- Columbia MD, US Mansur SHOMALI - Columbia MD, US Abhimanyu KUMBARA - Columbia MD, US Anand IYER - Columbia MD, US Malinda PEEPLES - Columbia MD, US Michelle DUGAS - Columbia MD, US Kenyon CROWLEY - Columbia MD, US Guodong GAO - Columbia MD, US
Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.
Systems And Methods For Analyzing, Interpreting, And Acting On Continuous Glucose Monitoring Data
- Columbia MD, US Mansur SHOMALI - Columbia MD, US Abhimanyu KUMBARA - Columbia MD, US Anand IYER - Columbia MD, US Malinda PEEPLES - Columbia MD, US Michelle DUGAS - Columbia MD, US Kenyon CROWLEY - Columbia MD, US Guodong GAO - Columbia MD, US
Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.
Systems And Methods For Analyzing, Interpreting, And Acting On Continuous Glucose Monitoring Data
- Columbia MD, US Mansur SHOMALI - Columbia MD, US Abhimanyu KUMBARA - Columbia MD, US Anand IYER - Columbia MD, US Malinda PEEPLES - Columbia MD, US Michelle DUGAS - Columbia MD, US Kenyon CROWLEY - Columbia MD, US Guodong GAO - Columbia MD, US
Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.
Systems And Methods For Analyzing, Interpreting, And Acting On Continuous Glucose Monitoring Data
- Columbia MD, US Mansur SHOMALI - Ellicott City MD, US Abhimanyu KUMBARA - Columbia MD, US Anand IYER - Columbia MD, US Malinda PEEPLES - Columbia MD, US Michelle DUGAS - Columbia MD, US Kenyon CROWLEY - Columbia MD, US Guodong GAO - Columbia MD, US
Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.
Systems And Methods For Analyzing, Interpreting, And Acting On Continuous Glucose Monitoring Data
- Columbia MD, US Mansur SHOMALI - Ellicott City MD, US Abhimanyu KUMBARA - Columbia MD, US Anand IYER - Columbia MD, US Malinda PEEPLES - Columbia MD, US Michelle DUGAS - Columbia MD, US Kenyon CROWLEY - Columbia MD, US Guodong GAO - Columbia MD, US
Assignee:
Welldoc, Inc. - Columbia MD
International Classification:
A61B 5/145 A61B 5/00 A61B 5/11
Abstract:
Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.
Systems And Methods For Analyzing, Interpreting, And Acting On Continuous Glucose Monitoring Data
- Columbia MD, US Mansur SHOMALI - Ellicott City MD, US Abhimanyu KUMBARA - Columbia MD, US Anand IYER - Columbia MD, US Malinda PEEPLES - Columbia MD, US Michelle DUGAS - Columbia MD, US Kenyon CROWLEY - Columbia MD, US Guodong GAO - Columbia MD, US
Assignee:
Welldoc, Inc. - Columbia MD
International Classification:
A61B 5/145 A61B 5/00 G16H 50/30
Abstract:
Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.
Database Management And Graphical User Interfaces For Measurements Collected By Analyzing Blood
- Columbia MD, US Hari KESANI - Columbia MD, US Anand IYER - Potomac MD, US Gabriel SUSAI - Ellicott City MD, US Mansur SHOMALI - Ellicott City MD, US Prasad Matti RAO - Ellicott City MD, US
WellDocs President and COO Anand Iyer noted that people with diabetes could have three to five times the likelihood of getting into an accident if they have a hypoglycemic episode while behind the wheel. As a result, alerting drivers to potentially hazardous glucose levels and prompting them to boo
Date: May 19, 2011
Category: Health
Source: Google
Ford Wants Your Next Car to Monitor Your Vital Signs as You Drive
trials in which diabetic patients show marked improvement simply through this sort of additional monitoring. Putting that interface in a car, everyones private, captive sanctuary, could be another way to keep patients connected, said Anand Iyer, the company's president and chief operating officer.