The Mobile Sensing Platform: An Embedded Activity Recognition System

• Published in: IEEE pervasive computing Vol. 7; no. 2; pp. 32 - 41
• Main Authors: Choudhury, T., Consolvo, S., Harrison, B., Hightower, J., LaMarca, A., LeGrand, L., Rahimi, A., Rea, A., Borriello, G., Hemingway, B., Klasnja, P., Koscher, K., Landay, J.A., Lester, J., Wyatt, D., Haehnel, D.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accelerometers; activity recognition; Algorithm design and analysis; embedded systems; Fitness; Health care; Human; machine learning; Medical services; Military; Monitoring; Pervasive computing; Platforms; Privacy; Protection; Recognition; Robustness; Software algorithms; Software design; Surveillance; Ubiquitous computing; wearable computers
• ISSN: 1536-1268; 1558-2590
• DOI: 10.1109/MPRV.2008.39

Activity-aware systems have inspired novel user interfaces and new applications in smart environments, surveillance, emergency response, and military missions. Systems that recognize human activities from body-worn sensors can further open the door to a world of healthcare applications, such as fitness monitoring, eldercare support, long-term preventive and chronic care, and cognitive assistance. Wearable systems have the advantage of being with the user continuously. So, for example, a fitness application could use real-time activity information to encourage users to perform opportunistic activities. Furthermore, the general public is more likely to accept such activity recognition systems because they are usually easy to turn off or remove.