Detecting mild cognitive loss with continuous monitoring of medication adherence

This paper describes an approach for detecting early cognitive loss using medication adherence behavior. We investigate the discriminative power of a comprehensive set of recurrent medication timing features extracted from timeof-day and inter-dose timing statistics. We adopt information theoretic measures for feature ranking for initial dimensionality reduction and conduct exhaustive leave-oneout cross validation for final feature selection and regularization. The selected feature set is subjected to a support vector machine for classification. The results demonstrate that patterns of adherence based on the data from relatively unobtrusive behavior monitoring can make reliable inference for mild cognitive loss individuals.

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Yonghong Huang, Deniz Erdogmus, Zhengdong Lu, Todd K. Leen
• Keywords: Cognitive Loss, ICASSP 2008, Medication Adherence Behavior, Recurrent Medication Timing, Signal Processing