Wearable devices are a complementary technology that has taken the world by storm. The market for diabetes wearables is estimated to reach $36.25 billion by 2032. That’s a 6.3% CAGR from 2021.
Recent advances in diabetes wearables have shown significant progress in improving, monitoring, and managing diabetes. Wearables like CGM devices and smart insulin pens have become more accurate, reliable, and user-friendly.
Advances in sensor technology have led to smaller, more comfortable sensors that can be worn for longer. Some devices are now designed to provide alerts and warn us if the glucose is getting too low or too high. We can track and log our insulin doses digitally and share diabetes-related data with healthcare experts.
The question is, what does the future of diabetes wearables look like? Can we expect better technologies to hit the market? Although I can’t predict the future, I can take a guess - AI and machine learning are going to shape the future of diabetes wearables. Here is how.
The Future of AI for Wearable Devices in Diabetes Monitoring
AI is a machine that can solve problems, process data, analyze, find patterns, and make predictions based on what it learns. It is like having a friend who can magically sift through piles and piles of information, think, learn, and help us make better decisions.
Technologies that drive the AI revolution in 2021 are machine learning (ML) and deep learning. These technologies have made impressive advancements. Mainly because we have more powerful computers and improved computational resources.
At the moment, there are dozens of FDA-cleared medical devices that use AI and ML. Although most of them are associated with oncology, cardiology, and radiology, there are AI-powered medical devices designed for managing diabetes.
These include self-management tools like AI-powered CGM systems, including insulin pumps and bionic pancreas. This is what the future of wearables for diabetes looks like with integrated AI capabilities.
Detect and Predict Diseases
Normally, when I get my eyes checked for retinopathy, I book an appointment and then wait about 6 weeks for the next one. The problem is, the longer the waiting period, the bigger the odds of the signs of retinopathy going unnoticed.
Eyenuk, a company founded by Kaushal Solanki, has developed EyeArt®, an AI-powered technology. This technology can automate the process of detecting diabetic retinopathy (DR).
EyeArt® allows any healthcare provider to capture retinal images using fundus cameras. They can then upload them to the cloud-based system. In just 60 seconds, the AI technology analyzes the images, providing a report that helps guide treatment decisions.
Since there is a need to assess DR risk and progression over time, Eyenuk further developed EyeMark™. This technology automatically quantifies and analyzes changes in the retina. This allows doctors to watch disease progression and evaluate the risk of blindness.
EyeMark™ is described as "superpower AI" because it enables medical experts to spot and track small lesions on the retina. This could be useful in the early detection and prediction of the disease.
The company is currently working on creating screening tools for serious eye conditions. Such as primary open-angle glaucoma (POAG) and age-related macular degeneration (AMD). Solanki also uses AI technology to develop tools that can detect damage to the tiny blood vessels in the eye. This may serve as an indicator for other ailments like cardiovascular disease and Alzheimer's disease.
Activity Classification
I’ve been using wearables for quite some time now. Most of them are equipped with accelerometers and gyroscopes. This allows them to measure geospatial orientation and acceleration.
By capturing these parameters, machine learning models can analyze and interpret various aspects. Such as activities, posture, fall detection, gait analysis, and more. You can use this information to:
- see and monitor any changes in movement patterns,
- check your activity levels,
- get personalized feedback,
- reminders, and so on.
Many studies have been done on AI-powered wearable technologies for diabetes. According to a recent report published in the Journal of Medical Internet Research, experts found that there is a lot of potential for growth in this field.
These wearable devices could replace invasive devices and traditional hospital settings, particularly in monitoring blood sugar levels. For example, wearable devices equipped with biosensors can be a more convenient and non-invasive method for people with diabetes to track their sugar levels.
It can eliminate the need for frequent hospital visits and greatly enhance the monitoring experience. But, more large-scale data is necessary to study the impact of wearable devices. Particularly those that use machine learning for diabetes.
Recognize New Patterns
Diabetes is an unpredictable disease. The body’s response to insulin can vary throughout the day and from person to person. Factors such as hormonal changes, disease, physical activity, and stress can all affect your insulin sensitivity. They can then lead to blood sugar highs and lows.
When you use wearable health tech, you can recognize these new patterns. For example, you can see how your daily activities and lifestyle choices are affecting your glycemic management. You can then use this knowledge to plan the next meal and adjust the diabetes medication.
With early detection, you can detect potential issues with diabetes. As well as avoid any triggers that might interfere with your diabetes care. If you were recently diagnosed with diabetes, or your condition is proving hard to manage, you can share the data with your healthcare team. They can help you create a personalized treatment plan.
Filter Large Volumes of Data
Thanks to AI, wearable devices can handle and process large amounts of data. So, you don’t have to worry about manually tracking or analyzing your diabetes treatment.
AI-powered tools are designed to provide real-time feedback that you can use to make timely adjustments to your diabetes care plan. This can help you fine-tune your strategies, and get precise and effective treatment.
Conclusion
The future of diabetes wearables seems to go hand-in-hand with AI and machine learning. By leveraging these technologies, we can expect wearables to become more intelligent and adaptive. They can help support people with diabetes in achieving better glucose control. AI can also reduce the burden of management and improve health outcomes.
