Sarnoff Corporation

The City University of New York

Columbia University

Other

Thomson Licensing

Gn Hearing A/s

Neuromatters, LLC

Soterix Medical, Inc.

Optios, Inc.

Lucas Cristobal Parra

Clay Douglas Spence

Paul Sajda

Marom Bikson

Abhishek Datta

Varun Bansal

Andrew Dittberner

Christopher Vincent Alvino

Tobias Piechowiak

Paul DeGuzman

Craig Fancourt

Jacek Dmochowski

Aalbert De Vries

Preet Minhas

Shiraz Azar Macuff

Sheldon Weinbaum

Luis Cardoso

Niranjan Khadka

Dan Steingart

Jinal Patel

Jorge Vega

Xiang Zhou

Yuliya Vengrenyuk

Stephane Carlier

Savvas Xanthos

Daniel Rosenthal

Yuzhuo Su

Johnson Ho

Ivan Vladimirov Iotzov

Charles Phillip Cloud

Andrew Burke Dittberner

Jacek Piotr Dmochowski

A hearing aid includes: a microphone configured to provide a microphone signal that corresponds with an acoustic stimulus naturally received by a user of the hearing aid; a processing unit coupled to the microphone, the processing unit configured to provide a processed signal based at least on the microphone signal; a speaker coupled to the processing unit, the speaker configured to provide an acoustic signal based on the processed signal; and a sensor configured to measure a neural response of the user to the acoustic stimulus, and to provide a sensor output; wherein the processing unit is configured to detect presence of speech based on the microphone signal, and to process the sensor output and the microphone signal to estimate speech intelligibility; and wherein the processing unit is also configured to adjust a sound processing parameter for the hearing aid based at least on the estimated speech intelligibility.

Hearing aids with self-adjustment capability based on electro-encephalogram (EEG) signals

Methods are disclosed for determining an efficacy of a stimulus based on one or more measurable physiological responses to one or more stimuli including one or more stimulus features. Data is acquired on physiological responses of a group of one or more subjects to presentation of one or more stimuli including one or more stimulus features. The data on the one or more physiological responses of the one or more subjects is correlated with the presentation of the one or more stimulus features included in the one or more stimuli. The correlated data on the one or more physiological responses are associated with a separately-determined efficacy of the one or more stimuli to form a stimulus efficacy model. From this information, a projected efficacy of a stimulus is determinable by comparing one or more subsequently-measured physiological responses to the stimulus with the stimulus efficacy model.

Method for predicting efficacy of a stimulus by measuring physiological response to stimuli

An electrode assembly for neuro-cranial stimulation includes an electrode, a conductive gel, and an adapter including an interior compartment for positioning the electrode relative to the adapter and for receiving and retaining the conductive gel. The conductive gel contacts the electrode along an electrode-gel interface. An orifice at one end of the interior compartment and adjacent to a positioning surface of the adapter for positioning the electrode assembly against a skin surface of a user enables the conductive gel is able to contact the skin surface of the user to define a gel-skin interface, such that a minimum distance between the electrode-gel interface and the gel-skin interface is maintained between 0.25 cm and 1.3 cm. An electrode assembly mounting apparatus is provided for adjustably positioning a plurality of electrode assemblies against target positions on the cranium.

Methods for reducing discomfort during electrostimulation, and compositions and apparatus therefor

In some embodiments of the present disclosure, systems and methods for effecting a physiological effect are provided. In some embodiments, a system is provided which comprises a plurality of current sources, where each current source having a positive output and a negative output and each being configured to provide a first current. The system may also include a plurality of stimulating electrodes electrically connected with the plurality of current sources such that at least a pair of the stimulating electrodes share at least one output of at least one of the plurality of current sources. The stimulating electrodes may be configured to provide electrical energy to tissue of a patient at the first current. The system may further include at least one sentinel electrode, and a first voltage monitor configured to monitor a first voltage across the at least one sentinel electrode and at least one of the plurality of stimulating electrodes.

System and method for conducting multi-electrode electrical stimulation

A method includes coupling electrodes to a patient's head and identifying whether any of the electrodes form a functional set, such that a desired therapeutic effect is achieved when the two or more electrodes deliver a total amount of current to the patient regardless of what portion of the total amount of current each respective electrode carries. One or more constant current sources are provided, each having a supply and return terminal, which supply and return equal amounts of current at any given time. The constant current source(s) are coupled to the electrodes in such a manner that each supply terminal and each return terminal is coupled to no more than the electrodes of a single one of the functional sets, if any, or to a single one of the electrodes not included in one of the functional sets.

Transcranial stimulation

A system includes an in vivo imaging device for imaging a blood vessel with a resolution level of at least fifty micrometers. The in vivo imaging device is capable of detecting a microcalcification in a fibrous cap of an atheroma. The system also includes a processor for receiving an image of the blood vessel from the in vivo imaging device. The processor uses the image to determine whether the blood vessel contains at least one microcalcification within the fibrous cap. In some embodiments, the processor is configured and arranged to predict a risk of rupture of the fibrous cap based, at least in part, on the presence of the at least one microcalcification. In some embodiments, treatment of a patient is based on the determination from the imaging whether the blood vessel includes at least one microcalcification within the fibrous cap of the atheroma.

