Scientists from the University of Sussex in the United Kingdom have developed an algorithm enabling smartwatches to track every move without being programmed beforehand.
Current smartwatches, while able to track certain activities like walking and biking, are only able to do so after programming. The algorithm developed by researchers is able to track activities, such as cutting vegetables and writing, as they occur.
"Current activity-recognition systems usually fail because they are limited to recognizing a predefined set of activities, whereas of course human activities are not limited and change with time,” said Hristijan Gjoreski of the University of Sussex. "Here we present a new machine-learning approach that detects new human activities as they happen in real time, and which outperforms competing approaches.”
Encompassing all activity in real-time allows for better understanding of an individual's everyday activity. By including the tracking of sedentary activity, researchers hope the algorithm could bring smartwatch users closer to understanding their own health.
"Future smartwatches will be able to better analyze and understand our activities by automatically discovering when we engage in some new type of activity,” said Daniel Roggen, head of the Sensor Research Technology Group at the University of Sussex. “This new method for activity discovery paints a far richer, more accurate, picture of daily human life. As well as for fitness and lifestyle trackers, this can be used in healthcare scenarios and in fields such as consumer behavior research."