Sensor model supervisor for a closed-loop insulin infusion system
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
A61M-005/172
A61M-005/142
A61B-005/00
A61B-005/145
G06F-019/00
G16H-020/17
출원번호
US-0138540
(2016-04-26)
등록번호
US-10130767
(2018-11-20)
발명자
/ 주소
Grosman, Benyamin
Wu, Di
Roy, Anirban
Parikh, Neha J.
출원인 / 주소
Medtronic MiniMed, Inc.
대리인 / 주소
Lorenz & Kopf, LLP
인용정보
피인용 횟수 :
0인용 특허 :
206
초록▼
An insulin infusion device includes a processor architecture, and a memory element that stores executable instructions to perform a method of controlling delivery of insulin to a user. The method operates the device in a closed-loop mode to deliver insulin, obtains patient-specific parameters for a
An insulin infusion device includes a processor architecture, and a memory element that stores executable instructions to perform a method of controlling delivery of insulin to a user. The method operates the device in a closed-loop mode to deliver insulin, obtains patient-specific parameters for a current time sample, and estimates a plasma insulin value and a blood glucose value for the user based on at least some of the patient-specific parameters. The estimating is also based on a previously estimated plasma insulin value obtained for a previous time sample, and a previously estimated blood glucose value obtained for the previous time sample. A predicted sensor glucose value is generated for the current time sample, and the closed-loop mode or a safe basal mode is selected for controlling operation of the insulin infusion device in accordance with the selected mode.
대표청구항▼
1. An insulin infusion device comprising: a reservoir for insulin to be delivered from the insulin infusion device to a body of a user;a processor architecture comprising at least one processor device; andat least one memory element associated with the processor architecture, the at least one memory
1. An insulin infusion device comprising: a reservoir for insulin to be delivered from the insulin infusion device to a body of a user;a processor architecture comprising at least one processor device; andat least one memory element associated with the processor architecture, the at least one memory element storing processor-executable instructions that, when executed by the processor architecture, perform a method of controlling delivery of insulin from the insulin reservoir to the body of the user, the method comprising: automatically operating the insulin infusion device in a closed-loop mode to deliver insulin from the insulin reservoir to the body of the user;obtaining, for a current time sample, a patient-specific insulin gain value (KI), a patient-specific fasting insulin basal rate value (IBasal), a patient-specific fasting blood glucose value (SGBase), a meter blood glucose value (MBG), and an insulin delivered value (Iin) that represents an amount of insulin delivered since a preceding time sample;estimating, for the current time sample, an estimated plasma insulin value (Ipt) and an estimated blood glucose value (Gt) for the user, the estimating based on at least some of the values of KI, IBasal, SGBase, MBG, and (Iin), and the estimating further based on a previously estimated plasma insulin value obtained for a previous time sample (Ipt-1), and a previously estimated blood glucose value obtained for the previous time sample (Gt-1);generating, for the current time sample, a predicted sensor glucose value (SGp) for the user, the generating based on the values of Gt and SGBase for the current time sample;selecting between the closed-loop mode, a first safe basal mode, or a second safe basal mode, based on at least some of the values of SGp, SG, Ipt, and Gt for the current time sample, the first safe basal mode representing a higher basal rate of insulin relative to the second safe basal mode; andcontrolling operation of the insulin infusion device to deliver insulin to the body of the user in accordance with the selected mode;wherein the closed-loop mode is selected in response to detecting a sensor over-reading condition, the first safe basal mode is selected only in response to detecting a sensor under-reading condition, and the second safe basal mode is selected only in response to detecting a sensor under-reading condition; andwherein the second safe basal mode, rather than the first safe basal mode, is selected when: a temporary target glucose value is raised to a threshold set point value; or SGp is below a specified low glucose threshold; or Ipt is above a specified typical basal rate. 2. The insulin infusion device of claim 1, wherein the method performed by the processor architecture further comprises: calculating a difference (SGpThDiff) between the predicted sensor glucose value (SGp) and a low threshold value in accordance with the expression: SGpThDiff=SGp−Low Threshold, wherein the second safe basal mode is selected when SGpThDiff<0. 