System and method for in vivo imaging of blood vessel walls to detect microcalcifications

An EEG cap () having 64 or 128 electrodes () is placed on the head of the subject () who is viewing CRT monitor (). The signals on each channel are amplified by amplifier () and sent to an analog-to-digital converter (). PC () captures and records the amplified signals and the signals are processed by signal processing PC () performing linear signal processing. The resulting signal is sent back to a feedback/display PC () having monitor ().

Single Trial detection in encephalography

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for developing transcranial electrical stimulation protocols are disclosed. In one aspect, a method includes forming a first array of electrodes and optimizing a plurality of electrode parameters within the first array of electrodes to achieve a desired physiological response; identifying one or more electrodes within the optimized first array that have relatively low current compared to the remaining electrodes in the first array; removing the identified low current electrodes from the first array to form a second array of electrodes, wherein the number of electrodes in the second array is less than the number of electrodes in the first array and optimizing a plurality of electrode parameters with the second array of electrodes to achieve a desired physiological response.

Neurocranial electrostimulation models, systems, devices, and methods

A computer system that processes mixtures of signals, such as speech and noise sources derived from multiple simultaneous microphone recordings, in order to separate them into their underlying sources. A source separation routine optimizes a filter structure by minimizing cross powers of multiple output channels while enforcing geometric constraints on the filter response. The geometric constraints enforce desired responses for given locations of the underlying sources, based on the assumption that the sources are localized in space.

Geometric source separation signal processing technique

Single trial detection in encephalography

A method and apparatus is disclosed for performing blind source separation using convolutive signal decorrelation. For a first embodiment, the method accumulates a length of input signal (mixed signal) that comprises a plurality of independent signals from independent signal sources. The invention then divides the length of input signal into a plurality of T-length periods (windows) and performs a discrete Fourier transform (DFT) on the signal within each T-length period. Thereafter, estimated cross-correlation values are computed using a plurality of the averaged DFT values. A total number of K cross-correlation values are computed, where each of the K values is averaged over N of the T-length periods. Using the cross-correlation values, a gradient descent process computes the coefficients of a FIR filter that will effectively separate the source signals within the input signal. A second embodiment of the invention is directed to on-line processing of the input signal&#x2014;i.e., processing the signal as soon as it arrives with no storage of the signal data. In particular, an on-line gradient algorithm is provided for application to non-stationary signals and having an adaptive step size in the frequency domain based on second derivatives of the cost function. The on-line separation methodology of this embodiment is characterized as multiple adaptive decorrelation.

Method and system for on-line blind source separation

A method and apparatus is disclosed for performing blind source separation using convolutive signal decorrelation. For a first embodiment, the method accumulates a length of input signal (mixed signal) that includes a plurality of independent signals from independent signal sources. The invention then divides the length of input signal into a plurality of T-length periods (windows) and performs a discrete Fourier transform (DFT) on the, signal within each T-length period. Thereafter, estimated cross-correlation values are computed using a plurality of the averaged DFT values. A total number of K cross-correlation values are computed, where each of the K values is averaged over N of the T-length periods. Using the cross-correlation values, a gradient descent process computes the coefficients of a finite impulse response (FIR) filter that will effectively separate the source signals within the input signal. A second embodiment of the invention is directed to on-line processing of the input signal&#x2014;i.e., processing the signal as soon as it arrives with no storage of the signal data. In particular, an on-line gradient algorithm is provided for application to non-stationary signals and having an adaptive step size in the frequency domain based on second derivatives of the cost function. The on-line separation methodology of this embodiment is characterized as multiple adaptive decorrelation.

An apparatus and a concomitant method for modeling local and non-local information in an image to compute an image probability distribution for the image is disclosed. In one embodiment, such an image probability distribution is determined in an object recognition system.

Method and apparatus for image processing by generating probability distribution of images

A signal processing system for detecting the presence of a desired signal component by applying a probabilistic description to the classification and tracking of various signal components (e.g., desired versus non-desired signal components) in an input signal is disclosed.

Method and apparatus for adaptive speech detection by applying a probabilistic description to the classification and tracking of signal components

A method and apparatus for training and operating a neural network using gated data. The neural network is a mixture of experts that performs &ldquo;soft&rdquo; partitioning of a network of experts. In a specific embodiment, the technique is used to detect malignancy by analyzing skin surface potential data. In particular, the invention uses certain patient information, such as menstrual cycle information, to &ldquo;gate&rdquo; the expert output data into particular populations, i.e., the network is soft partitioned into the populations. An Expectation-Maximization (EM) routine is used to train the neural network using known patient information, known measured skin potential data and correct diagnosis for the particular training data and patient information. Once trained, the neural network parameters are used in a classifier for predicting breast cancer malignancy when given the patient information and skin potentials of other patients.

Growing community of inventors

Brooklyn, NY, United States of America

Lucas Cristobal Parra