Bleeding Edge in Diabetes Technology


We live in a world where technology makes our lives easier.

Instant messaging helps us talk to our friends and family with a push of a button. Online banking saves us a trip. Exercise apps create personalized exercise plans just for us. Clearly, technology helps us maximize our time and efforts.

Additionally, technology helps us better manage Type 1 Diabetes and live a happy and healthy life. Here are some emerging technologies in Type 1 Diabetes management for 2017.


1. Wearable Sensors

Wearable Technology

You’ve probably used wearable sensors if you’ve ever used a Fitbit during your workout. Or if you’ve used apps that count the number of calories you lost on your run.

Stanford professor Mike Snyder was interested in how wearable sensors can be used in healthcare. He looked at whether they can diagnose you before you realize you’re sick.

He participated in a study and wore a number of devices, including oximeters. On a plane ride to Norway, he noticed that his sensors had picked up several symptoms. He had dropping oxygen levels, elevated heart rate, and a burning fever. He remembered he had been bitten by a tick two weeks earlier. Immediately, he realized he must have contracted Lyme disease.

He quickly rushed to a doctor, who diagnosed him with the disease. Because he was wearing the devices, the doctor was able to save his life. Thus, the sensors succeeded in diagnosing him before he knew he was sick.

Similarly, at Docto, we apply the same logic to help patients with Type 1 Diabetes manage their condition. Docto monitors your blood-sugar levels in real time. It uses a predictive model to learn your glucose response to stress and calorie absorption. Additionally, it measures your glucose response at night to predict hypo and hyperglycemia. We work with a Dexcom CGM and fitness tracker.


2. Machine Learning

Netflix Technology

Machine learning is the idea that computers can learn and perform tasks using statistical methods. Without relying on a human to program it, the computer is able to recognize patterns and perform tasks.

Websites like Netflix use machine learning to learn our movie and TV show preferences. They are then able to give us suggestions on what to watch next. In the healthcare sector, machine learning is used to improve diagnostics and predict outcomes. This helps doctors diagnose their patients. Apps like NextIT and AiCue use machine learning to remind patients to take their medicine. They also alert the patients in case of an emergency.

Similarly, Docto applies the same type of thinking. Docto uses CGM and fitness tracker data to learn and predict fluctuations in a user’s blood sugar levels. It uses an advanced learning algorithm that combines metabolic, behavioural, and current glucose data. Thus, Docto can predict blood sugar levels one hour into the future.


3. Next Generation CGM

Additionally, here are a few other technologies to look forward to. Dexcom is working with Verily to launch a miniaturized continuous glucose monitoring device in 2018. They also plan to launch a “disposable, inexpensive Band Aid-sized glucose monitor” in 2020 or 2021. The idea is that patients can peel on and off the CGM, as they would a Band Aid. Furthermore, this product will be cost effective.

Moreover, this next generation of CGM is set to include more information about the patient’s lifestyle. This will allow it to accurately analyze the data.


Make sure to check out our other posts for more articles about Type 1 Diabetes innovation and research. Additionally, you can find us on Facebook and Twitter.


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