3. The insulin infusion device of claim 1, wherein the method performed by the processor architecture further comprises: collecting, during a predetermined period of time, MBG values, sensor glucose (SG) values from a continuous glucose sensor, meal-related data, insulin history data, and total daily insulin data associated with the user; andcalculating, for each predetermined period of time, the values of KI, IBasal, and SGBase, the calculating based on at least some of the collected MBG values, SG values, meal-related data, insulin history data, and total daily insulin data. 4. The insulin infusion device of claim 3, wherein the method performed by the processor architecture further comprises: searching the SG values for a fasting glucose value for the user, wherein the values of IBasal and SGBase are calculated based on an identified fasting glucose value. 5. The insulin infusion device of claim 1, wherein: IBasal represents an estimated basal rate needed to maintain the fasting blood glucose value (SGBase) for the user; andSGBase represents an estimated fasting blood glucose value for the user when insulin is delivered at the fasting insulin basal rate value (IBasal). 6. The insulin infusion device of claim 1, wherein the method performed by the processor architecture further comprises: resetting the value of Gt-1 with each new value of MBG in accordance with the expression: Gt-1=MBG SGBase. 7. The insulin infusion device of claim 1, wherein the method performed by the processor architecture further comprises: processing at least some of the values of SGp, SG, Ipt, and Gt for the current time sample to detect the sensor under-reading condition. 8. An insulin infusion system comprising: a continuous glucose sensor that generates sensor data indicative of sensor glucose values (SG) for a user; andan insulin infusion device coupled to receive the sensor data generated by the continuous glucose sensor, the insulin infusion device comprising an insulin reservoir for insulin to be delivered from the insulin infusion device to the user, a processor architecture comprising at least one processor device and further comprising at least one memory element associated with the processor architecture, the at least one memory element storing processor-executable instructions that, when executed by the processor architecture, cause the insulin infusion device to perform a method comprising:automatically operating the insulin infusion device in a closed-loop mode to deliver insulin from the insulin reservoir to the body of the user;obtaining, for a current time sample, a patient-specific insulin gain value (KI), a patient-specific fasting insulin basal rate value (IBasal), a patient-specific fasting blood glucose value (SGBase), a meter blood glucose value (MBG), and an insulin delivered value (Iin) that represents an amount of insulin delivered since a preceding time sample;estimating, for the current time sample, an estimated plasma insulin value (Ipt) and an estimated blood glucose value (Gt) for the user, the estimating based on at least some of the values of KI, IBasal, SGBase, MBG, and (Iin), and the estimating further based on a previously estimated plasma insulin value obtained for a previous time sample (Ipt-1), and a previously estimated blood glucose value obtained for the previous time sample (Gt-1);generating, for the current time sample, a predicted sensor glucose value (SGp) for the user, the generating based on the values of Gt and SGBase for the current time sample;selecting between the closed-loop mode, a first safe basal mode, or a second safe basal mode, based on at least some of the values of SGp, SG, Ipt, and Gt for the current time sample, the first safe basal mode representing a higher basal rate of insulin relative to the second safe basal mode; andcontrolling operation of the insulin infusion device to deliver insulin to the body of the user in accordance with the selected mode;wherein the closed-loop mode is selected in response to detecting a sensor over-reading condition, the first safe basal mode is selected only in response to detecting a sensor under-reading condition, and the second safe basal mode is selected only in response to detecting a sensor under-reading condition; andwherein the second safe basal mode, rather than the first safe basal mode, is selected when: a temporary target glucose value is raised to a threshold set point value; or SGp is below a specified low glucose threshold; or Ipt is above a specified typical basal rate. 9. The system of claim 8, wherein the method performed by the processor architecture further comprises: collecting, during a predetermined period of time, MBG values, sensor glucose (SG) values from a continuous glucose sensor, meal-related data, insulin history data, and total daily insulin data associated with the user; andcalculating, for each predetermined period of time, the values of KI, IBasal, and SGBase, the calculating based on at least some of the collected MBG values, SG values, meal-related data, insulin history data, and total daily insulin data. 10. The system of claim 8, wherein: IBasal represents an estimated basal rate needed to maintain the fasting blood glucose value (SGBase) for the user; andSGBase represents an estimated fasting blood glucose value for the user when insulin is delivered at the fasting insulin basal rate value (IBasal). 