1868 results about "Brain waves" patented technology

A noise-free portable EEG system is provided. The system has hardware and software and can evaluate mental state quantitatively. The quantitative data of mental states and their levels can be applied to various areas of brain-machine interface including consumer products, video game, toys, military and aerospace as well as biofeedback or neurofeedback.

A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided. The system includes an intelligent bio-signal processing system that is operable to: capture bio-signal data and in addition optionally non-bio-signal data; and analyze the bio-signal data and non-bio-signal data, if any, so as to: extract one or more features related to at least one individual interacting with the biofeedback computer system; classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems. A number of additional system and computer implemented method features are also provided.

There is presented a reliable technique for measuring condition change in nonlinear data such as brain waves. The nonlinear data is filtered and discretized into windowed data sets. The system dynamics within each data set is represented by a sequence of connected phase-space points, and for each data set a distribution function is derived. New metrics are introduced that evaluate the distance between distribution functions. The metrics are properly renormalized to provide robust and sensitive relative measures of condition change. As an example, these measures can be used on EEG data, to provide timely discrimination between normal, preseizure, seizure, and post-seizure states in epileptic patients. Apparatus utilizing hardware or software to perform the method and provide an indicative output is also disclosed.

The labor involved in cleaning for each examination is reduced, the examination can be carried out hygienically, and the convenience of use is improved. An electrode apparatus for detecting brain waves which is arranged in contact with the scalp and which detects brain wave signals is provided. The electrode apparatus for detecting brain waves comprises a rod-shaped electrode apparatus main body having an electrode disposed at the tip thereof, a cap which is mountable on the tip of the electrode apparatus main body and which has an elastic member which contains an electrolyte and which is disposed making close contact so as to cover the electrode, and a connection means which detachably connects the cap to the electrode apparatus main body.

Method and apparatus for determining the state of entrainment between biological systems which exhibit oscillatory behavior such as heart rhythms, respiration, blood pressure waves and low frequency brain waves based on a determination of heart rate variability (HRV) and an evaluation of the power spectrum thereof. Entrainment reflects a harmonious balance between the two branches of the autonomic nervous system within the body. This internal state of heightened physiological efficiency enhances health and promotes optimal performance. According to one embodiment a method is used to determine the entrainment level based on an entrainment parameter related to HRV. The method first determines the power distribution spectrum (PSD) and then calculates an entrainment parameter (EP), which is a measure of the power distribution in the HRV spectrum. High EP values occur when this power is concentrated within a relatively narrow range of frequencies, and lower values when the power is distributed over a broader range of frequencies. In one embodiment, an apparatus is provided for monitoring the heart beat and presenting this information via a personal computer, handheld device, or other processing means.

A method of detecting pain in a subject, comprises the steps of generating brain wave data based on brain wave activity of the subject and comparing the brain wave data to reference data to generate result data, the reference data corresponding to at least one of (i) population normative data indicative of brain wave activity of a first plurality of individuals in an absence of pain, (ii) population reference data indicative of brain wave activity of a second plurality of individuals generated in response to pain events inflicted on the second plurality of individuals, (iii) subjective population reference data indicative of brain wave activity of a third plurality of individuals reporting a sensation of pain, and (iv) population of reference data indicative of brain wave activity of a fourth population of individuals following an intervention which has changed a subjective report of pain in combination with determining a presence of pain experienced by the subject as a function of the result data.

A system and method for calculating an engagement value by quantifying an amount that a user is acting without thinking considering brainwaves and a heart rate can be used to compare media based on an individual or a group of individuals. Events of the media can be contrasted and compared by the engagement value as well. Statistical measurements may be taken to improve media.

A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided. The system includes an intelligent bio-signal processing system that is operable to: capture bio-signal data and in addition optionally non-bio-signal data; and analyze the bio-signal data and non-bio-signal data, if any, so as to: extract one or more features related to at least one individual interacting with the biofeedback computer system; classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems. A number of additional system and computer implemented method features are also provided.

The invention provides a brain wave analysis method. The method uses classical time-frequency domain analysis and principal component analysis methods to solve the problem of electroencephalographic feature extraction, successfully extracts time-frequency domain parameters closely related to the tension, fatigue and relaxation of human bodies, maps the time-frequency domain parameters into principal component space, and uses a support vector machine to efficiently analyze non-linear relation in the principal component space so as to improve the accuracy and validity of interpretation.

