Assessment of Cognitive Performance in Elderly Life via Meaningful Play

Cognitive decline is the deterioration of one or more cognitive functions such as attention, memory, or processing speed. Inherent to aging, most people will encounter some form of cognitive decline during their lifetime while retaining the ability to perform instrumental activities of daily living. However, beyond this age-related cognitive decline due to aging, some people will experience pathological cognitive decline: an abnormal rate of cognitive impairment due to neurological diseases such as dementia or due to physical trauma. In contrast to age-related cognitive decline, this pathological cognitive decline hinders activities of daily living. In between the stages of age-related and pathological cognitive decline, is the stage of Mild Cognitive Impairment (MCI), which is characterized by a slight yet noticeable decline in cognition. Nevertheless, instrumental activities of daily living remain mostly intact in this stage. While the diagnosis of MCI is not always followed by a diagnosis of dementia, people diagnosed with MCI have a markedly higher chance of progressing to dementia. As such, early case-finding of MCI and timely adjusting the diagnosis is crucial to ensure apt medical support. To aid this cause and to better understand the dwindling of cognition, this dissertation sets out to explore the possibilities of using digital card games to assess differences in cognitive performance due to cognitive aging and MCI. In particular, the use of digital biomarkers, i.e., user-generated physiological and behavioral data collected through digital devices, is investigated. Embedded into day-to-day interactions, these digital biomarkers can be used to support diagnosis without interfering with the person's daily routine. In addition, as they are high-resolution in nature, they allow for making informed inferences of neuropsychological processes previously unavailable to psychologists. In this doctoral dissertation, two different aspects of cognitive decline are measured using different digital card games. First, digital biomarker caused by cognitive aging are assessed using the card game FreeCell. To this end, a generic image processing toolkit was built to extract digital biomarkers from the Microsoft Solitaire Collection. Using this toolkit, data was captured from three different age categories. Machine learning models trained on this data showed promise in classifying the younger and older age categories but lacked in classifying games played by the m