A Practical Approach to Recognizing Physical Activities

We are developing a personal activity recognition system that is practical, reliable, and can be incorporated into a variety of health-care related applications ranging from personal fitness to elder care. To make our system appealing and useful, we require it to have the following properties: (i) data only from a single body location needed, and it is not required to be from the same point for every user; (ii) should work out of the box across individuals, with personalization only enhancing its recognition abilities; and (iii) should be effective even with a cost-sensitive subset of the sensors and data features. In this paper, we present an approach to building a system that exhibits these properties and provide evidence based on data for 8 different activities collected from 12 different subjects. Our results indicate that the system has an accuracy rate of approximately 90% while meeting our requirements. We are now developing a fully embedded version of our system based on a cell...

• Type: Journal
• Year: 2006
• Where: PERVASIVE
• Authors: Jonathan Lester, Tanzeem Choudhury, Gaetano Borriello
• Keywords: Applied Computing, Health-care Related Applications, Personal Activity Recognition, PERVASIVE 2006, Single Body Location