Abstract: Providing an indication of a state of awareness for a patient includes a receiver configured to acquire an EEG signal; a first bandpass filter coupled with the receiver and configured to filter the EEG signal to generate a first signal in a first frequency band; and a second bandpass filter coupled with the receiver and configured to filter the EEG signal to generate a second signal in a second frequency band. Also included are a mixer coupled with the first and second bandpass filters and configured to combine the first signal and the second signal to produce a combined signal; and a visual display screen configured to display the combined signal.

Abstract: A computer system for acquiring a control command. The system includes one or more processors in communication with non-transitory data storage media having instructions stored thereon that, when executed by the one or more processors, configure the one or more processors to perform particular steps. The steps include: receiving, at an electroencephalogram (EEG) receiver, baseline EEG data; and acquiring, using a normalisation module, one or more normalisation factors from the baseline EEG data. The steps further include: receiving, at the EEG receiver, stimulated EEG data sensed by one or more EEG sensors; and correlating the stimulated EEG data across the one or more EEG sensors, using a correlation module, to generate one or more correlation coefficients corresponding to one or more stimulation frequencies, each of the one or more stimulation frequencies corresponding to a respective candidate control command.

Abstract: An automatic brake control apparatus controls a braking device of a vehicle to execute a brake operation at a brake operating timing. The automatic brake control apparatus includes a brain activity state acquirer unit configured to acquire an activity state of a brain of a driver of the vehicle; a change determiner unit configured to use the activity state of the brain of the driver acquired after the braking device has executed a brake operation at a brake operating timing to determine whether changing the brake operating timing is necessary or unnecessary; and a change controller configured to change the brake operating timing in response to that changing the brake operating timing is determined to be necessary.

Abstract: A three-dimensional neural probe electrode array system is described. Planar probes are microfabricated and electrically connected to flexible micro-machined ribbon cables using a rivet bonding technique. The distal end of each cable is connected to a probe with the proximal end of the cable being customized for connection to a printed circuit board. Final assembly consists of combining multiple such assemblies into a single structure. Each of the two-dimensional neural probe arrays is positioned into a micro-machined platform that provides mechanical support and alignment for each array. Lastly, a micro-machined cap is placed on top of each neural electrode probe and cable assembly to protect them from damage during shipping and subsequent use. The cap provides a relatively planar surface for attachment of a computer controlled inserter for precise insertion into the tissue.

Abstract: Systems and methods are described for super-resolving electromagnetic localization by obtaining electric field data and/or magnetic field data captured over a period of time by at least one multi-channel recording device having a first resolution, applying holographic backpropagation constrained by sparsity approximation and/or low-rank approximation in a near-field and/or a far-field to the captured data, reconstructing electromagnetic energy flow information at a second resolution in one iteration, the second resolution being higher than the first resolution in at least two of three spatial dimensions, and generating data indicating an energy source location, an energy sink location, and/or a causality relation based on the electromagnetic energy flow information at the second resolution.

Abstract: A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person is disclosed. The system includes an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person. The electromagnetic signals include a time component and a frequency component. A monitor monitors a response of the person to a stimulus and a characteristic of the stimulus. A synchronization module synchronizes the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response and the characteristic. A processor processes the set of electromagnetic signals and extracts feature vectors. The feature vectors define a class of behavioral intent. The processor determines the behavioral intent of the person based on the feature vectors. A brain machine interface and a method for identifying a behavioral intent of a person is also disclosed.

Abstract: A mobile device is programmed with an application that uses the mobile device's camera, accelerometer and microphone to enable a parent, coach or player to use it as a tool to diagnose a concussion. The tool may diagnose concussion on the basis of one or multiple factors that are scored, for example the player's balance, eye movement, speech responses to questions, button pressing response time, and other information about the location of the impact. A mobile device may be equipped with speech recognition and voice prompting to enable a concussion examination of a player to be administered by another player or coach to the injured player without significant effort by the injured player or helper. Each test may be scored, by itself or against one or more baselines for the injured player to develop an overall score and likelihood of a concussion. When the coach thinks there is a concussion, he/she can use the application to help find a doctor.

Abstract: The disclosure relates to an automatic brain-probe guidance systems. Specifically, the disclosure is directed to a real-time method and system for guiding a probe to the dorsolateral oscillatory region of the subthalamic nucleus in the brain of a subject in need thereof using factored Partially Observable Markov Decision Process (POMDP) via Hidden Markov Model (HMM) represented as a dynamic Bayesian Network (DBN).

