Researchers from the Washington State University School of Electrical Engineering and Computer Science have developed an algorithm to increase the accuracy of wearable devices by replacing and representing missing health data.

Wearable devices are increasingly popular for important health applications, such as for vital sign monitoring, rehabilitation, and movement disorders. Especially in rural areas, a wearable device can provide continuous and important health information when a doctor is far away. The wearable devices use sensors to collect information on users’ health and then make decisions using machine learning algorithms.

However, while the machine learning algorithms assume that data from all sensors are available, that is often not the case, says Ganapati Bhat, Raymond and Beverly Lorenz Distinguished Assistant Professor in WSU’s School of Electrical Engineering and Computer Science who led the work.

Every Wednesday is Wearable Wednesday here at Adafruit! We’re bringing you the blinkiest, most fashionable, innovative, and useful wearables from around the web and in our own original projects featuring our wearable Arduino-compatible platform, FLORA. Be sure to post up your wearables projects in the forums or send us a link and you might be featured here on Wearable Wednesday!