PORTABLE BRAIN ACTIVITY SENSING PLATFORM FOR ASSESSMENT OF VISUAL FIELD DEFICITS

Methods, systems, and devices are disclosed for monitoring electrical signals of the brain. In one aspect, a system for monitoring electrical brain activity associated with visual field of a user includes a sensor unit to acquire electroencephalogram (EEG) signals including a plurality of EEG sensors attached to a casing attachable to the head of a user, a visual display unit attachable to the head of the user over the user's eyes to present visual stimuli, in which the visual stimuli is configured to evoke multifocal steady-state visual-evoked potentials (mfSSVEP) in the EEG signals exhibited by the user acquired by the sensor unit, and a data processing unit in communication with the sensor unit and the visual display unit to analyze the acquired EEG signals and produce an assessment of the user's visual field, in which the assessment indicates if there is a presence of visual field defects in the user's visual field. 1. A system for monitoring brain activity associated with the visual field of a user , comprising:a sensor unit to acquire electroencephalogram (EEG) signals including one or more electrodes attached to a casing wearable on the head of a user;a visual display unit including a display screen to present visual stimuli to the user in a plurality of sectors of a visual field, wherein the presented visual stimuli includes an optical flickering effect at a selected frequency mapped to each sector of the visual field, the visual stimuli configured to evoke multifocal steady-state visual-evoked potentials (mfSSVEP) in the EEG signals exhibited by the user acquired by the sensor unit; anda data processing unit in communication with the sensor unit and the visual display unit to analyze the acquired EEG signals and produce an assessment of the user's visual field.2. The system of claim 1 , wherein the produced assessment of the user's visual field is a quantitative assessment that indicates if there is a presence of a visual field defect in the user's visual ...

NON-INVASIVE CHARACTERIZATION OF A PHYSIOLOGICAL PARAMETER

The present invention provides a method and device for characterizing a physiological parameter. The method, in one application, uses one or more non-invasive sensors to collect patient data, and may also collect data on environmental conditions. At least some of the patient data has a direct relationship with the physiological parameter, that is, a change in the physiological parameter is reflected in the data set, although the magnitude of the physiological parameter may masked by noise, interference, or other environmental or patient influences. The direct patient data preferably has a generally linear relationship with the physiological parameter, and if not, the patient data is linearized according to an algorithm, table, or other adjustment process. These linearizing processes may be predefined, and may adaptively learn or adjust. A blind signal source process is applied to the linearized data to generate separated signals, and the signal associated with the physiological parameter ...

Real-time multi-channel EEG signal processor based on on-line recursive independent component analysis

A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis is provided. A whitening unit generates covariance matrix by computing covariance according to a received sampling signal. A covariance matrix generates a whitening matrix by a computation of an inverse square root matrix calculation unit. An ORICA calculation unit computes the sampling signal and the whitening matrix to obtain a post-whitening sampling signal. The post-whitening sampling signal and an unmixing matrix implement an independent component analysis computation to obtain an independent component data. An ORICA training unit implements training of the unmixing matrix according to the independent component data to generate a new unmixing matrix. The ORICA calculation unit may use the new unmixing matrix to implement an independent component analysis computation. Hardware complexity and power consumption can be reduced by sharing registers and arithmetic calculation units.

CELL-PHONE BASED WIRELESS AND MOBILE BRAIN-MACHINE INTERFACE

Techniques and systems are disclosed for implementing a brain-computer interface. In one aspect, a system for implementing a brain-computer interface includes a stimulator to provide at least one stimulus to a user to elicit at least one electroencephalogram (EEG) signal from the user. An EEG acquisition unit is in communication with the user to receive and record the at least one EEG signal elicited from the user. Additionally, a data processing unit is in wireless communication with the EEG acquisition unit to receive and process the recorded at least one EEG signal to perform at least one of: sending a feedback signal to the user, or executing an operation on the data processing unit. 1. A system for implementing a brain-computer interface , the system comprising:a stimulator to provide at least one stimulus to a user to elicit at least one electroencephalogram (EEG) signal from the user;an EEG acquisition unit in communication with the user to receive and record the at least one EEG signal elicited from the user; and sending a feedback signal to the user, and', 'executing an operation on the data processing unit., 'a data processing unit in wireless communication with the EEG acquisition unit to receive and process the recorded at least one EEG signal to perform at least one of2. The system of claim 1 , wherein the EEG acquisition unit comprises:at least an electrode in communication with the user to receive the EEG signal;analog circuitry to amplify and filter the received EEG signal; anddigital circuitry to generated a digital EEG signal based on the amplified and filtered EEG signal.3. The system of claim 2 , wherein the analog circuitry comprises:instrument amplifiers to amplify the received EEG signal; anda filter to band-pass filter the amplified EEG signal.4. The system of claim 3 , wherein the digital circuitry comprises:an analog-to-digital converter to generate digital EEG signals based on the amplified and filtered EEG signal; anda microcontroller in ...

