Patents by Inventor Derek Morris

Derek Morris has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210272789
    Abstract: A method is disclosed comprising obtaining or acquiring chemical or other non-mass spectrometric data from one or more regions of a target (2) using a chemical sensor (20). The chemical or other non-mass spectrometric data may be used to determine one or more regions of interest of the target (2). An ambient ionisation ion source 1 may then be used to generate aerosol, smoke or vapour (5) from one or more regions of the target (2).
    Type: Application
    Filed: May 7, 2021
    Publication date: September 2, 2021
    Inventors: Steven Derek PRINGLE, Emrys JONES, Michael Raymond MORRIS, Julia BALOG, James Ian LANGRIDGE, Keith RICHARDSON, Daniel SIMON, Lajos GODORHAZY, Daniel SZALAY, Zoltan TAKATS
  • Publication number: 20210260289
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210260287
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210259591
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210260288
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210260286
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Patent number: 10889373
    Abstract: A drone system has a camera mounted to a frame of a drone, the camera configured to acquire image data upon receipt of a signal from a flight controller and a precision location device configured for continuously obtaining location data. Additionally, the drone system has a computing device configured for receiving a signal indicating that an image has been acquired, the computing device configured for transmitting a signal to a precision location device indicating that an image has been acquired, and the precision location device is further configured to record event data associated with a time indicating when the image was acquired.
    Type: Grant
    Filed: March 1, 2018
    Date of Patent: January 12, 2021
    Assignee: GEOCUE GROUP, LLC
    Inventors: Lewis Graham, Nancy Graham, Derek Morris, Carl Steven Riddell, Hai Quang Dinh
  • Publication number: 20200040306
    Abstract: A printable composition for the manufacture of cell-receiving scaffolds comprising about 0.3 wt % to about 3.0 wt % of one or more collagens; about 5.0 wt % to about 40.0 wt % of one or more monomers; about 0.5 wt % to about 2.0 wt % of a photo initiator; and 0 wt % to about 75 wt % of a vehicle comprising a protic solvent, by weight of the printable composition; wherein the printable composition has a resolution of about 100 microns or less when printed, a photo speed (Dp/Ec) of about 0.1-5 mm (Dp) and about 10-100 mJ/cm2 (Ec) when printed, and a green strength of at least about 5 kPa after drying. The present technology further includes methods of manufacturing a three-dimensional cell-receiving scaffold using the printable composition.
    Type: Application
    Filed: August 1, 2019
    Publication date: February 6, 2020
    Applicant: Lung Biotechnology PBC
    Inventors: Pingyong Xu, Luis Alvarez, Derek Morris, Iman Yazdi
  • Publication number: 20190135431
    Abstract: A system for synchronizing events has a first subsystem that detects, measures, or generates a first set of events and the first subsystem has a first clock for time-stamping each event detected, measured, or generated by the first subsystem. The system further has a second subsystem that detects, measures, or generates a second set of events and the second subsystem has a second clock not synchronized to the first clock. The second clock is for time-stamping events detected, measured, or generated by the second subsystem. The first set of events is related to the second set of events. The system further has a processor that correlates the first set of events with the second set of events to determine a value indicative of a temporal shift between a time of occurrence of the first set of events and a time of occurrence of the second set of events.
    Type: Application
    Filed: October 17, 2018
    Publication date: May 9, 2019
    Applicant: Geocue Group, Inc.
    Inventors: Lewis N. Graham, JR., Carl S. Riddell, Derek Morris
  • Publication number: 20180297700
    Abstract: A drone system has a camera mounted to a frame of a drone, the camera configured to acquire image data upon receipt of a signal from a flight controller and a precision location device configured for continuously obtaining location data. Additionally, the drone system has a computing device configured for receiving a signal indicating that an image has been acquired, the computing device configured for transmitting a signal to a precision location device indicating that an image has been acquired, and the precision location device is further configured to record event data associated with a time indicating when the image was acquired.
    Type: Application
    Filed: March 1, 2018
    Publication date: October 18, 2018
    Applicant: Geocue Group, LLC
    Inventors: Lewis Graham, Nancy Graham, Derek Morris, Carl Steven Riddell, Hai Quang Dinh