Sean A Mcnamara

US Patent:

20130290450, Oct 31, 2013

Filed:

Apr 23, 2013

Appl. No.:

13/868269

Inventors:

Andrew Psaltis - Littleton CO, US
Sean McNamara - Lehi UT, US

Assignee:

WEBTRENDS INC. - Portland OR

International Classification:

H04L 12/58

US Classification:

709206

Abstract:

The current document is directed to systems and methods that stream real-time, processed data from remote processor-controlled user appliances, including personal computers, tablets, mobile phones, and laptops, to application programs for display, analysis, and other purposes and to other data-consuming devices and systems. In one implementation, a real-time processed-data streaming system includes instrumentation within remote, processor-controlled user devices, data collection at geographically distributed data-collection centers, consolidation of event messages generated by the geographically distributed data-collection centers within consolidation systems, processing of the consolidated event messages within one or more processing centers, and streaming of processed data, in the form of various types of processed-data-containing messages, to consumers of the data, including application programs that render the data for display on electronic display devices.

US Patent:

20170209090, Jul 27, 2017

Filed:

Apr 7, 2017

Appl. No.:

15/482519

Inventors:

- Glendale CO, US
Sean M. McNamara - Denver CO, US

International Classification:

A61B 5/00
A61B 8/00
A61B 8/08

Abstract:

Provided is a non-invasive system and method of determining human body fat based on image processing. The method includes receiving at least one ultrasound scan image of at least a portion of a skin layer as disposed above one or more additional tissue layers, the skin layer defining a horizontal axis and the image provided by a plurality of pixels. The method continues by horizontally blurring the pixels of the image and thresholding the pixels of the image to provide a binary image having a plurality of elements of different sizes. The method continues with morphing the structural elements of the binary image to remove small elements and connect large elements. With this resulting image, the method distinguishes a body fat layer from the remaining elements and determines the body fat layer thickness. An associated system is also disclosed.

US Patent:

20160249887, Sep 1, 2016

Filed:

Apr 18, 2016

Appl. No.:

15/131909

Inventors:

- Denver CO, US
Pierre Sarnow - Littleton CO, US
Sean M. McNamara - Denver CO, US

International Classification:

A61B 8/08
A61B 8/00

Abstract:

Provided is a non-invasive system and method for determining a target glycogen score value for a target muscle and potentially at least one indicator muscle. The method includes receiving an ultrasound scan of a target muscle; evaluating at least a portion of the ultrasound scan to determine glycogen store value within the target muscle; recording the determined glycogen store value for the muscle as an element of a glycogen value data set for the muscle; evaluating the glycogen value data set to determine a value range; and in response to the range being at least above a pre-determined threshold, establishing a target score for the muscle as based on an upper portion of the value range. The method may be repeated to identify ranges for a plurality of muscles, the muscle with the greatest range being identified as an indicator muscle. An associated system is also disclosed.

US Patent:

20160081654, Mar 24, 2016

Filed:

Sep 19, 2014

Appl. No.:

14/491553

Inventors:

- Denver CO, US
Sean M. McNamara - Denver CO, US

International Classification:

A61B 8/08
A61B 8/00
A61B 5/00

Abstract:

Provided is a non-invasive system and method of determining human body fat based on image processing. The method includes receiving at least one ultrasound scan image of at least a portion of a skin layer as disposed above one or more additional tissue layers, the skin layer defining a horizontal axis and the image provided by a plurality of pixels. The method continues by horizontally blurring the pixels of the image and thresholding the pixels of the image to provide a binary image having a plurality of elements of different sizes. The method continues with morphing the structural elements of the binary image to remove small elements and connect large elements. With this resulting image, the method distinguishes a body fat layer from the remaining elements and determines the body fat layer thickness. An associated system is also disclosed.