Neuroptics, Inc.

Other

Teledyne Scientific and Imaging, LLC

Claudio M Privitera

Kamran Siminou

Lawrence W Stark

Jeffrey Oliver

Ming Qian

Mario Aguilar

Karen Zachery

A method of screening a pupil of a subject to determine whether the pupil reflex resembles a canonical pupil reflex is disclosed. The method comprises the steps of stimulating the pupil with a stimulus source, such as a pupilometer and determining whether one of various pupillary response conditions is met.

Pupilary screening system and method

A computer program is disclosed for performing the following method: recording images of a response of a left pupil to a stimulus thereby resulting in a first set of sequential images; recording images of a response of a right pupil to the same stimulus at the same time as the first images were recorded, thereby resulting in a second set of sequential images; displaying on a display simultaneously the first set of images and the second set of image, wherein the two sets of images are synchronized, and wherein a center of the left pupil of each image from the first set of sequential images is aligned with a center of the right pupil from the second set of sequential images on the display.

Methods, systems, and devices for monitoring anisocoria and asymmetry of pupillary reaction to stimulus

A system for use during a medical procedure. The system includes a pupilometer for obtaining data descriptive of one or more pupilary characteristics from an eye of a subject, and means for delivering a noxious stimulus. The means for delivering a noxious stimulus is in communication with the pupilometer and is activated by the pupilometer thereby sending a noxious stimulus to an anatomical structure of the patient.

Pupilometer with pupil irregularity detection, pupil tracking, and pupil response detection capability, glaucoma screening capability, intracranial pressure detection capability, and ocular aberration measurement capability

A method of screening a pupil of a subject to determine whether the pupil reflex resembles a canonical pupil reflex is disclosed. The method comprises the steps of stimulating the pupil with a stimulus source. The method further includes the steps of using a pupilometer to track the pupil's constriction response over a duration of time, wherein the step of tracking the pupil constriction response begins substantially simultaneously with or immediately subsequent to timeand lasts for a period of time y, and using the pupilometer to collect a plurality of data points in which each data point corresponds with a diameter of the pupil at a specific time within the time duration y. The method further includes the step of generating a pupil data profile by compiling the data points and determining whether one or more conditions arc met. wherein the one or more conditions comprises the following: (a) more than two data points exist representing the same pupil diameter at three or more separate times during duration y; (b) a first phase of the pupilary reflex response exists, wherein said first phase is characterized by a period of non-constriction immediately subsequent to time, said first phase having a duration of less than about 100 msec or greater than about 1000 msec; (c) if two data points exist representing the same pupil diameter at two separate times yand yduring duration y, then the duration of time between yand yis less than about 100 msec; or during the first phase of the pupilary reflex, the diameter of the pupil increases before it decreases. Existence of one of said conditions indicates that the pupil reflex does not resemble a canonical reflex.

Pupilary screening method and system

A pupilometer that has image capturing means, a light source that emits light; and imaging software that processes image data obtained by the image capturing means and produces an output is described. The output comprises a single scalar value indicative of a neurological condition of a patient, wherein the scalar value can be applied to a scale indicative of a neurological condition. The image data comprises one or more components of the pupil's dynamic response to light emitted by the light source.

A computationally efficient and robust approach for monitoring the instantaneous pupil response as a correlate to significant cognitive response to relevant stimuli derives data samples d(n) of the pupil diameter (area), v(n) of pupil velocity and a(n) of pupil acceleration from the pupillary response and segments the data samples into a sequence of time-shifted windows. A feature extractor extracts a plurality of spatio-temporal pupil features from the data samples from the response and baseline periods in each window. A classifier trained to detect patterns of the extracted spatio-temporal pupil features for relevant stimuli generates an output indicative of the occurrence of absence of a significant cognitive response in the subject to a relevant stimulus.

Fusion-based spatio-temporal feature detection for robust classification of instantaneous changes in pupil response as a correlate of cognitive response

A pupilometer having image capturing means, illumination means generating and emitting light of a first wavelength, stimulation means generating and emitting light of a second wavelength, and image processing software. The image processing software receives data from the image capturing means, identifies a pupil's dynamic response to light generated by the stimulation means, analyzes one or more components of the pupil's dynamic response, and produces an output comprising a value indicative of a neurological condition of a patient.

A pupilometer having a pupil irregularity or non-uniformity detection capability. The pupilometer may comprise an imaging sensor for generating signals representative of a pupil of an eye, a data processor; and a program executable by the data processor for enabling the data processor to process signals received from the imaging sensor and to thereby identify one or more regions of non-uniformity within an image of a perimeter of the pupil. The pupilometer may incorporate several innovative calibration and thresholding routines and may provide the basis for an innovative medical diagnostics system, when coupled to a network containing a suitable medical database and data processing hardware.

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Berkeley, CA, United States of America

Claudio M Privitera