John M Irvine, 32Boston, MA

6993378, Jan 31, 2006

Jun 25, 2002

10/178839

Mark D. Wiederhold - San Diego CA, US
Steven A. Israel - Fairfax VA, US
Rodney P. Meyer - Burke VA, US
John M. Irvine - Somerville MA, US

Science Applications International Corporation - San Diego CA

A61B 5/0402

600509, 382115

Methods involving extraction of information from the inherent variability of physiometrics, including data on cardiovascular and pulmonary functions such as heart rate variability, characteristics of ECG traces, pulse, oxygenation of subcutaneous blood, respiration rate, temperature or COcontent of exhaled air, heart sounds, and body resonance, can be used to identify individual subjects, particularly humans. Biometric data for use in the methods can be obtained either from contact sensors or at a distance. The methods can be performed alone or can be fused with previous identification algorithms.

2020022, Jul 23, 2020

Jan 21, 2020

16/748717

- Cambridge MA, US
Laura Jane Mariano - Somerville MA, US
Abraham Schneider - Andover MA, US
John Irvine - Somerville MA, US

A61B 5/00
G06T 7/00
G06N 3/04
G06N 3/08
G16H 50/20
G16H 30/20

A method of predicting progression of a cognitive state in a subject is disclosed including obtaining a neuroimage of the subject, acquiring a data sample from the neuroimage, selecting a time at which to predict progression of the cognitive state, and performing a calculation on the data sample by a transformation function to determine data associated with multiple cognitive metrics. A method of evaluating a cognitive state of a subject is also disclosed including providing a convolutional neural network, training the convolutional neural network with reference data to construct a transformation function, using the transformation function to predict multiple cognitive metrics from a subject data sample and a selected time, and determining the cognitive state of the subject from the predicted cognitive metrics. A cognitive evaluation system is also disclosed including a memory, a processor, and a cognitive state prediction component configured to program the processor with a transformation function.

2020002, Jan 30, 2020

Jul 25, 2018

16/044874

- Cambridge MA, US
John M. Irvine - Somerville MA, US
Nirmal Keshava - Cambridge MA, US

A61B 5/00
A61B 5/055
A61B 5/16
G16H 50/20
G16H 30/40

A MRS (magnetic resonance spectroscopy or nuclear magnetic resonance NMR)-based PTSD (post-traumatic stress disorder) and mTBI (mild traumatic brain injury) diagnostic system and method uses MRS signals, already pre-processed by the MRS scanner software. The signals are collected in vivo from specific regions of the brain. A wavelet decomposition is applied to the MRS signals, and the amplitude of the wavelet coefficients and their location in the MRS signals are used as features for training diagnostic classifiers of disease states. These classifiers are identified through analysis of features of individuals whose health status is known. Once the classifiers are trained, patients can be diagnosed by using the same wavelet features extracted from in vivo MRS scans of their brain regions.

2020003, Jan 30, 2020

Jul 25, 2018

16/044877

- Cambridge MA, US
John M. Irvine - Somerville MA, US

G01R 33/46
G01R 33/465

A 2-D MRS (magnetic resonance spectroscopy), or equivalently, NMR (nuclear magnetic resonance), pre-processing method produces clean MRS signals from raw data for possible use, among other applications, for diagnoses of neurological disorders such as PTSD and mTBI of the brain. The specific 2-D MRS data referred to in this invention are the 2-D MRS Correlation Spectroscopy or 2-D COSY data.

2018031, Nov 1, 2018

May 1, 2018

15/967673

- Cambridge MA, US
Laura Jane Mariano - Somerville MA, US
Abraham Schneider - Andover MA, US
John Irvine - Somerville MA, US

A61B 5/00
G16H 30/20
G16H 50/20
G06N 3/08
G06N 3/04
G06T 7/00

A method of predicting progression of a cognitive state in a subject is disclosed including obtaining a neuroimage of the subject, acquiring a data sample from the neuroimage, selecting a time at which to predict progression of the cognitive state, and performing a calculation on the data sample by a transformation function to determine data associated with multiple cognitive metrics. A method of evaluating a cognitive state of a subject is also disclosed including providing a convolutional neural network, training the convolutional neural network with reference data to construct a transformation function, using the transformation function to predict multiple cognitive metrics from a subject data sample and a selected time, and determining the cognitive state of the subject from the predicted cognitive metrics. A cognitive evaluation system is also disclosed including a memory, a processor, and a cognitive state prediction component configured to program the processor with a transformation function.

2017010, Apr 20, 2017

Oct 18, 2016

15/296786

- Cambridge MA, US
Peter Lommel - Andover MA, US
Lei Hamilton - Lexington MA, US
Rami Mangoubi - Newton MA, US
Richard Wood - Derry NH, US
John Irvine - Somerville MA, US
Stephen Duncan - Winchester MA, US
David O'Dowd - Boston MA, US

A61B 3/00
G06T 7/00
G06K 9/62
G06K 9/46
A61B 3/12
A61B 3/10

The present disclosure describes systems and methods to select fovea containing optical coherence tomography (OCT) images. The systems and methods described herein receive a plurality of OCT images. The portion of the OCT images are selected for further processing, where a line tracing the border between the retina and non-retina tissue is generated. A difference of the line is generated. Candidate OCT images are then generated responsive to the generated difference line. The lowest point among each difference lines generated for each of the OCT images is identified, and the OCT image to which the lowest point corresponds is identified as the fovea containing OCT image.

2017010, Apr 20, 2017

Oct 18, 2016

15/296790

- Cambridge MA, US
Peter Lommel - Andover MA, US
Rami Mangoubi - Newton MA, US
Richard Wood - Derry NH, US
Lei Hamilton - Lexington MA, US
John Irvine - Somerville MA, US
Stephen Duncan - Winchester MA, US

G06T 7/00

The present disclosure describes a system and method to segment optical coherence tomography (OCT) images. The present system uses a hybrid method that employs both Bayesian level sets (BLS) and graph-based segmentation algorithms. The system first identifies retinal tissue within an OCT image using the BLS algorithms. The identified retinal tissue is then further segmented using the graph-based segmentation algorithms.

2015022, Aug 6, 2015

Feb 2, 2015

14/611788

- Cambridge MA, US
John M. Irvine - Somerville MA, US
David Reed - Boston MA, US

G06K 9/00
G06K 9/46

This disclosure provides systems, methods, and apparatus for analyzing a video are disclosed. An input video signal can be received and a quality metric associated with the input video signal can be determined. A parameter to be used in a first object tracking process can be selected, based in part on the quality metric associated with the input video signal. A background model can be extracted from the input video signal based on an online median estimate of the intensity values of the pixels in the image frames. The online median estimate can be calculated using a quantile function.