Abstract: A method, comprising detecting, in at least a first brain region of a patient, an electrical activity relating to an epileptic activity; determining a first regularity index of said electrical activity; and applying at least one first electrical stimulation to at least one neural target of said patient for treating said epileptic event, in response to said first regularity index being within a first range. A non-transitive, computer-readable storage device for storing instructions that, when executed by a processor, perform the method. A medical device system suitable for use in the method.

Abstract: Systems and methods are provided for identifying, monitoring, and treating migraines and migraineurs. An electroencephalogram (EEG) of a patient is obtained. The EEG comprises a plurality of EEG signals. At least two features are extracted of a network feature across at least one pair of the plurality of EEG signals in the alpha frequency band, a feature derived from a signal decomposition of at least one EEG signal, and a feature representing the power spectrum density of at least one EEG signal. The patient is classified into one of a plurality of classes, each representing one of the presence of migraine symptoms, a response to migraine treatment, a type of migraineur, a current stage of a migraine, and a likelihood that the patient is a migraineur, according to the extracted at least two features.

Abstract: A brain wave measuring device includes a first brain wave measuring unit that contacts an ear of a user, a second brain wave measuring unit, joined to the first brain wave measuring unit, that contacts the ear, and a transmitter that transmits a brain wave measurement result obtained by the first brain wave measuring unit and the second brain wave measuring unit to a terminal device.

Abstract: The system and methods described herein determine a subject's indication of attention to a first and a second sensory stimuli. The system determines a sensory evoked response of the subject by calculating the statistical relationship between the subject's neural response to the stimuli and a signal feature of the first and the second sensory stimuli. A magnitude value of the sensory evoked response is extracted to determine whether the subject attended-to or ignored the sensory stimuli. The system will select the stimuli that elicited the greater indication of attention, and then trigger further processing by a computer. Such processing can include selecting future content for improving safety warnings, educational materials, or advertisements or further processing can include controlling and navigating a brain computer user interface.

Abstract: A method for analyzing electroencephalogram (EEG) signals is disclosed. EEG signals are received from a sensor coupled to a user. Contextual information from one or both of the user and the user's environment is also received. The EEG signals are processed in real time using a machine learning model to predict an action of the user, which is associated with the contextual information. Output associated with the predicted action is then generated.

Abstract: Systems and methods for treating a subject with a psychiatric disorder are provided in which a therapy session is conducted. In the therapy session, each respective expression image in a plurality of expression images is sequentially displayed. Each expression image is independently associated with an expression. The successive display of images is construed as a tiled series of expression image subsets, each consisting of N expression images. Upon completion of the display of each respective subset, the user is challenged as to whether the first and the last images in the respective subset exhibit the same emotion. A score is determined for the respective subset based on whether the subject learned to respond correctly. The number of images in each subset is adjusted to a new number based on these scores. A treatment regimen is prescribed to the subject for the psychiatric disorder based at least in part on the scores.

Abstract: Provided in the present disclosure are a wireless scene identification apparatus and method for performing identification on the scene category of a predetermined wireless scene, and a wireless communication device and system. The wireless scene identification apparatus comprises: a processing circuit, configured to classify, on the basis of features extracted from environment parameters in a predetermined wireless scene, wireless channel conditions of wireless signals in the predetermined wireless scene by means of a plurality of trained classifiers, and perform decision fusion on the classification results of the plurality of classifiers, so as to classify the wireless channel conditions as wireless channel conditions in the predetermined plurality of wireless channel conditions.

Abstract: A system and method are presented for use in monitoring brain activity of a subject. The system comprises a control unit which comprises: a data input utility for receiving measured data comprising data corresponding to signals measured during a certain time period and being indicative of a subject's brain activity originated from locations in the subject's brain during said certain time period, and a processor utility which is configured and operable for processing the measured data and generating data indicative thereof in the form of a multi-parameter function presenting a relation between frequency and time data of the measured signals and for analyzing said relation and identifying a subject-related signature corresponding to the subject's brain neural activity.

Abstract: Apparatus, system, and computer readable media determine the probability of visual recognition of an image by a subject using electroencephalography (EEG) corresponding to a Visual Evoked Potential (VEP). The apparatus comprises means for presenting a series of visual stimuli corresponding to said image to evoke EEG signals. The visual stimuli of the image are presented in an orientation sequence based on a timing cycle. At least one prism is provided for placement in front of the series of visual stimuli corresponding to said image. The EEG signals evoked in response to said visual stimuli and said prism placed in front of said visual stimuli are recorded and processed by a processor. VEP is generated corresponding to the presence of a shift and thereby provides object statistic reliability of the visual recognition of the image by the subject.

