Advisory System
Cheetah advisory system
Prelude
Cheetah will generatie advice about insulin dosis or food intake. Several software packages offer this kind of functionality, but none of them an advice as personal as Cheetah will. The system learns from the user and learns how its body reacts on events such as insulin usage, food comsumption and activitivies like sports. The generated KB about the user is then shared (anonymously) with other users over the internet. Likewise, the user receives knowledge from other users. And this is exactly what makes cheetah unique: it will be the first diabetes software that doesnt just learn from one isolated user, but learns from all. This combined with a smart knowledge inferencing system will add up to a complete diabetes health system.
Advice
Three types of advice can hypothetically be generated. The first one is short-term, and gives advice about today. The second one tackles long-term problems and generates modifications to the current food/insulin diet. The third kind of advice generates a complete diet for you. [Type A is a must for Cheetah, while types B and C are optional at the moment]
Type A Advice
Examples:
- Ann wants to eat grandma's pie. Give her current glucose level, she wants insulin advice to prevent a hyper.
- Ann will exercise in 2 ours, and wants food advice to prevent a hypo.
Advice Features:
- Advice is generated about insulin dosis or food intake about today (max. 24h ahead).
Steps:
- The user asks for short-term advice
- The system presents a scheme on which the user fills in today's future insulin or food intake. (Needs a intuitive and easy UI which allows the user to choose default values). The user can fill in "?" which are events to be advised.
- Cheetah puts these things into his model and sees how to fill in the ?'s to make the glucose prediction as stable as possible.
- Cheetah presents the advise.
Type B Advice
Examples:
- Ann always has a hypo at night. She wants advice to prevent this to happen again.
- Ann always has a hyper in the evening. She wants advice to prevent his to happen again.
Advice Features:
- Advice is generated not only for today, but is more general. Unlike type A, the (hypo/hyper) problem is recurrent.
Steps:
- The user (and cheetah) spots a hypo/hyper problem and wants a solution.
- Cheetah searches what causes the recurrent problem.
- Cheetah presents the cause and gives advice how to solve this.
Type C Advice
Examples:
- Pete has very much hypo's and hypers and wants the systeem to make a compleet food diet for him.
- Pete goes on a food diet and asks the system to make a new insulin advise for him.
Advice Features:
- Advice consists of a complete new personal diet, generated from scratch.
Steps:
- [This is a stub] System makes everything a variable and optimizes the curve.