Title :
Sensor-Based Activity Recognition
Author :
Chen, Liming ; Hoey, Jesse ; Nugent, Chris D. ; Cook, Diane J. ; Yu, Zhiwen
Author_Institution :
Sch. of Comput. & Math., Univ. of Ulster, Belfast, UK
Abstract :
Research on sensor-based activity recognition has, recently, made significant progress and is attracting growing attention in a number of disciplines and application domains. However, there is a lack of high-level overview on this topic that can inform related communities of the research state of the art. In this paper, we present a comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition. We first discuss the general rationale and distinctions of vision-based and sensor-based activity recognition. Then, we review the major approaches and methods associated with sensor-based activity monitoring, modeling, and recognition from which strengths and weaknesses of those approaches are highlighted. We make a primary distinction in this paper between data-driven and knowledge-driven approaches, and use this distinction to structure our survey. We also discuss some promising directions for future research.
Keywords :
knowledge engineering; ubiquitous computing; data-driven approach; knowledge-driven approach; pervasive computing; primary distinction; sensor-based activity recognition; vision-based activity recognition; Biomedical monitoring; Data models; Hidden Markov models; Human factors; Monitoring; Wearable sensors; Activity modeling; activity monitoring; activity recognition; dense sensing; pervasive computing;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/TSMCC.2012.2198883