Abstract: Provided are prefrontal-based brain-machine interfacing apparatus and a method thereof.

Abstract: The invention proposes an In-situ Sensor (1) for being implanted within tissue of a mammal (P) comprising •an energy harvesting portion (RX), •a communication portion (TX), •a pressure sensor (SP) for measuring interstitial pressure of surrounding tissue when located within tissue, •a further sensor (SF), whereby the further sensor is selected from a group comprising pH sensor, lactate sensor, impedance sensor, radiation sensor, temperature sensor, sensor for bioelectrical potentials, •whereby said further sensor (SF), said pressure sensor (SP) as well as the communication portion (TX) are powered by the energy harvesting portion (RX), •whereby information indicative of the measurement provided by the pressure sensor (SP) and data indicative of the measurement provided by said further sensor (SF) is communicated via said communication portion (TX) towards an extracorporeal receiving entity (ECE), •whereby said communication portion (TX) and/or said pressure sensor (SP) and/or said further sensor (SF) are adap

Abstract: A system may detect silent, internal articulation of words by a human user, by measuring low-voltage electrical signals at electrodes positioned on a user's skin. The measured signals may have been generated by neural activation of speech articulator muscles during the internal articulation. The system may detect the content of internally articulated words even though the internal articulation may be silent, may occur even when the user is not exhaling, and may occur without muscle movement that is detectable by another person. The system may react in real-time to this detected content. In some cases, the system reacts by providing audio feedback to the user via an earphone or a bone conduction transducer. In other cases, the system reacts by controlling another device, such as a luminaire or television. In other cases, the system reacts by sending a message to a device associated with another person.

Abstract: Systems, methods, and apparatus are described that employ a fast concussion model usable to detect occurrence of traumatic events that can contribute to mild traumatic brain injury (mTBI) and to assess the risk that mTBI has occurred or is likely to occur should further traumatic events occur. A method includes receiving motion data related to a head acceleration event from sensors configured to detect head motion of a subject, using the motion data to obtain an estimate of axon signal dysfunction affecting a component of the subject's brain as a result of the head acceleration event, determining a Neurologic Injury Measure (NIM) from the estimate of axon signal dysfunction, and generating a probability that the subject has been concussed by the head acceleration event based on the NIM. The estimate of axon signal dysfunction may be based on strain at nodes of Ranvier in the component of the subject's brain.

Abstract: A method for calibrating and executing a rehabilitation exercise for a stroke-affected limb of a stroke patient is disclosed, the method comprising the steps of providing a haptic device for an able limb of the stroke patient to manipulate to perform a calibration action to result in a first position of the haptic device, and providing the haptic device for the stroke-affected limb to manipulate to perform the calibration action to result in a second position of the haptic device. The method further comprises the steps of moving the haptic device coupled with the stroke-affected limb from the second position towards the first position until a predetermined counterforce is detected, indicating an extreme position for the stroke-affected limb using the haptic device, and calibrating the haptic device with the extreme position such that during the rehabilitation exercise, the haptic device is prevented from moving beyond the extreme position.

Abstract: A system includes a controllable device configured to provide a premises related service in an area. The system includes a neural device to be positioned with respect to a part of a body of a user and circuitry to process nerve signals detected in real-time. The system also includes a processor in communication with the circuitry, a memory and instructions stored in the memory for execution by the processor. Data stored in the memory associates each of some number of predetermined sets of nerve signals with a control instruction. Execution of the instructions configures the processor to use the stored data to analyze the real-time detected nerve signals to determine when real-time detected nerve signals correspond to one of the predetermined sets of nerve signals and generate a control data signal based on the associated control instruction to cause a controller to control an operation of the controllable device.

Abstract: Techniques are disclosed for defining a homeostatic window for controlling delivery of electrical stimulation therapy to a patient. In one example, a method includes generating and delivering electrical stimulation therapy to tissue of a patient via electrodes. Further, the method includes adjusting a level of a parameter of the electrical stimulation therapy such that a signal of the patient is not less than a lower bound and not greater than an upper bound. The lower bound is determined to be the magnitude of the signal while receiving electrical stimulation therapy sufficient to reduce one or more symptoms of a disease while the patient was receiving medication for reduction of the one or more symptoms. Further, the upper bound is determined to be the magnitude of the signal while receiving electrical stimulation therapy sufficient to reduce the one or more symptoms when the patient was not receiving the medication.

