Edward P Sweeney

US Patent:

20210259591, Aug 26, 2021

Filed:

Dec 7, 2020

Appl. No.:

17/114254

Inventors:

- San Diego CA, US
Derek James Escobar - Escondido CA, US
Sumitaka Mikami - San Diego CA, US
Hari Hampapuram - Portland OR, US
Benjamin Elrod West - San Diego CA, US
Nathanael Paul - Knoxville TN, US
Naresh C. Bhavaraju - San Diego CA, US
Michael Robert Mensinger - San Diego CA, US
Gary A. Morris - La Jolla CA, US
Andrew Attila Pal - San Diego CA, US
Eli Reihman - San Diego CA, US
Scott M. Belliveau - San Diego CA, US
Katherine Yerre Koehler - Solana Beach CA, US
Nicholas Polytaridis - San Diego CA, US
Rian Draeger - San Diego CA, US
Jorge Valdes - San Diego CA, US
David Price - Carlsbad CA, US
Peter C. Simpson - Cardiff CA, US
Edward Sweeney - Poway CA, US

International Classification:

A61B 5/145
A61B 5/00
A61M 5/172
A61M 5/142

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.

US Patent:

20210260286, Aug 26, 2021

Filed:

Dec 7, 2020

Appl. No.:

17/114137

Inventors:

- San Diego CA, US
Derek James Escobar - Escondido CA, US
Sumitaka Mikami - San Diego CA, US
Hari Hampapuram - Portland OR, US
Benjamin Elrod West - San Diego CA, US
Nathanael Paul - Knoxville TN, US
Naresh C. Bhavaraju - San Diego CA, US
Michael Robert Mensinger - San Diego CA, US
Gary A. Morris - La Jolla CA, US
Andrew Attila Pal - San Diego CA, US
Eli Reihman - San Diego CA, US
Scott M. Belliveau - San Diego CA, US
Katherine Yerre Koehler - Solana Beach CA, US
Nicholas Polytaridis - San Diego CA, US
Rian Draeger - San Diego CA, US
Jorge Valdes - San Diego CA, US
David Price - Carlsbad CA, US
Peter C. Simpson - Cardiff CA, US
Edward Sweeney - Poway CA, US

International Classification:

A61M 5/172
G16H 40/67
G16H 20/17
G16H 10/60
G06N 20/00

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.

US Patent:

20210260287, Aug 26, 2021

Filed:

Dec 7, 2020

Appl. No.:

17/114142

Inventors:

- San Diego CA, US
Derek James Escobar - Escondido CA, US
Sumitaka Mikami - San Diego CA, US
Hari Hampapuram - Portland OR, US
Benjamin Elrod West - San Diego CA, US
Nathanael Paul - Knoxville TN, US
Naresh C. Bhavaraju - San Diego CA, US
Michael Robert Mensinger - San Diego CA, US
Gary A. Morris - La Jolla CA, US
Andrew Attila Pal - San Diego CA, US
Eli Reihman - San Diego CA, US
Scott M. Belliveau - San Diego CA, US
Katherine Yerre Koehler - Solana Beach CA, US
Nicholas Polytaridis - San Diego CA, US
Rian Draeger - San Diego CA, US
Jorge Valdes - San Diego CA, US
David Price - Carlsbad CA, US
Peter C. Simpson - Cardiff CA, US
Edward Sweeney - Poway CA, US

International Classification:

A61M 5/172
G16H 20/17
H04W 12/037
H04L 9/30
G16H 40/67
G06N 20/00

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.

US Patent:

20210260288, Aug 26, 2021

Filed:

Dec 7, 2020

Appl. No.:

17/114190

Inventors:

- San Diego CA, US
Derek James Escobar - Escondido CA, US
Sumitaka Mikami - San Diego CA, US
Hari Hampapuram - Portland OR, US
Benjamin Elrod West - San Diego CA, US
Nathanael Paul - Knoxville TN, US
Naresh C. Bhavaraju - San Diego CA, US
Michael Robert Mensinger - San Diego CA, US
Gary A. Morris - La Jolla CA, US
Andrew Attila Pal - San Diego CA, US
Eli Reihman - San Diego CA, US
Scott M. Belliveau - San Diego CA, US
Katherine Yerre Koehler - Solana Beach CA, US
Nicholas Polytaridis - San Diego CA, US
Rian Draeger - San Diego CA, US
Jorge Valdes - San Diego CA, US
David Price - Carlsbad CA, US
Peter C. Simpson - Cardiff CA, US
Edward Sweeney - Poway CA, US

International Classification:

A61M 5/172
G16H 20/17
G16H 40/67
G16H 50/30
G16H 50/20
G16H 10/60
H04W 12/033

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.

US Patent:

20210260289, Aug 26, 2021

Filed:

Dec 7, 2020

Appl. No.:

17/114213

Inventors:

- San Diego CA, US
Derek James Escobar - Escondido CA, US
Sumitaka Mikami - San Diego CA, US
Hari Hampapuram - Portland OR, US
Benjamin Elrod West - San Diego CA, US
Nathanael Paul - Knoxville TN, US
Naresh C. Bhavaraju - San Diego CA, US
Michael Robert Mensinger - San Diego CA, US
Gary A. Morris - La Jolla CA, US
Andrew Attila Pal - San Diego CA, US
Eli Reihman - San Diego CA, US
Scott M. Belliveau - San Diego CA, US
Katherine Yerre Koehler - Solana Beach CA, US
Nicholas Polytaridis - San Diego CA, US
Rian Draeger - San Diego CA, US
Jorge Valdes - San Diego CA, US
David Price - Carlsbad CA, US
Peter C. Simpson - Cardiff CA, US
Edward Sweeney - Poway CA, US

International Classification:

A61M 5/172
A61M 5/142
G06N 20/20

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.