Files
Abstract
Socialization is an essential part of healthy aging. Still, due to normal changes in health and lifestyle, elderly individuals are at increased risk of becoming lonely—a qualitative state characterized by a subjective deficit in social relationships. In the elderly, loneliness predicts morbidity and mortality, is associated with decreased cognitive functioning, impairs sleep quality, decreases mobility, and reduces quality of life. As a result, it is increasingly important to identify and assist lonely individuals. The focus of this thesis is to develop techniques to assess loneliness based on data from motion, contact, phone, and computer sensors in the home, setting the framework for unobtrusively measuring loneliness among older adults.