Algorithm sensor augmented bolus estimator for semi-closed loop infusion system

• US 7,547,281 B2
• Filed: 12/30/2005
• Issued: 06/16/2009
• Est. Priority Date: 02/01/2005
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Clark, H. Bud, Wu, Bihong, Moberg, Sheldon B., Mastrototaro, John J., Tolle, Mike Charles Vallet, Mueller, John C. Jr., Steil, Garry M., Williams, Gary L., Hayes, Andrew C.
• Primary Examiner(s): Marmor, II; Charles A
• Assistant Examiner(s): Natnithithadha; Navin
• Application Number:
  US11/322,489
• Publication Number:
  US 20060173406A1
• Time in Patent Office: 1,264 Days
• Field of Search: 600/309, 600345-366, 604 65- 67, 604/31, 604/522, 604/503, 604/504
• US Class Current: 600/365
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/7239 using differentiation including higher order derivatives
• CPC Class Codes: A61M 2005/14208 with a programmable infusion control system, characterised by the infusion program
• CPC Class Codes: A61M 2205/18 with alarm
• CPC Class Codes: A61M 2205/35 Communication
• CPC Class Codes: A61M 2230/005 Parameter used as control input for the apparatus
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

An infusion system is for infusing a fluid into the body of a patient. The infusion system includes at least one sensor for monitoring blood glucose concentration of the patient and an infusion device for delivering fluid to the patient. The sensor produces at least one sensor signal input. The infusion device uses the at least one sensor signal input and a derivative predicted algorithm to determine future blood glucose levels. The infusion device delivers fluid to the patient when future blood glucose levels are in a patient'"'"'s target range. The infusion device is capable of suspending and resuming fluid delivery based on future blood glucose levels and a patient'"'"'s low shutoff threshold. The infusion device suspends fluid delivery when future blood glucose levels falls below the low shutoff threshold. The infusion device resumes fluid delivery when a future blood glucose level is above the low shutoff threshold.

Claims

1. An infusion system for infusing a fluid into the body of a patient, the infusion system comprising:

at least one sensor for monitoring blood glucose concentration of the patient, wherein the sensor produces at least one sensor signal input; and

an infusion device for delivering fluid to the patient,

wherein the infusion device uses the at least one sensor signal input and a derivative predicted algorithm to determine future blood glucose levels,

the derivative predicted algorithm calculates a first derivative of a sensor current sample from the at least one sensor signal input at time period n, and then calculates a first derivative of a sensor glucose value from the at least one sensor signal input using the first derivative of the sensor current sample to determine future blood glucose levels,

the infusion device is capable of automatically suspending and resuming fluid delivery based on future blood glucose levels and the patient'"'"'s predefined low shutoff threshold, and

the infusion device recommends more fluid delivery based on a positive derivative from the derivative predicted algorithm, and the infusion device recommends less fluid delivery based on a negative derivative from the derivative predicted algorithm.

2. The system according to claim 1, wherein the infusion device delivers fluid to the patient when future blood glucose levels are in the patient'"'"'s predefined target range.

3. The system according to claim 1, wherein the infusion device automatically suspends fluid delivery when a future blood glucose level falls below the predefined low shutoff threshold.

4. The system according to claim 1, wherein the infusion device automatically resumes fluid delivery when a future blood glucose level is above the predefined low shutoff threshold.

5. The system according to claim 1, wherein the predefined low shutoff threshold is always above the infusion system'"'"'s lowest shutoff threshold.

6. The system according to claim 1, wherein the infused fluid is insulin.

7. The system according to claim 1, wherein the infusion system further includes an alarm to provide alerts to the patient.

8. The system according to claim 7, wherein the patient selects at least one alarm to activate, wherein the at least one alarm includes an audible alarm for providing audible alerts, a vibration alarm for providing tactile alert, and a visual alarm for providing visual alerts.

9. The system according to claim 1, wherein the derivative predicted algorithm utilizes at least one of current blood glucose concentrations, meal carbohydrate content, sensor current sample at time period n, system calibration factor, and insulin-on-board at time period n.

10. The system according to claim 1, wherein the first derivative of the sensor current sample is calculated from a slope of the sensor current sample versus time using a Savitzky-Golay finite impulse response filter.

11. An infusion system for infusing a fluid into the body of a patient, the infusion system comprising:

at least one sensor for monitoring blood glucose concentration of the patient, wherein the sensor produces at least one sensor signal input; and

an infusion device for delivering fluid to the patient,

wherein the infusion device uses the at least one sensor signal input and a derivative predicted algorithm to determine future blood glucose levels,

the derivative predicted algorithm calculates a first derivative of a sensor current sample from the at least one sensor signal input at time period n, and then calculates a first derivative of a sensor glucose value from the at least one sensor signal input using the first derivative of the sensor current sample to determine future blood glucose levels,

the infusion device is capable of automatically suspending and resuming fluid delivery based on future blood glucose levels and the patient'"'"'s predefined low shutoff threshold, and

the infusion device recommends a particular type of bolus for delivery based on the derivative predicted algorithm.

12. The system according to claim 11, wherein the particular type of bolus is selected from the group consisting of a dual wave bolus and a square wave bolus.

13. The system according to claim 11, wherein the infusion device delivers fluid to the patient when future blood glucose levels are in the patient'"'"'s predefined target range.

14. The system according to claim 11, wherein the infusion device automatically suspends fluid delivery when a future blood glucose level falls below the predefined low shutoff threshold.

15. The system according to claim 11, wherein the infusion device automatically resumes fluid delivery when a future blood glucose level is above the predefined low shutoff threshold.

16. The system according to claim 11, wherein the predefined low shutoff threshold is always above the infusion system'"'"'s lowest shutoff threshold.

17. The system according to claim 11, wherein the infused fluid is insulin.

18. The system according to claim 11, wherein the infusion system further includes an alarm to provide alerts to the patient.

19. The system according to claim 18, wherein the patient selects at least one alarm to activate, wherein the at least one alarm includes an audible alarm for providing audible alerts, a vibration alarm for providing tactile alert, and a visual alarm for providing visual alerts.

20. The system according to claim 11, wherein the derivative predicted algorithm utilizes at least one of current blood glucose concentrations, meal carbohydrate content, sensor current sample at time period n, system calibration factor, and insulin-on-board at time period n.

21. The system according to claim 11, wherein the first derivative of the sensor current sample is calculated from a slope of the sensor current sample versus time using a Savitzky-Golay finite impulse response filter.