11. The system of claim 8, wherein the method performed by the processor architecture further comprises: resetting the value of Gt-1 with each new value of MBG in accordance with the expression: Gt-1=MBG−SGBase. 12. The system of claim 8, wherein the method performed by the processor architecture further comprises: processing at least some of the values of SGp, SG, Ipt, and Gt for the current time sample to detect the sensor under-reading condition. 13. A method of operating an insulin infusion device to regulate delivery of insulin to a body of a user, the method comprising: obtaining, from a continuous glucose sensor, sensor glucose (SG) values for the user;calculating, from the obtained SG values, a patient-specific fasting insulin basal rate value (IBasal) and a patient-specific fasting blood glucose value (SGBase), wherein IBasal represents an estimated basal rate needed to maintain SGBase for the user, and wherein SGBase represents an estimated fasting blood glucose value for the user when insulin is delivered at IBasal;using the values of IBasal and SGBase to calculate, for a current time sample, an estimated plasma insulin value (I p t) and an estimated blood glucose value (Gt) for the user; andusing the values of Ipt, Gt, SGBase, and SG to select between a closed-loop mode of operation, a safe nominal basal mode of operation, or a safe low basal mode of operation for the insulin infusion device the safe nominal basal mode of operation representing a higher basal rate of insulin relative to the safe low basal mode of operation; andautomatically operating the insulin infusion device to control delivery of insulin from the insulin infusion device to the body of the user, in accordance with the selected mode of operation;wherein the closed-loop mode of operation is selected in response to detecting a sensor over-reading condition, the safe nominal basal mode of operation is selected only in response to detecting a sensor under-reading condition, and the safe low basal mode of operation is selected only in response to detecting a sensor under-reading condition; andwherein the safe low basal mode of operation, rather than the safe nominal basal mode of operation, is selected when: a temporary target glucose value is raised to a threshold set point value; or a predicted sensor glucose value (SGp) is below a specified low glucose threshold; or Ipt is above a specified typical basal rate. 14. The method of claim 13, further comprising: processing at least some of the values of Ipt, Gt, SGBase, and SG for the current time sample to detect the sensor under-reading condition.
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이 특허에 인용된 특허 (206)
Batina, William P.; White, Robert M., Acquisition circuit for cardiac pacer.
Schulman Joseph H. ; Lucisano Joseph Y. ; Shah Rajiv ; Byers Charles L. ; Pendo Shaun M., Alumina insulation for coating implantable components and other microminiature devices.
Tune Joel (Antioch IL) Anderson Robert L. (Boulder CO) Blankenship Larry (Boulder CO) Colesworthy ; III Daniel C. (Boulder CO) Heim Warren P. (Boulder CO) Miller ; III Scott A. (Boulder CO) Sherman B, Ambulatory infusion pump.
Coutr James E. (Concord MA) Griffin Wayne P. (Dracut MA) Crisler Charles M. (Windham NH), An infusion management and pumping system having an alarm handling system.
Say James ; Tomasco Michael F. ; Heller Adam ; Gal Yoram,ILX ; Aria Behrad ; Heller Ephraim ; Plante Phillip John ; Vreeke Mark S. ; Friedman Keith A. ; Colman Fredric C., Analyte monitoring device and methods of use.
Steil, Garry M.; Rebrin, Kerstin; Goode, Jr., Paul V.; Mastrototaro, John J.; Purvis, Richard E.; Van Antwerp, William P.; Shin, John J.; Talbot, Cary D., Closed loop system for controlling insulin infusion.
Prestele Karl (Erlangen DEX) Franetzki Manfred (Uttenreuth DEX) Reif Erich (Erlangen DEX), Device for the infusion of fluids into the human or animal body.
Say James ; Tomasco Michael F. ; Heller Adam ; Gal Yoram,ILX ; Aria Behrad ; Heller Ephraim ; Plante Phillip John ; Vreeke Mark S., Electrochemical analyte.
James Say ; Michael F. Tomasco ; Adam Heller ; Yoram Gal IL; Behrad Aria ; Ephraim Heller ; Phillip John Plante ; Mark S. Vreeke, Electrochemical analyte sensor.
Zhuang, Zhiming; Alberth, Jr., William P.; Foo, Ken K., Electronic device and method for determining a touch input applied to a capacitive touch panel system incorporated therein.
Gibson, Scott R.; Shah, Rajiv; Chernoff, Edward; Byers, Charles, Electronic lead for a medical implant device, method of making same, and method and apparatus for inserting same.
Gregg Brian A. (13940 Braun Dr. Golden CO 80401) Heller Adam (5317 Valburn Cir. Austin TX 78731) Kerner Wolfgang (Universitat Zu Lubeck ; Klinik Fur Innerere Medizin ; Razeburger Allee 160 D-2400 Lub, Enzyme electrodes.
Gregg Brian A. (13940 Braun Dr. Golden CO 80401) Heller Adam (5317 Valburn Cir. Austin TX 78731) Kerner Wolfgang (Universitat zu Lubeck ; Klinik fur Innerere Medizin ; Razeburger Allee 160 D-2400 Lub, Enzyme electrodes.