STIMULI GENERATING METHODS, DEVICES AND CONTROL SYSTEMS TO INDUCE VISUAL EVOKED POTENTIALS USING IMPERCEPTIBLE FLICKERING MULTI-COLOR LIGHTS

Visual or photic stimuli generating methods, devices and control systems for inducing steady-state visual evoked potential (SSVEP) from human viewers without causing discomfort to the viewers or distorting the embedding images are disclosed. The control system includes a stimuli-generating device and an electroencephalography (EEG) sensing device. The stimuli-generating device includes a first and a second light source. The first light source generates a flickering light with a first wavelength while a second light source generates another flickering light with one or more wavelength(s) differ from that of the first one. Together, the light sources generate visual/photic stimuli flickering above their critical flicker fusion threshold while maintaining the colorfulness and hue of the embedding images. At least one electrode of the EEG sensing device is connected to each viewer, configured to receive and analyze his/her EEG signals in order to detect and determine his/her responses to the stimuli. 1. A method to imperceptibly alter an individual's brain state and/or induce measurable responses of the individual's neural cortices comprising modulating flickering of at least one stimulating light source to induce a desired neural response or specific change of the individual brain state; wherein the flickering is imperceptible to the individual being compensated by at least one compensating light source , wherein each of the compensating light sources are composed of one or more color light(s) with specific or randomized spatial luminance distributions and temporal waveforms.2. The method of claim 1 , wherein each stimulating light source comprises one or more color light(s) claim 1 , each of which has a specific wavelength claim 1 , a special spatial luminance distribution and a specific temporal waveform along with a specific flickering frequency claim 1 , amplitude and/or phase to serve the purpose of inducing specific neural responses and/or causing specific ...

WEARABLE MULTI-MODAL BIO-SENSING SYSTEM

A multi-modal bio-sensing apparatus is disclosed including a first sensor module comprising a photoplethysmogram (PPG) sensor configured to produce a first output representative of a blood volume of a human user, wherein the PPG sensor is configured to remove from the first output an error signal due to movement of a user; a second sensor module comprising an electroencephalogram (EEG) sensor configured to produce a third output representative of brain neural activity of the user; a third sensor module comprising an eye-gaze camera configured to capture a gaze direction of one or more eyes of the user; and a wireless communications transceiver coupled to receive sensor data from the first sensor module, the second sensor module, or the third sensor module and configured to wirelessly transmit the received sensor data from the first sensor module, the second sensor module, or the third sensor module out of the multi-modal bio-sensing apparatus. 1. A multi-modal bio-sensing apparatus , comprising:a first sensor module comprising a photoplethysmogram (PPG) sensor configured to produce a first output representative of a blood volume of a user, wherein the PPG sensor is configured to remove from the first output an error signal due to movement of the user;a second sensor module comprising an electroencephalogram (EEG) sensor configured to produce a third output representative of brain neural activity of the user;a third sensor module comprising an eye-gaze camera configured to capture a gaze direction of one or more eyes of the user; anda wireless communications transceiver coupled to receive sensor data from the first sensor module, the second sensor module, or the third sensor module and configured to wirelessly transmit the received sensor data from the first sensor module, the second sensor module, or the third sensor module out of the multi-modal bio-sensing apparatus.2. The multi-modal bio-sensing apparatus of claim 1 , wherein the error signal is determined from a ...

Portable brain activity sensing platform for assessment of visual field deficits

Methods, systems, and devices are disclosed for monitoring electrical signals of the brain. In one aspect, a system for monitoring electrical brain activity associated with visual field of a user includes a sensor unit to acquire electroencephalogram (EEG) signals including a plurality of EEG sensors attached to a casing attachable to the head of a user, a visual display unit attachable to the head of the user over the user's eyes to present visual stimuli, in which the visual stimuli is configured to evoke multifocal steady-state visual-evoked potentials (mfSSVEP) in the EEG signals exhibited by the user acquired by the sensor unit, and a data processing unit in communication with the sensor unit and the visual display unit to analyze the acquired EEG signals and produce an assessment of the user's visual field, in which the assessment indicates if there is a presence of visual field defects in the user's visual field.

