving the characteristic vectors; and the testing phase b comprises the following steps of: (b1) arranging an electrode; (b2) beginning to collect electro-oculogram signals; (b3) pre-treating; (b4) carrying out smoothing treatment; (b5) projecting the electro-oculogram signals to the characteristic vectors of the directions of the eye movement, which are obtained in the training phase a; (b6) carrying out differential treatment on a projecting result; and (b7) identifying the direction of the eye movement of a person to be tested in the testing phase b according to the positive-negative classification of the electro-oculogram signals corresponding to the maximum amplitude of a differential result .

The invention relates to an intelligent wearing device, in particular to a virtual-reality device with the head-bio-electricity-signal-based human-computer interaction function. According to the virtual-reality device, as a bio-electricity signal collecting module is additionally arranged in a traditional virtual-reality device, electroencephalogram (EEG), electro-oculogram (EOG) and electromyogram (EMG) of a user are collected through the bio-electricity signal collecting module at the same time, and the human-computer interaction function in multiple modes including electroencephalogram interaction, electro-oculogram interaction, electromyogram interaction and combinations thereof can be achieved on the virtual-reality device by analyzing and calculating the three characteristic signals.

The invention discloses a method for simultaneously removing multiple artifacts from single-channel electroencephalogram signals. The method includes the following steps that, firstly, single-channelelectroencephalogram signals are decomposed through singular spectrum analysis, and a multi-dimensional signal component matrix is obtained; 2, a second-order blind identification method is used for blind source separation of the signal component matrix, and several independent source components are obtained; 3, the independent source components containing the artifacts are selected and subjectedto zero setting; 4, the independent source components obtained after zero setting are subjected to blind source separation inverse transformation, and the clean single-channel electroencephalogram signals are obtained after reconstruction. The method achieves simultaneous removal of the artifacts (myoelectricity, electro-oculogram and electrocardio artifacts) from the single-channel electroencephalogram signals, and electroencephalography components in the signals are effectively retained.

Provided is portable sleep monitoring equipment. Hospitals normally adopt polysomnography system to detect patients' electroencephalograms, electro-oculograms, lower jaw electromyograms, oro-nasal airflow, breathing movement, electrocardiograms, blood oxygen, snore, limb movement, positions and other parameters, and then the patients' deep and light sleep cycles and quality are analyzed. The portable sleep monitoring equipment includes a power supply management unit, a communication unit and an acceleration sensor and further includes a physical sign monitoring module; the physical sign moduleis provided with a red light LED, an infrared light LED and a photosensor; a shell of the portable sleep monitoring equipment is made of a light-proof material, and the portions, corresponding to theLEDs and the photosensor, of the shell are made of a light transmittance material. The communication unit includes a wireless communication unit, an information relay unit and a server, wherein the information relay unit and the server are communicated through a network. The physical signs monitored by the physical sign monitoring module include pulse waveform, heart-rate values, blood oxygen values and blood vessel microcirculation parameters.

The invention relates to an aircraft three-dimensional space target searching system and method based on electroencephalogram and electro-oculogram. The system comprises an aircraft, an electrode capand a PC-side ground control system. The method comprises the following steps: the aircraft collects environment data through a two-dimensional laser range finder to process so as to obtain a feasibledirection of the aircraft, and sends the feasible direction to the PC-side ground control system; the PC-side ground control system converts electroencephalogram collected by the electrode cap into ahorizontal direction task and a vertical direction task of the aircraft and a control instruction converted at two direction task interfaces to send to the aircraft. By adopting the way of combiningthe hybrid brain-computer interface collected to the 6-lead left-right hand motor imagery electroencephalogram feature and 2-lead blinking feature and a semi-autonomous navigation based on the two-dimensional laser range finder, the indoor three-dimensional space target search in the multi-rotor aircraft is realized, the system has the advantages of being high in intelligence degree, low in computing overhead, easy to operate, stable in control, and capable of enabling the user to accomplish more control tasks at the same time.

The invention discloses a sleep monitoring device and a system. The system comprises a sleeping monitoring device, a data processing and transmitting module, a cloud platform and an analysis display terminal, wherein the sleep monitoring device comprises an electroencephalogram monitoring module and an electro-oculogram monitoring module which are connected through a flexible circuit and are usedfor monitoring electroencephalogram and electro-oculogram signals of a human body, and the electroencephalogram monitoring module comprises a feedback electrode, a reference electrode, an electroencephalogram monitoring electrode and a first processing circuit; the electro-oculogram monitoring module comprises an electro-oculogram monitoring electrode and a second processing circuit. By the aid ofthe wearable sleep monitoring device and the wearable sleep monitoring system, distributed and accurate measurement of sleep monitoring can be realized, and the current situation is improved that thewearable sleep monitoring device based on bioelectrical signals and having high precision and medical grade is lacking at present.

The invention relates to a barrier-aiding activity platform based on electro-oculogram signal control. The platform comprises an electro-oculogram signal acquisition module, a controller and a man-machine interaction module, and controlled objects are household appliances and wheelchairs; the electro-oculogram signal acquisition module is used for acquiring electro-oculogram signals when a user intends to blink; then the signal is sent to the controller, and the signal is identified and converted into a control instruction; and finally, the instruction is sent to the household appliance and the wheelchair to complete specified actions. In the process, the man-machine interaction module feeds back the current operation step and the operation state in real time. The barrier-aiding activity platform can help people with body height disorder and perfect brain, sends instructions to household appliances and wheelchairs through eye actions of the eye electric collection device, completes daily activities such as moving indoors and controlling the household appliances, meets the daily life and indoor activity requirements of the people, and can powerfully relieve the pressure of taking care of patients of this kind of families.