Lord Peter C. (Santa Clarita CA) Van Antwerp William P. (Brentwood CA) Mastrototaro John J. (Los Angeles CA) Cheney ; II Paul S. (Beverly Hills CA) Schnabel Nannette M. (Valencia CA), Flex circuit connector.
Dempsey Michael K. (Acton MA) Kotfila Mark S. (Chelmsford MA) Snyder Robert J. (Westford MA), Flexible patient monitoring system featuring a multiport transmitter.
Schulman Joseph H. (Santa Clarita CA) Rule ; III Orville R. (Los Angeles CA) Whitmoyer David I. (Los Angeles CA) Lebel Ronald J. (Sherman Oaks CA) Lucisano Joseph Y. (Saugus CA) Mann Alfred E. (Bever, Glucose monitoring system.
Schulman Joseph H. (Santa Clarita CA) Rule ; III Orville Rey (Los Angeles CA) Whitmoyer David I. (Los Angeles CA) Lebel Ronald J. (Sherman Oaks CA) Lucisano Joseph Y. (Saugus CA) Mann Alfred E. (Beve, Glucose sensor assembly.
McIvor, K. Collin; Cabernoch, James L.; Branch, Kevin D.; Van Antwerp, Nannette M.; Halili, Edgardo C.; Mastrototaro, John J., Glucose sensor package system.
Allen Douglas J. (Indianapolis IN) Johnson Kirk W. (Indianapolis IN) Nevin Robert S. (Indianapolis IN), Hydrophilic polyurethane membranes for electrochemical glucose sensors.
Schulman Joseph H. ; Byers Charles L. ; Adomian Gerald E. ; Colvin Michael S., Implantable enzyme-based monitoring systems having improved longevity due to improved exterior surfaces.
Wilson George S. (Lawrence KS) Bindra Dilbir S. (Lawrence KS) Hill Brian S. (Lawrence KS) Thevenot Daniel R. (Paris Cedex FRX) Sternberg Robert (Thiais FRX) Reach Gerard (Paris Cedex KS FRX) Zhang Ya, Implantable glucose sensor.
Meadows, Paul M.; Mann, Carla M.; Tsukamoto, Hisashi; Chen, Joey, Implantable pulse generators using rechargeable zero-volt technology lithium-ion batteries.
Gargano Diane A. ; Flachbart Eric J. ; Cowen Barry ; Duh Monica ; Rudser ; Jr. John L. ; Zhen Ken ; Noble Lynn ; Warhurst Julian ; Pedraza Luis, Infusion pump for at least one syringe.
Coutre James E. (114 Stone Root La. Concord MA 01742) Griffin Wayne P. (55 Surrey La. Dracut MA 01826) Crisler Charles M. (10 Sunridge Rd. Windham NH 03087), Infusion pump management system for suggesting an adapted course of therapy.
Causey ; III James D. (Simi Valley CA) Schloss Harold C. (Los Angeles CA) Snell Jeffery D. (Northridge CA), Interactive programming and diagnostic system for use with implantable pacemaker.
Say, James L.; Sakslund, Henning; Tomasco, Michael F.; Audett, Jay D.; Cho, Hyun; Yamasaki, Duane O.; Heller, Adam, Mass transport limited in vivo analyte sensor.
Castellano Thomas P. (Beverly Hills CA) Schumacher Robert (Beverly Hills CA), Medication delivery device with a microprocessor and characteristic monitor.
Colman Fredric C. (Granada Hills CA) Purvis Richard E. (Glendale CA), Medication infusion system having optical motion sensor to detect drive mechanism malfunction.
Peterson Bruce A. (Milwaukie OR) Hogard Michael E. (Oregon City OR) Johnson Harley D. (Portland OR) Kelly Thomas D. (Portland OR) Long Jean M. (Portland OR) Preston ; Jr. William G. (Portland OR), Method and apparatus for kidney dialysis.
Joseph H. Schulman ; Joseph Y. Lucisano ; Rajiv Shah ; Charles L. Byers ; Shaun M. Pendo, Method of applying insulation for coating implantable components and other microminiature devices.
Feldman, Benjamin J.; Heller, Adam; Heller, Ephraim; Mao, Fei; Vivolo, Joseph A.; Funderburk, Jeffery V.; Colman, Fredric C.; Krishnan, Rajesh, Method of using a small volume in vitro analyte sensor with diffusible or non-leachable redox mediator.
