최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
DataON 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
Edison 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
Kafe 바로가기국가/구분 | United States(US) Patent 등록 |
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국제특허분류(IPC7판) |
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출원번호 | US-0436357 (2012-03-30) |
등록번호 | US-8721585 (2014-05-13) |
발명자 / 주소 |
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출원인 / 주소 |
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대리인 / 주소 |
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인용정보 | 피인용 횟수 : 0 인용 특허 : 332 |
Systems and methods for integrating a continuous glucose sensor, including a receiver, a medicament delivery device, and optionally a single point glucose monitor are provided. Manual integrations provide for a physical association between the devices wherein a user (for example, patient or doctor)
Systems and methods for integrating a continuous glucose sensor, including a receiver, a medicament delivery device, and optionally a single point glucose monitor are provided. Manual integrations provide for a physical association between the devices wherein a user (for example, patient or doctor) manually selects the amount, type, and/or time of delivery. Semi-automated integration of the devices includes integrations wherein an operable connection between the integrated components aids the user (for example, patient or doctor) in selecting, inputting, calculating, or validating the amount, type, or time of medicament delivery of glucose values, for example, by transmitting data to another component and thereby reducing the amount of user input required. Automated integration between the devices includes integrations wherein an operable connection between the integrated components provides for full control of the system without required user interaction.
1. An integrated system for monitoring and treating diabetes, the system comprising: a continuous glucose sensor, wherein the glucose sensor measures glucose in a host for a period exceeding one hour, and outputs a data stream, including one or more sensor data points generated at predetermined inte
1. An integrated system for monitoring and treating diabetes, the system comprising: a continuous glucose sensor, wherein the glucose sensor measures glucose in a host for a period exceeding one hour, and outputs a data stream, including one or more sensor data points generated at predetermined intervals;a receiver operably connected to the glucose sensor, wherein the receiver receives the data stream; anda medicament delivery device, wherein the delivery device is at least one of physically connected or operably connected to the receiver; wherein at least one of the receiver or the medicament delivery device comprises a processor module that determines, based on the data stream as input, at least one parameter of a medicament to be delivered via the medicament delivery device in an automated mode that does not require user interaction to administer medicament using the medicament delivery device, wherein the parameter is selected from the group consisting of a type of medicament, an amount of medicament, a timing of delivery of medicament, and combinations thereof, wherein the processor module triggers a semi-automated mode when a potential risk is identified, wherein in the semi-automated mode, the processor module requests a glucose concentration measurement from a single point glucose monitor and determines based on the glucose concentration measured by the single point glucose monitor as an input value, at least one parameter of a medicament to be delivered via the medicament delivery device. 2. The integrated system of claim 1, wherein glucose sensor comprises an enzyme membrane system for electrochemical detection of glucose and the single point glucose monitor comprises an enzyme membrane system for electrochemical detection of glucose. 3. The integrated system of claim 1, wherein the single point glucose monitor is operably connected to the receiver. 4. The integrated system of claim 1, wherein the single point glucose monitor is operably connected to the receiver by a wired connection. 5. The integrated system of claim 1, wherein the single point glucose monitor is operably connected to the receiver by a wireless connection. 6. The integrated system of claim 1, wherein the potential risk to the health of the host is identified based on an evaluation of a measured or estimated glucose concentration value of the host. 7. The integrated system of claim 1, wherein the potential risk to the health of the host is identified based on an evaluation of a measured or estimated rate of change of the glucose concentration of the host. 8. The integrated system of claim 1, wherein the potential risk to the health of the host is identified based on an evaluation of a measured or estimated acceleration of the glucose concentration of the host. 9. The integrated system of claim 1, wherein the potential risk is identified based on a mealtime event, an exercise event or a sleep event associated with the host. 10. The integrated system of claim 1, wherein the processor module identifies a dosing pattern of the host using a pattern recognition algorithm, wherein the potential risk is identified based on the identified dosing pattern. 11. The integrated system of claim 1, wherein the potential risk is identified by evaluating a discrepancy between a glucose concentration measured by the single point monitor and a glucose concentration measured by the continuous glucose sensor. 