A method and apparatus to monitor the neurologic state of a patient undergoing general anesthesia is provided. Previous automated systems to monitor the neurologic state of a patient undergoing general anesthesia involve a significant time delay between the patient's true hypnotic state and the computed indices. The present invention reduces this time delay by using a different analysis technique applied to spontaneous EEG. A wavelet decomposition and statistical analysis of the observed EEG is conducted and compared to reference data to provide a numerical indicator. In addition, this indicator is more consistent with the patient's loss of consciousness indicated by the loss of count event than previous systems.

Methods and devices are provided for monitoring and manipulating a person's brainwaves to achieve a desired mental state. A method of improving a student's test-taking ability includes analyzing EEG data to determine a student's focus level during an exam and providing a suggestion to the student for improving the student's focus level. A method of manipulating brain activity includes measuring a listener's brainwave frequency and providing binaural beats to the listener to guide the listener to a desired mental state. The binaural beats may be incorporated into music in such a way that they may not be distinguished over the music. A portable apparatus includes EEG electrodes connected to earphones with malleable wire that facilitates preferential placement and stability on a user's scalp.

Method and apparatus for determining the state of entrainment between biological systems which exhibit oscillatory behavior such as heart rhythms, respiration, blood pressure waves and low frequency brain waves based on a determination of heart rate variability (HRV) and an evaluation of the power spectrum thereof. Entrainment reflects a harmonious balance between the two branches of the autonomic nervous system within the body. This internal state of heightened physiological efficiency enhances health and promotes optimal performance. According to one embodiment a method is used to determine the entrainment level based on an entrainment parameter related to HRV, The method first determines the power distribution spectrum (PSD) and then calculates an entrainment parameter (EP), which is a measure of the power distribution in the HRV spectrum. High EP values occur when this power is concentrated within a relatively narrow range of frequencies, and lower values when the power is distributed over a broader range of frequencies. In one embodiment, an apparatus is provided for monitoring the heart beat and presenting this information via a personal computer, handheld device, or other processing means.

Provided is a configuration capable of executing a detection test for a comfort level including the quality of sleep, which is measurable at home without requiring the measurement of brain waves or electrocardiogram. The respiratory waveform of a subject during sleep is continuously measured and recorded from the respiratory gas flow, etc., and is window-Fourier transformed at each measurement time to generate a frequency spectrum, and a bandwidth including a respiratory frequency is extracted. The index indicating the regularity of the respiratory period of the subject is also calculated at each time point during the sleep, and the time-dependency of this index during the sleep is represented as a graph. A medical device includes a sleep evaluation system equipped with a control means for performing control so that a sleep cycle repeated at a cycle of about 90 minutes is clearly observed if the comfort level including the quality of sleep of the subject is favorable.

The invention relates to an intelligent insomnia therapeutic instrument, aiming at providing a therapeutic instrument which can induce and regulate potential action of the sleep center of a patient so as to accelerate the falling asleep speed of the patient and improve the sleep quality or realize a natural timing awaking function. The technical proposal is as follows: the instrument comprises a signal output module generating time varying magnetic fields, a bipolar electrode brain wave acquiring module acquiring real-time brain waves of the patient and a main controller obtaining the brain waves and carrying out down-conversion or up-conversion, wherein the signal output module converts digital brain signals output by the main controller into analogue signals which are amplified so as to drive a magnetic field generator to generate time varying magnetic fields used for treating.

A method and system for analyzing the status of a subject. A cordless recording device comprising a set of electrodes is attached on the forehead of the subject to collect brain wave signal data from the subject. Based on the brain wave signal data, status information indicative of the status of the subject during a measurement period is generated. A bioimpedance signal is further measured through two electrodes of the electrode set and heart rate data is derived from the bioimpedance signal. The heart rate data is utilized to enhance the quality of the status information, which is typically sleep state information. The invention also relates to a recording device attachable to the forehead of the subject. The recording may comprise a data memory for storing the data measured from the subject during the measurement period.

Method and apparatus for determining the state of entrainment between biological systems which exhibit oscillatory behavior such as heart rhythms, respiration, blood pressure waves and low frequency brain waves based on a determination of heart rate variability (HRV) and an evaluation of the power spectrum thereof. Entrainment reflects a harmonious balance between the two branches of the autonomic nervous system within the body. This internal state of heightened physiological efficiency enhances health and promotes optimal performance. According to one embodiment a method is used to determine the entrainment level based on an entrainment parameter related to HRV, The method first determines the power distribution spectrum (PSD) and then calculates an entrainment parameter (EP), which is a measure of the power distribution in the HRV spectrum. High EP values occur when this power is concentrated within a relatively narrow range of frequencies, and lower values when the power is distributed over a broader range of frequencies. In one embodiment, an apparatus is provided for monitoring the heart beat and presenting this information via a personal computer, handheld device, or other processing means.