Abstract: A system and method of steady-state visual evoked potential (SSVEP) frequency detection using bio-inspired filter banks (BIFB) includes, acquiring electroencephalographic (EEG) signals from a subject in response to a repetitive visual stimulus, estimating the power spectral density (PSD) of the channel of the EEG signals including at least one SSVEP response, extracting one or more SSVEP response features from the estimated PSD of the channel using a bio-inspired filter bank (BIFB) and classifying the extracted SSVEP response features to determine if the detected SSVEP response frequency from the EEG signals acquired from the subject substantially matches the repetition frequency of the repetitive visual stimulus.

Abstract: Various methods and systems are provided for cerebral diagnosis. In one example, among others, a method includes obtaining EEG signals from sensors positioned on a subject; conditioning data from the EEG signals to remove artifacts; generating a cerebral network model based at least in part upon the conditioned data; determining network features based upon the cerebral network model; and determining a cerebral condition of the subject based at least in part upon the network features. In another example, a method includes determining a recording condition of a positioned EEG sensor and providing an indication of an unacceptable recording condition of the EEG sensor. In another example, a system includes an EEG recording module to acquire signals; a signal conditioning module to condition signal data; a signal analysis module to determine signal features and cerebral network features; and a condition classification module to determine a cerebral condition of the subject.

Abstract: Systems and methods for sonifying electrical signals obtained from a living subject, particularly EEG signals, are disclosed. A time-domain signal representing the activity of an organ is obtained. A voltage of the time-domain signal over a time block is determined. An acoustic signal based on the time-domain signal over the time block is produced. The acoustic signal comprises one or more audibly discernible variations representative of the activity of the organ. If the determined voltage is over a threshold voltage, the time-domain signal is squelched over at least a portion of the time-block as the acoustic signal is produced. The time-domain signal can be squelched by ramping down the signal as an input to produce the acoustic signal. The frequency spectrum of the acoustic signal can also be adjusted as it is produced, such as by flattening the signal and/or attenuating high frequencies along the frequency spectrum of the signal.

Abstract: The object is to acquire electroencephalogram of high resolution with fewer number of electrodes than usual. An electroencephalogram measurement apparatus comprising: a plurality of electrodes 110 attached on the scalp of a subject for acquisition of electroencephalogram signals of the subject; and an electroencephalogram generation unit 150 for generating an electroencephalograms at locations of the scalp where the electrodes are attached and electroencephalograms at locations of the scalp where the electrodes are not attached.

Abstract: A human-machine interaction method based on visual stimulations. The method can be applied to multiple new technical fields of display, which comprise but are not limited to the fields of virtual reality (VR), augmented reality (AR), mixed reality (MR), holographic projection and glasses-free 3D. The system consists of three parts: a human body biological collection apparatus, a software client for human-machine interaction and a display terminal. Input ports of the software client are connected to a human body physiological signal collection device (in a wired or wireless manner); a user wears the collection device, and communication ports of the client are respectively connected to communication ports of a display module by means of a multichannel communication module. Firstly, the system is initialized, and then starts to run based on a control method of visual stimulations (an object flicker or distortion).

Abstract: To efficiently assess, prioritize, and re-assess individuals respectively for intervention OR for ongoing programs/activities OR for personalized rehabilitation or training activities: A Computerized Interactive Psychological Assessment Protocol including the steps of: using a predetermined interactive media, interfacing with a client, (A) accepting some predetermined goal-relevant self-assessment responses from the client, regarding the client's respective motivation, belief, know-how, state-of-mind, activity, etc.

Abstract: A “Predictive Controller” operates with any type of controller or user input device to predict user inputs or responses to a current state of an application. A predictive model of the current state of the application is applied to prior user inputs to jointly predict a current user-specific psychological state or profile of the user and a predicted next user response or input. The predicted response or input is provided as the user input to the particular application prior to receiving the actual user input, thereby reducing latency of the response of the application to that actual user input. In addition, a tangible feedback corresponding to the predicted next user input is provided. Further, the predictive capabilities of the Predictive Controller can be applied to locally or remotely hosted instances of the application to reduce latencies associated with user inputs received from any type of controller or user input device.