12. An integrated system for monitoring and treating diabetes, the system comprising: a continuous glucose sensor, wherein the glucose sensor measures glucose in a host for a period exceeding one hour, and outputs a data stream, including one or more sensor data points generated at predetermined intervals;a receiver operably connected to the glucose sensor, wherein the receiver receives the data stream; anda medicament delivery device, wherein the delivery device is at least one of physically connected or operably connected to the receiver, wherein the integrated system operates in a plurality of modes, the plurality of modes comprising: an automated mode that does not require user interaction to administer medicament using the medicament delivery device, wherein the system determines, based on the data stream as input, at least one parameter of a medicament to be delivered via the medicament delivery device in the automated mode;a semi-automated mode that requires user interaction to administer medicament using the medicament delivery device, wherein the system requests a glucose concentration measured by a single point glucose monitor and determines, using the glucose concentration as input, at least one parameter of a medicament to be delivered via the medicament delivery device in the semi-automated mode; andwherein the processor module operates the integrated system in the automated mode unless the semi-automated mode is triggered, wherein the semi-automated mode is automatically triggered responsive to the integrated system determining that a predetermined condition is met. 13. The integrated system of claim 12, wherein the processor module prompts the user for the biological sample in the semi-automated mode. 14. The integrated system of claim 12, wherein the predetermined condition is based on an evaluation of a clinical risk. 15. The integrated system of claim 12, wherein the predetermined condition is based on an evaluation of information manually inputted by a user into the receiver. 16. The integrated system of claim 12, wherein the predetermined condition is based on an evaluation of input associated with at least one of time of day, meals, sleep, calories, exercise or sickness. 17. The integrated system of claim 12, wherein the predetermined condition is adaptive over time. 18. The integrated system of claim 12, wherein the processor module learns a behavior pattern of the host, wherein the predetermined condition is based on the learned behavior pattern. 19. A method for monitoring and treating diabetes, the system comprising: receiving sensor data from a continuous glucose sensor the sensor data comprising one or more sensor data points;determining, using electronic circuitry, in an automated mode, at least one parameter of a medicament to be delivered via a medicament delivery device, wherein the parameter is selected from the group consisting of a type of medicament, an amount of medicament, a timing of delivery of medicament, and combinations thereof, wherein the at least one parameter is determined using the sensor data as an input value, wherein the automated mode administers medicament using the medicament delivery device without user interaction;triggering a semi-automated mode responsive to the processor module determining that a predetermined condition is met; anddetermining, using a processor module, in the semi-automated mode, at least one parameter of a medicament to be delivered via a medicament delivery device, wherein the parameter is selected from the group consisting of a type of medicament, an amount of medicament, a timing of delivery of medicament, and combinations thereof, wherein the at least one parameter is determined using a glucose concentration measured by a single point glucose monitor as an input value, wherein the semi-automated mode administers medicament using the medicament delivery device only after a user interaction confirms the medicament administration. 20. The method of claim 19, comprising evaluating at least one of a measured or estimated glucose concentration value of the host, a measured or estimated rate of change of the glucose concentration of the host or a measured or estimated acceleration of the glucose concentration of the host, wherein the predetermined condition is based on at least one of a measured or estimated glucose concentration value of the host, a measured or estimated rate of change of the glucose concentration of the host or a measured or estimated acceleration of the glucose concentration of the host. 21. The method of claim 19, wherein the predetermined condition is based on a mealtime event, an exercise event or a sleep event associated with the host. 22. The method of claim 19, comprising identifying a dosing pattern of the host using a pattern recognition algorithm, wherein the predetermined condition is based on the identified dosing pattern. 23. The method of claim 19, comprising evaluating a discrepancy between a glucose concentration measured by the single point monitor and a glucose concentration measured by the continuous glucose sensor, wherein the predetermined condition is based on the discrepancy. 24. The method of claim 19, comprising prompting the user for the biological sample in the semi-automated mode. 25. The method of claim 19, comprising evaluating a clinical risk, wherein the predetermined condition is based on the evaluation. 26. The method of claim 19, comprising evaluating information manually inputted by a user, wherein the predetermined condition is based on the evaluation. 27. The method of claim 19, wherein the predetermined condition is adaptive over time. 28. The method of claim 19, comprising learning a behavior pattern of the host, wherein the predetermined condition is based on the learned behavior pattern.
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