A noninvasive brain computer interface (BCI) system includes an electroencephalography (EEG) electrode array configured to acquire EEG signals generated by a subject. The subject observes movement of a stimulus. A computer is coupled to the EEG electrode array and configured to collected and process the acquired EEG signals. A decoding algorithm is used that analyzes low-frequency (delta band) brain waves in the time domain to continuously decode neural activity associated with the observed movement.

A method for monitoring anesthetization of a patient, includes the steps of removably connecting a plurality of electrodes to the scalp of the patient and administering sufficient anesthesia to the patient so that the patient attains a plane of anesthesia selected by an operator. The brain waves of the patient are then amplified and digitized after the patient has been anesthetized, before beginning the medical procedure, to obtain a first set of digital data. The brain waves of the patient are then amplified and digitized during the medical procedure to provide a second set of digital data and the first and second sets of digital data are analyzed in at least one of a time domain and a frequency domain. Separate trajectories are then computed from the data analysis trajectories for at least two different indices of an anesthetic state of the patient during the medical procedure, the indices being selected from a group including a Depth Index (DI), a Memory Index (MI) and a Pain Index (PI). A system for providing anesthesia to a patient, includes a plurality of electrodes, a first arrangement allowing an operator to administer anesthesia to the patient until the patient has attained a selected plane of anesthesia and a second arrangement coupled to the electrodes for amplifying and digitizing brain waves of the patient after the patient has been anesthetized, before the medical procedure has been begun to obtain a first set of digital data, the second arrangement amplifying and digitizing ongoing brain waves of the patient during the medical procedure to provide a second set of digital data in combination with a third arrangement analyzing the first and second sets of digital data in at least one of a time domain and a frequency domain, a fourth arrangement computing from the data analysis separate trajectories for at least two different indices of a state of the patient during the medical procedure, the indices being selected from a group including a Depth Index (DI), a Memory Index (MI) and a Pain Index (PI), a fifth arrangement providing control signals when any of the trajectories indicates that the patient is deviating from the selected plane of anesthesia and a sixth arrangement automatically adjusting two different anesthetic agents administered to the patient based on the control signal to restore the patient to the selected plane of anesthesia.

An apparatus and method are provided for analyzing information relating to the physiological and psychological conditions of a driver. Psychological conditions such as comfortableness or degree of alertness are estimated on the basis of physical data such as fluctuation in brain waves. This apparatus comprises a first neural network having a pre-processed 1 / f fluctuation signal for brain waves as an input and for estimating a degree of alertness of the driver, and a second neural network receiving the estimated degree of alertness and the pre-processed 1 / f fluctuation signal, for estimating and outputting driving comfortableness. By employing a neural network, which has a mapping ability as well as flexible adaptability even for non-linear data, based on the learning function, more accurate estimation of mental conditions can be achieved in comparison with conventional statistical analysis.

A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided. The system includes an intelligent bio-signal processing system that is operable to: capture bio-signal data and in addition optionally non-bio-signal data; and analyze the bio-signal data and non-bio-signal data, if any, so as to: extract one or more features related to at least one individual interacting with the biofeedback computer system; classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems. A number of additional system and computer implemented method features are also provided.

A method for changing appearance of EEG or a relationship of brain wave patterns while achieving behavioral changes, the method including individualized assessing of dysregulated patterns of brain function using topographic quantitative electroencephalogram (LORETA [low resolution brain electromagnetic tomography] qEEG) or regular EEG recollection, modifying or priming neuroplasticity with transcranial direct current stimulation (tDCS) or with magnetic or electromagnetic fields to modify cortical excitability of neurons in dysregulated areas, and self-regulating LORETA patterns with neurofeedback to change an appearance of EEG or a relationship of brain wave patterns while achieving behavioral changes.

A method of facilitating a skill learning process or improving performance of a task, comprising: determining a brainwave pattern reflecting neuronal activity of a skilled subject while engaged in a respective skill or task; processing the determined brainwave pattern with at least one automated processor; and subjecting a subject training in the respective skill or task to brain entrainment by a stimulus selected from the group consisting of one or more of a sensory excitation, a peripheral excitation, a transcranial excitation, and a deep brain stimulation, dependent on the processed temporal pattern extracted from brainwaves reflecting neuronal activity of the skilled subject.

