Date Added: Oct 2010
With more older adults and people with cognitive disorders preferring to stay independently at home, prompting systems that assist with Activities of Daily Living (ADLs) are in demand. In this paper, with the introduction of "The PUCK", the authors take the very first approach to automate a prompting system without any predefined rule set or user feedback. They statistically analyze realistic prompting data and devise a classifier from statistical outlier detection methods. Further, they devise a sampling technique to help with skewed and scanty data sets. They empirically find a class distribution that would be suitable for the work and validate the claims with the help of three classical machine learning algorithms.