DFS - Diabetes Forecast System

Diabetes Forecast System
Blood Glucose Level Measuring Technology


Conclusions
Final Status The current version of DFS (3.0) is only a preliminary version that shows the feasible interface of the device; most critical functions are working except the prediction model and actual reading of the blood glucose level (BGL). Users can record their exercise, diet, and BGL reading (assume they used other device than DFS because DFS is not physically capable of reading BGL now) and save them for future use, which is the prediction. Ideally, the prediction will change every time with different type of meal, different period of exercise, and different amount of dose of insulin. This is why DFS records all the data in each section and time after performing the tasks. The data in the History section (represented by the magnifying glass) is supposed to be used to make the prediction of BGL level over time. Right now, the DFS 3.0 has a random prediction that changes every time the exercise, diet, insulin, and BGL reading is recorded; this is to show that in the real working version the prediction should have actually changed. As for now, DFS 3.0 is not ready for public release. Future Work and Recommendations The future possible tasks for DFS would be mainly the actual implementation of the prediction model and the ability of reading BGL for the device. We believe that the Markov chains would be a feasible option for the prediction model. Currently, Markov chains are used for predicting weather conditions, and are the basis for Google's PageRank algorithm (http://en.wikipedia.org/wiki/Markov_chain). With further study and alternation, DFS would adopt a working model and be able to predict users’ BGL. Several different versions of DFS's interface have been developed, right now we have the data needed for translating DFS from English to Spanish, Chinese, and Japanese. Here is an example chart of corresponding terms in English and Chinese/Japanese: As for recommendations, the myLife group has developed a very nice project that tracks personal diet information; we would like to cooperate with them to further improve the diet tracking function for the DFS device. We were also impressed by the DDAS (Diabetes Diabetic Analysis Software) group's project. They developed an interface on the web that users could upload information to about diet, exercise and insulin intake (not to mention BGL readings) in order to pass this along to doctors. What's required is to have a glucometer such as ours to record those types of information in order to be uploaded. Also, it is crucial to conduct more usability tests in the future as we add new capabilities such as new language supports.

Conclusions

Final Status

The current version of DFS (3.0) is only a preliminary version that shows the feasible interface of the device; most critical functions are working except the prediction model and actual reading of the blood glucose level (BGL). Users can record their exercise, diet, and BGL reading (assume they used other device than DFS because DFS is not physically capable of reading BGL now) and save them for future use, which is the prediction. Ideally, the prediction will change every time with different type of meal, different period of exercise, and different amount of dose of insulin. This is why DFS records all the data in each section and time after performing the tasks. The data in the History section (represented by the magnifying glass) is supposed to be used to make the prediction of BGL level over time. Right now, the DFS 3.0 has a random prediction that changes every time the exercise, diet, insulin, and BGL reading is recorded; this is to show that in the real working version the prediction should have actually changed. As for now, DFS 3.0 is not ready for public release.

Future Work and Recommendations

The future possible tasks for DFS would be mainly the actual implementation of the prediction model and the ability of reading BGL for the device. We believe that the Markov chains would be a feasible option for the prediction model. Currently, Markov chains are used for predicting weather conditions, and are the basis for Google's PageRank algorithm (http://en.wikipedia.org/wiki/Markov_chain). With further study and alternation, DFS would adopt a working model and be able to predict users’ BGL.

Several different versions of DFS's interface have been developed, right now we have the data needed for translating DFS from English to Spanish, Chinese, and Japanese. Here is an example chart of corresponding terms in English and Chinese/Japanese:

As for recommendations, the myLife group has developed a very nice project that tracks personal diet information; we would like to cooperate with them to further improve the diet tracking function for the DFS device. We were also impressed by the DDAS (Diabetes Diabetic Analysis Software) group's project. They developed an interface on the web that users could upload information to about diet, exercise and insulin intake (not to mention BGL readings) in order to pass this along to doctors. What's required is to have a glucometer such as ours to record those types of information in order to be uploaded. Also, it is crucial to conduct more usability tests in the future as we add new capabilities such as new language supports.