Bringing it all together: Wearable data fusion
Yunus Çelik, Alan Godfrey
Abstract
Commercial-based wearables have become an integral part of our lives, revolutionising the way we monitor and manage our health 1 , 2 . Devices including smartwatches, fitness trackers, respiratory bands, electrodermal response sensors, and smart insoles have the potential to enable more insightful physical examinations through high-resolution data. It’s akin to a mini clinic worn directly on our body. Many physiological outcomes can be collected from those now described as routine (e.g., heart rate, blood oxygen levels, sleep patterns) to those previously unattainable beyond a clinic or complex monitoring equipment (e.g., electrocardiogram, electrodermal activity) 3 . But here’s the thing: having all these data doesn’t necessarily give the full picture of health 4 , 5 , 6 . For instance, quantifying daily heart rate is useful, but without considering other outcomes such as physical activity levels or sleep quality, it may be meaningless to gauge the true impact of daily activities on overall health or treatment interventions. There is a need to move beyond isolated data points and embrace a holistic approach to monitoring. That’s where data fusion comes in. It’s the process of combining data from different sources to create a more complete picture of what’s going on.