Systems that can detect cognitive decline or harmful levels of stress could assist users in managing their stress and health. However, current assessments are often obtrusive or require specialized equipment, and not suited to continuous monitoring of cognitive status. This research leverages attributes of everyday keyboard interactions to proactively and continuously monitor cognitive function. A laboratory study was conducted where typing samples were collected to explore the effects of stress, age, and cognitive impairment on interaction patterns. Keystroke and linguistic features were extracted from the samples and models were constructed for each group as well as for nine individual participants. Correct classification rates were 60% for stress in younger adults, 60.5% for stress in older adults, 79.1% for age, 78.6% for cognitive impairment, and ranged from 62% to 88% with a mean of 72% for stress in individuals. This research contributes a unique combination of features for text and keystroke analysis, enhances understanding of how stress and cognitive impairment affect typing patterns, and has implications for systems for health monitoring. Further research includes exploration of additional keystroke and linguistic features, further interaction techniques, study of varied levels and types of stress, and a longitudinal study of cognitive decline. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]