Abstract: System and method for evaluating a cognitive load on a user, corresponding to a stimulus is disclosed. Electroencephalogram (EEG) data corresponding to the stimulus of a user is received. The stimulus corresponds to a mental task performed by the user. The EEG data is split into a plurality of slots. A slot of the plurality of slots comprises a subset of the EEG data. One or more EEG features are extracted from the subset of the EEG data. The one or more EEG features are represented in one of a frequency domain and a time domain. A plurality of data points present in the one or more EEG features is grouped into two or more clusters using an unsupervised learning technique. The two or more clusters comprise one or more data points of the plurality of data points. The one or more data points correspond to a level of the cognitive load.

Abstract: The present application discloses various methods and apparatuses for determining a head movement, wherein a method for determining a head movement disclosed comprises: acquiring, in response to a head movement of a human body, brain electricity detection information of a human body; and determining the head movement corresponding to the brain electricity detection information. The present application provides a new solution for head movement recognition, by which accuracy of head movement recognition is improved.

Abstract: The present invention is directed to a method of continuously monitoring neuronal avalanches in a subject comprising (a) determining a deviation in avalanche exponent (?) or branching parameter (?) from a predetermined value at rest, wherein the pre-determined value of ? is a slope of a size distribution of the synchronized neuronal activity and the predetermined value is ?3/2 and the pre-determined value of ? is a ratio of successively propagated synchronized neuronal activity and the predetermined value is 1; and (b) repeating step (a) one or more times to continuously monitor neuronal avalanches in a subject. The invention also features methods of determining or monitoring the degree of sleep deprivation in a subject, methods of identifying subjects that are susceptible to a sleep disorder and methods of diagnosing a sleep disorder in a subject.

Abstract: A device and method for user authentication. The device for authentication includes an extraction unit configured to extract a signal feature of a brainwave signal of a user to be authenticated and a comparison unit configured to compare the signal feature with a signal feature sample pre-stored in a feature library on an individual basis. When there a signal feature sample is matched with the signal feature, the device retrieves account information and a password of the user according to the matched signal feature sample. The device for authentication further includes a response unit configured to respond to a request of the user according to the account information and the password. The present disclosure can improve the security and convenience of user authentication.

Abstract: Computer-implemented methods and automated systems for real-time detection of spreading depolarizations in a brain injured patient, based an algorithm of (a) providing a reference data base of spreading depolarization waveform templates generated from EEG recordings of confirmed spreading depolarizations (SD) in a reference brain-injured patient cohort; (b) recording an EEG of the brain injured patient to generate recorded EEG waveforms; (c) detecting a slow potential change present in a recorded EEG waveform by applying a power spectral density estimate to the recorded waveform; (d) comparing a detected SPC to a reference database of SD waveform template to identify a candidate SD; and (e) rejecting a candidate SD as a false positive based on overall signal power and amplitude analysis and identifying a non-rejected candidate SD as a detected SD.

Abstract: An electronic device may include an EMG sensor to be coupled to a user. The electronic device may include a control device configured to generate a control output based upon a control input and to change a scaling between the control input and the control output based upon the EMG sensor. The EMG sensor may include a pair of EMG sensors, with each EMG sensor being associated with a respective one of opposing muscles of the user.

Abstract: A system for clinical decision support includes a database of previously-recorded waveform data from comparator-patients and a comparator module. The comparator module receives physiological waveform data for a patient and identifies a pattern in the patient's physiological waveform data, wherein the pattern accounts for a morphology and a rhythm of the patient's physiological waveform. The comparator module then compares the patient's physiological waveform data to the previously-recorded waveform data using a pattern recognition algorithm to detect the pattern in the previously-recorded waveform data to identify one or more matches. The comparator module further generates a result set based on the one or more matches.

Abstract: An isolation circuit and a method for providing isolation between two dies are provided. The isolation circuit includes: an isolation module, configured to generate an isolation signal based on an input signal from a first die and to provide isolation between the first die and a second die, where the isolation signal is smaller than the input signal in amplitude, and the first die is coupled with the second die; a latch module, configured to latch the isolation signal at a certain level and output a latched signal; an amplifier module, configured to amplify the latched signal. In the isolation circuit, a modulation module and a demodulation module can be saved.

Abstract: Provided are methods to measure and or monitor consciousness in a subject, including analyzing brain activity with weighted symbolic mutual information (wSMI) and/or Kolgomorov symbolic complexity (KSC). In addition, methods and apparatus to administer a stimulus and/or a medicament to a subject according to their consciousness level which has been determined using the method described herein are also provided.

