Hassan, Arshia Zernab2018-09-212018-09-212018-07https://hdl.handle.net/11299/200140University of Minnesota M.S. thesis.July 2018. Major: Computer Science. Advisor: Arshia Khan. 1 computer file (PDF); viii, 166 pages.Alzheimer’s and related dementia are associated with a gradual decline in cognitive abilities of an individual, impairing independent living abilities. Wandering, a purposeless disoriented locomotion tendency or behavior of dementia patients, requires constant caregiver supervision to reduce the risk of physical harm to patients. Integrating technology into care ecology has the potential to alleviate stress and expense. An automatic wandering detection system, when integrated with an intervention module, may provide warnings as well as assistive prompt, in times of abnormal behavior. In this study, we survey existing research on technology aided methodologies and algorithms to detect wandering behavior in movement data of individuals affected with dementia. Our study provides insights into mechanisms of collecting trajectory data and finding patterns that distinguish wandering from normal behavior. Furthermore, we analyze technologies and methodologies used in wandering management, depending on researchers perception of wandering scenarios, and discuss the general challenges of conducting research in this domain. After exploring various existing approaches, we analyze an algorithm that employs vector angles to compute travel direction in spatiotemporal data and verify if including the rate of change of the angles would augment the identification process. In addition, we explore the feasibility of utilizing infrared motion sensor cameras in collecting movement data.enThesis or Dissertation