Moberg, Sheldon B.; Causey, III, James D.; Bare, Rex O.; Scherer, Andrew J.; Sargent, Bradley J., Methods, apparatuses, and uses for infusion pump fluid pressure and force detection.
Brown Stephen J. ; Jensen Erik K., On-line health education and feedback system using motivational driver profile coding and automated content fulfillment.
Roizen Michael (Chicago IL) Turcotte ; II William E. (Oak Park IL) Pfisterer Richard E. (Arlington Heights IL), Portable medical interactive test selector having plug-in replaceable memory.
Say James ; Tomasco Michael F. ; Heller Adam ; Gal Yoram,ILX ; Aria Behrad ; Heller Ephraim ; Plante Phillip John ; Vreeke Mark S., Process for producing an electrochemical biosensor.
Livingston John H. (Los Angeles CA) Frye Ward K. (San Luis Obispo CA) Field Jeffrey F. (Northridge CA), Proctective case for a medication infusion pump.
Sancoff Gregory E. (Leucadia CA) McWilliams Mark (San Diego CA) Barr Howard S. (Escondido CA) Cordner ; Jr. Edward T. (Carlsbad CA) Barton Russell C. (Monrovia CA), Programmable infusion system.
Shin, John J.; Holtzclaw, Kris R.; Dangui, Nandita D.; Kanderian, Jr., Sami; Mastrototaro, John J.; Hong, Peter I., Real time self-adjusting calibration algorithm.
Langen Pauline A. (Simsbury CT) Katz Jeffrey S. (West Hartford CT) Dempsey Gayle (Needham MA) Pompano James (East Haven CT), Remote monitoring of high-risk patients using artificial intelligence.
Epstein Paul (Brookline MA) Petschek Harry (Lexington MA) LaWhite Eric (South Royalton VT) Strohl Clair (Norfolk MA) Coyne Henry (Framington MA) Kaleskas Edward (Jefferson MA) Adaniya George (Swampsc, Remotely programmable infusion system.
Lundquist Ingemar H. (Pebble Beach CA) Tarczy-Hornoch Zoltan (Berkeley CA) Kardos Thomas J. (Laguna Beach CA), Retroperfusion and retroinfusion control apparatus, system and method.
Liamos, Charles T.; Feldman, Benjamin J.; Funderburk, Jeffery V.; Krishnan, Rajesh; Plante, Phillip John; Vivolo, Joseph A.; Jin, Robert Y.; Cloud, Michael S., Small volume in vitro analyte sensor and methods.
Liamos, Charles T.; Feldman, Benjamin J.; Funderburk, Jeffery V.; Krishnan, Rajesh; Plante, Phillip John; Vivolo, Joseph A.; Jin, Robert Y.; Cloud, Michael S., Small volume in vitro analyte sensor and methods.
Nason Clyde K. (25745 N. Player Dr. Valencia CA 91355) Culp Gordon W. (13832 Haynes St. Van Nuys CA 91401), Solenoid drive apparatus for an external infusion pump.
Aoki Thomas T. (1021 El Sur Way Sacramento CA 95825), System and method for treating animal body tissues to improve the dietary fuel processing capabilities thereof.
Tacklind Christopher A. (Palo Alto CA) Sanders Matthew H. (Los Altos Hills CA) Walne Geoffrey B. (Atherton CA), System for monitoring and reporting medical measurements.
Blomquist Michael L. (Coon Rapids MN) Peterson Thomas L. (Shoreview MN), Systems and methods for operating ambulatory medical devices such as drug delivery devices.
Mann, Alfred E.; Purvis, Richard E.; Mastrototaro, John J.; Causey, James D.; Henke, James; Hong, Peter; Livingston, John H.; Hague, Clifford W.; Hite, Brad T., Telemetered characteristic monitor system and method of using the same.
Lord Peter C. (Santa Clarita CA) Van Antwerp William P. (Brentwood CA) Mastrototaro John J. (Los Angeles CA) Cheney ; II Paul S. (Beverly Hills CA) Schnabel Nannette M. (Valencia CA), Transcutaneous sensor insertion set.
Gerety, Eugene P.; Strempski, Richard A.; Sardi, Stephen G., Two-dimensional printed code for storing biometric information and integrated off-line apparatus for reading same.
Carter,Scott J.; Flanders,Edward L.; Hannah,Stephen E., Wireless LAN architecture for integrated time-critical and non-time-critical services within medical facilities.
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