Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Motion capture for the rest of us
Journal of Computing Sciences in Colleges
Analyzing features for activity recognition
Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Does location help daily activity recognition?
ICOST'12 Proceedings of the 10th international smart homes and health telematics conference on Impact Ananlysis of Solutions for Chronic Disease Prevention and Management
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The development of context aware services is one proposed way to support independent living for the elderly. Performing test scenarios with the elderly helps when developing the context aware services. However, rigorous testing is not always desirable when working with elderly subjects. Our research proposes to capture the activity data of the subjects to use with a virtual environment and virtual human to test the services. This paper begins a larger set of research by describing a process in which the daily activities of the elderly are captured using accelerometer sensors. The process consists of pre-investigation, data capturing and data postprocessing. Using common activity recognition methods daily activities chosen by two elderly subjects themselves are recognized reasonably well. This allows using the described process in larger experiments to acquire more activity data.