Hi LLC

Julian Kates-Harbeck

Ryan Field

Jamu Alford

Benjamin Shapiro

Bryan Johnson

Antonio H Lara

Husam Katnani

Ethan Pratt

Hamid Dehghani

Gabriel Lerner

Viktoria Rojkova

Micah Ledbetter

Michael Henninger

Isai Olvera

Katherine Perdue

Benjamin Siepser

Zachary Bednarke

Ashutosh Chaturvedi

Victoria A Poissant

Vincent Maurice

An illustrative optical measurement system includes a light source configured to emit light directed at a target within a user. The system further includes a detector configured to detect photon arrival times for photons of the light after the light is scattered by the target. The system further includes a processor configured to determine, based on the photon arrival times, histogram data associated with the target, the histogram data including noise. The processor is further configured to determine, based on the photon arrival times, a random matrix corresponding to the photon arrival times. The processor is further configured to determine, based on the random matrix, a noise distribution representing a distribution of the noise within the histogram data. The processor is further configured to generate clean histogram data using the noise distribution to filter at least a portion of the noise from the histogram data.

Systems and methods for noise removal in an optical measurement system

An actuated magnetic field is generated at a plurality of distinct frequencies that at least partially cancels an outside magnetic field at the plurality of distinct frequencies, thereby yielding a total residual magnetic field. The total residual magnetic field is coarsely detected and a plurality of coarse error signals are respectively output. The total residual magnetic field is finely detected and a plurality of fine error signals are respectively output. The actuated magnetic field is controlled respectively at the plurality of distinct frequencies at least partially based on at least one of the plurality of coarse error signals, and finely controlled respectively at the plurality of distinct frequencies at least partially based on at least one of the plurality of fine error signals.

Nested and parallel feedback control loops for ultra-fine measurements of magnetic fields from the brain using a neural detection system

An illustrative method includes accessing, by a computing device, a model simulating light scattered by a simulated target, the model comprising a plurality of parameters. The method further includes generating, by the computing device, a set of possible histogram data using the model with a plurality of values for the parameters. The method further includes determining, by the computing device, a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data.

Systems and methods for data representation in an optical measurement system

A calibration system for a magnetometer having an unknown gain is disclosed. A calibration magnetic field is generated at a calibration frequency of a known amplitude at the magnetometer. A measurement of the calibrating magnetic field is reported by the magnetometer. A ratio of an amplitude of the calibration magnetic field measurement reported by the magnetometer and the known amplitude of the calibrating magnetic field at the magnetometer is computed. The unknown gain of the magnetometer is determined at least partially based on computed ratio.

Self-calibration of flux gate offset and gain drift to improve measurement accuracy of magnetic fields from the brain using a wearable neural detection system

At least one magnetic field actuator is configured for generating an actuated magnetic field that at least partially cancels an outside magnetic field, thereby yielding a total residual magnetic field. A plurality of magnetometers are configured for taking measurements of the total residual magnetic field. The magnetometers include a plurality of coarse magnetometers and a plurality of fine magnetometers. A processor is configured for acquiring the total residual magnetic field measurements from the coarse magnetometers, estimating the total residual magnetic field at the fine magnetometers based on total residual magnetic field measurements acquired from the plurality of coarse magnetometers, and controlling the actuated magnetic field at least partially based on the total residual magnetic field estimates at the fine magnetometers in a manner that suppresses the total residual magnetic field at the fine magnetometers to a baseline level, such that at least one of the fine magnetometers is in-range.

Estimating the magnetic field at distances from direct measurements to enable fine sensors to measure the magnetic field from the brain using a neural detection system

An active shield magnetometry system comprises at least one magnetic field actuator configured for generating an actuated magnetic field that at least partially cancels an outside magnetic field, thereby yielding a total residual magnetic field. The active shield magnetometry system further comprises a plurality of magnetometers respectively configured for measuring the total residual magnetic field and outputting a plurality of total residual magnetic field measurements. The active shield magnetometry system further comprises at least one feedback control loop comprising at least one optimal linear controller configured for controlling the actuated magnetic field at least partially based on at least one of the plurality of total residual magnetic field measurements respectively output by at least one of the plurality of magnetometers.

Optimal methods to feedback control and estimate magnetic fields to enable a neural detection system to measure magnetic fields from the brain

A system for training a neurome that emulates a brain of a user comprises a non-invasive brain interface assembly configured for detecting neural activity of the user in response to analog instances of a plurality of stimuli peripherally input into the brain of the user from at least one source of content, memory configured for storing a neurome configured for outputting a plurality of determined brain states of an avatar in response to inputs of the digital instances of the plurality of stimuli, and a neurome training processor configured for determining a plurality of brain states of the user based on the detected neural activity of the user, and modifying the neurome based on the plurality of determined brain states of the user and the plurality of determined brain states of the avatar.

Methods for training and using a neurome that emulates the brain of a user

An illustrative optical measurement device includes a light source configured to emit light pulses directed at a target. The optical measurement device further includes a detector configured to detect arrival times for photons of the light pulses after the photons are scattered by the target. The optical measurement device further includes a processing unit configured to generate, based on the arrival times of the photons at the detector, histogram data associated with the target. The processing unit is further configured to determine, based on the histogram data, an absolute optical property associated with the target. The processing unit is further configured to determine, based on the absolute optical property, a blood oxygenation level of the user, and perform an operation based on the blood oxygenation level.

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Marina Del Rey, CA, United States of America

Julian Kates-Harbeck