In this day and age, most of us have probably seen or used fitness and activity trackers at some point. There are a plethora of commercial smartwatches and rings available from brands like Apple, Garmin, Fitbit, and Oura to name a few. We know that these can be extremely useful in tracking activity, sleep, and heart rate but the fact that they can be extremely useful in early disease detection remains fairly lesser known. There are ongoing investigations on the use of these devices for research on Alzheimer’s disease, breast cancer, movement-related disorders, flu and more recently even COVID-19. How, you might be thinking? Welcome to the world of digital biomarkers!

Digital biomarkers are digitally collected data that are transformed into indicators of health outcomes. For instance, glucose levels measured from a continuous glucose monitor can be useful in predicting diabetic state. I am a graduate student in biomedical engineering at the BIG IDEAS Lab and our research focuses on analyzing wearable device data to develop digital biomarkers and gain useful health insights.

When our body starts getting affected by a particular health condition or disorder, say a viral infection or diseases like diabetes, our physiological signals start changing, sometimes slowly over time. These physiological signals can be tracked over a long period of time using wearable devices like fitness trackers. With the use of data analytics and machine learning tools, we can train our algorithms to detect these small changes in the body’s physiological signature to alert us of disease onset or progression. I am fascinated by the potential it holds to transform the way we look at healthcare and am excited about generating more awareness around digital biomarker research.

There are quite a few challenges that digital biomarker research currently faces. The codes and algorithms are often not freely available and the research requires familiarity with coding which often alienates people who are not comfortable with codes. In order to make digital biomarker discovery more accessible and collaborative, our lab developed an open-source platform called the Digital Biomarker Discovery Pipeline (DBDP). The DBDP features code sets, functions, and algorithms for the entire digital biomarker discovery pipeline. For more information about the platform, read this fantastic blog by our lab member here.

In order to expand the initiative and spread general awareness about digital biomarkers, we have recently launched dbdpED (DBDP — Education). dbdpED will aim to provide you with all the tools to get started with digital biomarker discovery. For the first phase of the dbdpED launch, we will focus on developing resources for high school students. The field of digital health is quite new and there is an excess of jargon around digital biomarkers discovery. We need

more resources to make this field inclusive and accessible. With the support of GradEngage, I aim to develop detailed and easy to understand lesson plans and organize workshops for the students at the North Carolina School of Science and Mathematics (NCSSM) on wearable data analysis. These workshops will give the students a chance to explore the various aspects of wearable data analysis and engage in discussions about the utility of the field. I aim to introduce the students to the various steps of digital biomarker discovery pipeline and encourage them to explore the various code sets that will be made available through the dbdpED platform. With extensive video tutorials and blogs, we will expand the dbdpED platform to make the end-to-end process of digital biomarker discovery available to anyone new to the field. The DBDP has multiple code sets for different stages of digital biomarker discovery. dbdpED will help you easily understand the purpose and utility of these code sets. These in-depth tutorials will provide users with a fun and engaging learning experience for digital biomarker discovery.

Not only will this help students gain an enriching experience in wearable data technology, data science and visualisation tools, it can be a great tool for personal health monitoring. The idea is to give students a taste of digital biomarker research and generate interest in the field early on. I am excited about engaging with the students and gaining their perspective on how this platform can be truly useful for young students. I believe this experience will prove to be uniquely enriching for me and help make the dbdpED platform what it is meant to be, useful, easy to grasp, and fun!