To increase intensity of the brain wave signal for detection. Provided is an apparatus for analyzing a brain wave which is installed on a vehicle comprising: a detection unit for detecting the brain wave signal, and separating and analyzing the detected brain wave signal; a discrimination unit for generating a control signal according to an intensity of the brain wave signal analyzed by the detection unit; a processing control unit for controlling subsequent processing according to a type of each of the plurality of control signals produced by the discrimination unit; at least one brain wave signal induction unit for generating a graphic inducing a predetermined type of the brain wave; and a display for displaying the generated graphic according to the received signal from the brain wave signal induction unit.

A method modifying a particular electrophysiological feature generated in response to a stimulus is disclosed. The method involves a repeated process of: sampling the brain wave state in order to apply a modifying pulse; modifying the brain wave state to a state more conducive to a required response; sampling the brain wave state in order to apply a response stimulus; applying a stimulus only when the brain wave state substantially meets the preselected response criteria; recording the brain wave activity of the subject subsequent to the application of the stimulus.

The control method for a device includes steps of: presenting a visual stimulation concerning a manipulation menu for a device; measuring event-related potentials after the visual stimulation is presented, where event-related potentials based on a timing of presenting the visual stimulation as a starting point are measured from a potential difference between each of electrodes and at least one reference electrode respectively worn on a face and in an ear periphery of a user; from each of the measured event-related potentials, extracting electroencephalogram data which is at 5 Hz or less and contains a predetermined time section, and combining the extracted electroencephalogram data into electroencephalogram characteristic data; comparing the electroencephalogram characteristic data against reference data prepared in advance for determining a desire to select an item in the manipulation menu; and, based on a comparison result, executing a manipulation of the device corresponding to the item.

The invention discloses a human body fatigue evaluation method based on brain waves. According to the method, a ThinkGearAM electroencephalogram chip is used for acquiring original brain wave signals, an built-in algorithm is used for analyzing and processing the original brain wave signals, and four kinds of parameters are given through calculation according to processed brain wave data; the four kinds of parameters include variable coefficients of five brain wave signals of original delta waves, original theta waves, original alpha waves, original beta waves and original gamma waves, two nonlinear parameters of complexity and power spectral entropy, a fatigue index F worked out through energy of four basic rhythms of the delta waves, the theta waves, the alpha waves and the beta waves in the brain waves, and two parameters of relaxation degree and attention degree extracted through the brain wave signals, and the four kinds of parameters serve as input of a probabilistic neural network (PPN), the output of the PNN serves as a human body fatigue evaluation basis, and therefore the human body fatigue can be judged according to the brain waves of people.

An ear plug (200) comprises a shell (206) with at least two electrodes (201-205) adapted for measuring brain wave signals, said electrodes (201-205) being connected with means for processing the measured signals, wherein the contours of the outer surface of the ear plug (200) and the electrodes (201-205) are individually matched to at least part of the ear canal and the concha of the user. The invention further provides a method for producing an ear plug.

A real-time simultaneous measurement apparatus includes: a hemoglobin information-receiving portion that sequentially receives hemoglobin information, which is information relating to the amount of hemoglobin in a head portion of a test subject, from a NIRS brain-measuring apparatus that receives a synchronization signal output by a synchronization signal output apparatus and acquires the hemoglobin information when the synchronization signal has been received; a brain wave information-receiving portion that sequentially receives the brain wave information of the test subject, from an EEG brain wave-measuring apparatus that receives a synchronization signal output by the synchronization signal output apparatus and acquires the brain wave information when the synchronization signal has been received; a synchronization processing portion that performs processing that synchronizes the hemoglobin information and the brain wave information; and an output portion that outputs the synchronized hemoglobin information and brain wave information.

A hearing aid comprises an amplifier (303, 309, 317), an input transducer (301), an output transducer (824) and a signal processing device (825). The amplifier (303, 309, 317) and the signal processing device (825) are connected. The hearing aid further comprises at least two electrodes (201-205) adapted for detecting electrical signals such as brain waves, the at least two electrodes (201-205) being connected to a differential amplifier (303, 309, 317), which in turn is connected to the signal processing device, and means for modifying the operation of said hearing aid in dependence of the detected signals. The invention further provides a method for adaptation of a hearing aid.