HEAD-MOUNTED DISPLAY EEG DEVICE

Methods, systems, and devices are disclosed for monitoring electrical signals of the brain. In one aspect, a system for monitoring electrical brain activity associated with visual field of a user includes a sensor unit to acquire electroencephalogram (EEG) signals including a plurality of EEG sensors circumnavigating the head of a user, and a head-mounted frame for docking a personal electronic device over the user's eyes to present visual stimuli, in which the visual stimuli is configured to evoke EEG signals exhibited by the user, in which the assessment indicates if there is a presence of visual field defects in the user's visual field. 1. A head mounted neuro-monitoring device for monitoring electrical brain activity associated with visual field of a user comprisinga. a sensor unit to acquire electroencephalogram (EEG) signals from one or more electroencephalograph (EEG) sensors arranged to acquire EEG signals from the head of a user andb. a portable electronic device frame capable of housing a removable portable electronic device with a visual display unit that is positioned in front of the user's eyes to present visual stimuli, in which the visual stimuli is configured to evoke visual-event-related responses (VERPs) in the EEG signals exhibited by the user and acquired by the sensor unit.2. The device of claim 1 , wherein the one or more electrodes is a ground or reference terminal.3. The device of claim 2 , wherein the electrodes are replaceable.4. The device of claim 1 , wherein the device comprises two or more electrodes arranged in an array to circumnavigate headband to record EEG signals across the parieto-occipital region of the brain.5. The device of claim 1 , further comprising a data processing unit to process multiple EEG signals and communicate with the sensor unit and the portable electronic device6. The device of claim 5 , wherein the processing unit is capable of improving the quality of the EEG signals claim 5 , estimating the parameter values ...

ARTIFACT REMOVAL TECHNIQUES WITH SIGNAL RECONSTRUCTION

Methods, systems, and devices are disclosed for removing non-stationary and/or non-stereotypical artifact components from multi-channel signals. In one aspect, a method for processing a signal includes obtaining a first signal decomposition of a multi-channel baseline signal in a first matrix including nominal non-artifact signal components and a second signal decomposition of a multi-channel data signal in a second matrix including artifact components, in which the first and second matrices are complimentary matrices, forming a linear transform by non-linearly combining the complementary matrices, and producing an output signal corresponding to the multi-channel data signal by applying the formed linear transform to one or more samples of the multi-channel data signal to remove artifacts and retain non-artifact signal content in the output signal. 1. A method for processing a signal to remove artifacts , comprising:obtaining a first signal decomposition of a multi-channel baseline signal in a first matrix including nominal non-artifact signal components and a second signal decomposition of a multi-channel data signal in a second matrix including artifact components, wherein the first and second matrices are complimentary matrices;forming a linear transform by non-linearly combining the complementary matrices; andproducing an output signal corresponding to the multi-channel data signal by applying the formed linear transform to one or more samples of the multi-channel data signal to remove artifacts and retain non-artifact signal content in the output signal.2. The method as in claim 1 , wherein the forming the linear transform by non-linearly combining the two complementary matrices includes classifying signal components of at least one of the multi-channel baseline signal or the multi-channel data signal into artifact and non-artifact components using a binary classification criterion.3. The method as in claim 2 , wherein the binary classification criterion is ...

