Diabetes management app | Innovations

Diabetes management app

Diabetes management app

Updated 16 May 2013, 15:08 AEST

BlueClover is a mobile phone app which does away with manual record-keeping for diabetics

DESLEY BLANCH :  Three final year information technologies students have combined their talents to create a mobile phone app to help diabetics better manage their condition.

One student Andrew Chen knows firsthand the difficulties that face diabetics from observing both his father and grandmother deal with the disease.

Andrew and his University of Sydney co-developers Donald Zhang and Robin Huang designed the BlueClover mobile phone app to replace the current manual method that diabetics use for tracking their daily food and beverage intake. They believe their method will make life much easier for the 347 million people affected by diabetes.

The three won the Microsoft Asian Cup with their mobile phone app BlueClover and were invited to represent Australia in Delhi, India to showcase their technology at the annual Board of Governors of the Asian Development Bank Forum last week as contestants in their “Apps for Asia” program.

BlueClover was one of Australia’s top three apps showcased, along with the top 3 apps from Korea, Malaysia, India and the Philippines.  Andrew Chen was surprised to find they were the only students invited to showcase their technology.

ANDREW CHEN : The amount of feedback we received from the visitors was certainly overwhelming, especially in a country like India where diabetes is quickly becoming a huge problem.  It was also great to see our achievement as we were the only team of students, whereas the other teams consisted of independent software developers.

DESLEY BLANCH : Now, you’ve had firsthand experience in observing two family members manage diabetes. Was this how this app started for you Andrew?

ANDREW CHEN : Yes, that’s correct. I saw how my dad had to manage his diabetes every single day and it was hard to see the tediousness of the tasks that my dad had to carry out as well as the negative impacts it had on his life.

DESLEY BLANCH : So what are the difficulties that face diabetics when they have to record and manage their daily intake of food and everything they drink in their beverages?

ANDREW CHEN : Pretty much everything that they do during the day has to be recorded. Before meals and after meals they have to record their blood glucose level as well as the foods that they eat, the amount of exercises that they perform and at the end of the day, they have to sit down and look at how they’re doing in terms of their blood glucose and if it’s too high or too low they have to take measures to keep it under control.

DESLEY BLANCH : So could you walk us through how someone would use your app as their blood glucose levels as you say, the amount of carbohydrates consumed for meals, insulin levels--all have to be recorded daily by diabetes and currently they write it down. But how do you do it with your app?

ANDREW CHEN : Our app simplifies the whole process. They can enter data into the application with only a few clicks but the important aspect is the ability to enter nutrient information from foods by simply scanning the bar code or using object recognition. So when the diabetic wants to eat food they can take the packaging and scan the bar code and our data base will return the information on the food, for example, the carbohydrates and the sugar levels.

DESLEY BLANCH : And if there’s no bar code on the food? You’re in a restaurant, a meal is put in front of you, what do you do then?

ANDREW CHEN : So our app also has object recognition which allows the app to recognise certain foods and objects. In the future, dishes of foods will be able to be recognised which will also allow the app to retrieve the amount of carbs for the foods.

DESLEY BLANCH : Well, it’s said that the bane of any diabetic’s life is counting carbohydrates in food consumed. So if it can count carbs, how accurate might it be?

ANDREW CHEN : Over the usage of the application, the accuracy will increment as the user can correct the amount of carbs if the retrieved data is not accurate. So the more the user uses our app, the more accurate it will get.

DESLEY BLANCH : And how are these numbers entered and recorded?

ANDREW CHEN : For bar codes, there is a huge data base which is stored on our cloud server which covers all available bar codes in the world.  For objects recognised through the app, the user will be able to enter carbohydrate information if it is unavailable which can then be modified throughout the usage of the app.

DESLEY BLANCH : Now Andrew, how did the three of you get together? What brought Donald and Robin onboard and what did you each contribute?

ANDREW CHEN : We started as a team during the summer break to participate in a competition and we’ve known each other since we started university. We contributed by separating the functionalities of the app into equal proportions and we each attempted different functionalities.

DESLEY BLANCH : Such as? I mean whose idea was it to allow the app to simply scan the bar codes of the products?

ANDREW CHEN : So when we sat down to design the app it was a goal to make it as innovative as possible and we actually started with object recognition first, which gradually became bar code scanning as it was much easier to implement technically. So, object recognition was done by Donald. He also did the cloud computing functionalities, while I did the data base back-ends, the log books and the overall usability of the application, while Robin did the Health Vault integration and the front end of the application.

DESLEY BLANCH : Another function is an alarm system. So how does the user make the most of this?

ANDREW CHEN : As the user uses our app more frequently, the data that is collected will be stored and it will form a prediction model for each customised case of the diabetes condition of the user as each diabetic has different requirements.

DESLEY BLANCH : And they have different amounts of exercise, have different amounts of food, so it somehow tailors itself and educates itself to become that person, representing that person only. Is that the way it works?

ANDREW CHEN : Yes, so once the model of the specific user is generated, notifications will be sent to the user throughout the day.

There are two aspects. The first aspect is just general reminders, for example, if the user does not enter glucose level data for a certain period of time the app will remind the user to do so.

The second aspect is certain reminders to better manage the diabetes condition. For example, if the app calculates that the glucose level of the user will be too high after certain foods are entered into the data base, it will remind the user that his or her glucose level is too high for the day and to take precautionary measures, such as, take more pills or inject more insulin, as well as to eat more healthy or to do more exercises.

Once the prediction model of the user has been created, we can use that data to further enhance the diabetes management experience. For example, we can take data from the calendar of the user and remind the user to take medication or insulin during the periods of time where he or she are not as busy.  

We can also take sensor data from the mobile phone, for example, the location of the user, which in turn allows us to retrieve the weather information. Because hot weather actually as a negative effect on diabetics in that they cannot sweat as much as usual people so the blood glucose level actually needs to be monitored even more carefully during hot weather.

DESLEY BLANCH : It sounds as though it can do all sorts of different things. I’m wondering how user-friendly it is for those who have little knowledge of such technologies?

ANDREW CHEN : We tried to make it as simple as possible especially because we’re using the Windows Phone platform which is very usable in terms of user interactions.

So as soon as you open up the application, all the main functionalities are easily accessible.  Bar code scanning and objective recognition is only one tap away.

DESLEY BLANCH : Andrew, what’s the competition out there in other electronic solutions that are currently available for diabetics and how close does yours come and how further advanced is yours from what’s available?

ANDREW CHEN :  What is available nowadays are very simple data collection applications. They do not have advanced functionalities such as bar code scanning or prediction models and use of mobile phone sensors. So our app actually stands out amongst the crowd greatly in terms of functionalities which enhance diabetes management.

DESLEY BLANCH : You were in India, where there’s a lot of poor people who maybe can’t afford a mobile device. Is that the case or will this go onto most mobile devices available?

ANDREW CHEN : We will try to make our app available on as many platforms as possible and especially with the support of companies such as Google and Microsoft smart phones are becoming more available in third world countries such as India.

DESLEY BLANCH : So what’s next in getting the product to market?

ANDREW CHEN : We are currently looking for more funding and we are also in the process of adding more functionalities. But we plan to make the application available as soon as possible.

DESLEY BLANCH : Andrew Chen, final year information technologies student at the University of Sydney whose BlueClover mobile phone app is set to help diabetics better manage their condition.

 

VIDEO of the students' video pitch which outlines the BlueClover phone app.   

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Contributors

Andrew Chen

Guest

Final year information technologies student

University of Sydney, New South Wales

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