Abstract: A motion tracking system monitors the motions performed by a user based on motion data received from one or more sensors. The motion tracking system may include a motion tracking device with one or more sensors, a smart device with one or more sensors and/or a server. As the user interacts with the motion tracking system or smart device the motion data generated by one or more sensors is processed by a software application. The software application generates interpreted data based on the motion data and contextual data such as the equipment being used by the user. Feedback is then provided to the user during and/or after the user has performed a motion or a set of motions. The feedback provided to the user may be visual, audio or tactile. The application may be used to monitor a routine in a sporting, fitness, industrial or medical environment, for example.

Abstract: The invention comprises methods and systems capable of processing simultaneously measured cardiac and motion signals, selecting from said signals the optimal cardiac and motion signal combination for cross spectral density calculations and, hereafter, itemizing the shared information in terms of the individual constituent frequencies and the effect exerted upon said frequencies by common underlying physiological states. The information is passed through a classifier, where said information is used to quantify the underlying physiological states, exemplified by but not limited to, sleep stage, quality and/or disorders that affect sleep stability. Inferences made by the methods described, for example, can be employed to aid home based sleep analysis and automated screening of patients with sleep disorders.

Abstract: Neuromodulation systems are described. An example neuromodulation system includes a controller wirelessly communicatively coupled to a host computer, a signal generator communicatively coupled to the controller, and a plurality of electrodes communicatively coupled to the signal generator. The controller, in conjunction with the signal generator and the at least one electrode are configured to deliver a stimulation to a mammal based on an instruction received from the host computer. The stimulation is configured to induce voluntary movement or restore function in the mammal.

Abstract: Provided is a stroke monitoring system capable of measuring a user's biometric signal including an electroencephalogram using a device such as a wearable device for determining whether a user has a stroke for 24 hours, building a database of the measured user's biometric signal and other information, and predicting an occurrence of a user's stroke.

Abstract: A data synchronization method includes: receiving time interval information sent by a second terminal device, where the time interval information includes a synchronization start time and a synchronization end time; obtaining, in stored waking and sleep time information, a time period set that is greater than or equal to the synchronization start time and that is less than or equal to the synchronization end time, where the time period set includes at least one sleep time period; determining, in the time period set, a sleep time period whose sleep duration is greater than a preset threshold; and sending, to the second terminal device, feature data collected in the determined sleep time period.

Abstract: Systems and methods for analyzing electrophysiological signals acquired from a subject are provided. In some aspects, a method includes receiving electrophysiological signals acquired from a subject using one or more sensors, and assembling a set of time-series data using the acquired electrophysiological signals. The method also includes analyzing the set of time-series data using a state-space multi-taper framework to generate spectral information describing the electrophysiological signals, and determining a brain state of the subject using the spectral information. The method further includes generating a report indicative of the determined brain state.

Abstract: Provided are systems and methods for medical diagnosis. The systems and methods may identify a coherence between paired sensor data respectively measured from a first sensor attached to a head of a subject and a second sensor attached to a body part of the subject. The systems and methods may determine an amount of volition in the subject's body based on the coherence. The systems and methods may determine a diagnosis or a treatment plan for a subject based on the amount of volition. The system and methods may be used to track interaction between individuals in a clinical setting or in a social group.

Abstract: Disclosed is a method for computerizing delineation and/or multi-label classification of an ECG signal, including: applying a neural network to the ECG, labelling the ECG, and optionally displaying the labels according to time with the ECG signal.

Abstract: A method and apparatus which combines multiple simultaneous signals thought to contain a common periodic component by performing principal component analysis on each of the multiple signals, finding the weight of the first principal component, and then adding the multiple signals together in a weighted sum according to the weight of the first principal component. The method and apparatus further includes a way of combining signals from successive overlapping time windows in real time by differentiating the signal and forming as each output signal sample the value of the preceding signal sample summed with the differential of the signal, weighted by weights based on the amplitude of the differential signal at that time point.

Abstract: This invention, which focuses on personality and aptitude matching by psychophysiologic response to stimuli, is referred to as Brain Matching. In general terms, this invention starts by selecting highly specialized skill sets and top performer group for each skill set. The various groups are analyzed though psychophysiologic stimuli testing by using basically the same testing consisting of large numbers stimuli tests in a consistent testing environment. Stimuli tests can range from hundreds to thousands of images each producing a brainwave response. Neural Networks, Artificial Intelligence, Deep Learning computers look at the test results, highly specialized group by other highly specialized group to reduce the groups signature/response commonality into a template. Test subjects are then tested using the same stimuli. The subject's test results are analyzed for correlation with the various specialized expert groups.