BIO-SENSING AND EYE-TRACKING SYSTEM

Methods, systems, and devices are disclosed for implementing a low-cost wearable multi-modal bio-sensing system capable of recording bio-markers and eye-gaze overlaid on world view in real-world settings. In an exemplary embodiment, a bio-sensing system uses at least two cameras and one or more bio-sensors to record a variety of events and bio-marker data. In another exemplary embodiment, the recorded information is used to track the eye position, calculate the pupil dimensions, and calculate the gaze of a human being. The eye position and dimensions of the pupil can be used for emotion recognition. 1. A bio-sensing system , comprising:a frame structured to be placed on a user's face;a first camera coupled to the frame and facing towards an eye of the user to capture a first set of images of the eye;a second camera coupled to the frame and facing away from the user and configured to capture a second set of images of an environment from the user's perspective;one or more sensors configured to measure biological functions of the user and to generate sensor data; anda computer electrically coupled to the one or more sensors, the first camera and the second camera.2. The bio-sensing system of claim 1 , wherein the computer includes at least one processor in communication with a memory operable to execute instructions to cause the computer to perform a method comprising:receiving the first set of images from the first camera;detecting location of a pupil of the eye based on the received first set of images; andcalculating coordinates of the pupil and a diameter of the pupil based on the received first set of images.3. The bio-sensing system of claim 2 , wherein the at least one processor is operable to execute instructions to further cause the computer to perform the method comprising:calculating a confidence of the pupil being present in the first set of images.4. The bio-sensing system of claim 2 , wherein the at least one processor is operable to execute instructions ...

REAL-TIME MULTI-CHANNEL EEG SIGNAL PROCESSOR BASED ON ON-LINE RECURSIVE INDEPENDENT COMPONENT ANALYSIS

A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis is provided. A whitening unit generates covariance matrix by computing covariance according to a received sampling signal. A covariance matrix generates a whitening matrix by a computation of an inverse square root matrix calculation unit. An ORICA calculation unit computes the sampling signal and the whitening matrix to obtain a post-whitening sampling signal. The post-whitening sampling signal and an unmixing matrix implement an independent component analysis computation to obtain an independent component data. An ORICA training unit implements training of the unmixing matrix according to the independent component data to generate a new unmixing matrix. The ORICA calculation unit may use the new unmixing matrix to implement an independent component analysis computation. Hardware complexity and power consumption can be reduced by sharing registers and arithmetic calculation units. 1. A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis (ORICA) , the real-time multi-channel EEG signal processor comprising:an inverse square root matrix calculation unit for providing a computation of eigen, eigen vector and inverse square root matrix;a whitening unit coupled to the inverse square root matrix calculation unit for covariance computation of a sampling signal to generate a covariance matrix, wherein the covariance matrix generates a whitening matrix based on the computation of the inverse square root matrix calculation unit;an ORICA calculation unit coupled to the inverse square root matrix calculation unit and the whitening unit for computing the sampling signal and the whitening matrix to obtain a post-whitening sampling signal, wherein an independent component analysis computation of the post-whitening sampling signal and a predetermined unmixing matrix is performed to obtain independent component data; andan ...

Device and method for detecting cardiac impairments

Electrocardiogram (ECG) recorded signals are processed by a computer-implemented method to substantially remove extraneous signals to produce intermediary signals, and to separate the intermediary signals using a non-orthogonal transformation method such as independent component analysis to produce independent components of signals. The separated signals are displayed to help physicians to analyze medical conditions and to identify locations of abnormal heart conditions.

Device and method for detecting cardiac impairments

Electrocardiogram (ECG) recorded signals are processed by a computer-implemented method to substantially remove extraneous signals to produce intermediary signals, and to separate the intermediary signals using a non-orthogonal transformation method such as independent component analysis to produce independent components of signals. The separated signals are displayed to help physicians to analyze medical conditions and to identify locations of abnormal heart conditions.

Portable brian activity sensing platform for assessment of visual field deficits

Method and system for cardiac signal decomposition

A method and system decomposes a cardiac signal, such as an electrocardiogram (ECG) signal, into components. The components are then usable to assist in the detection of an abnormal heart condition. More particularly, a single lead sensor is used to generate a single lead cardiac signal. The cardiac signal is segmented into a set of cycle segments according to detected heart waveforms. The cycle segments are aligned and used to generate a set of cross-sectional signals. The cross-sectional signals are aligned and presented as inputs to a signal separation process, which separates the cardiac signal into a set of components. The components may be grouped according to predefined criteria. The components or groups may be analyzed or displayed to assist in the detection of an abnormal cardiac signal, which may be indicative of an abnormal heart condition. In one example, the signal separation process is a non-orthogonal transformation method such as independent component analysis (ICA).

System and method for spectral analysis

The system and method for spectral analysis uses a set of spectral data. The spectral data is arranged according to a second dimension, such as time, temperature, position, or other condition. The arranged spectral data is used in a signal separation process, such as an independent component analysis (ICA), which generates independent signals. The independent signals are then used for identifying or quantifying a target component.