Pascal Poupart, Ph.D.
University of Waterloo
Waterloo, Ontario, Canada

2008 Everyday Technologies for Alzheimer Care Grant

The current methods for assessing Alzheimer's disease involve testing a person's cognitive and functional abilities at fixed points in time. But Alzheimer's disease may reveal itself with a wide range of symptoms that progress differently in different people, and these tests don’t capture the subtle changes in cognition and function during daily activities. Additionally, drug treatments, such as cholinesterase inhibitors, can have varying effects on different people's symptoms, making assessment more difficult.

Recent advances in sensors and information technology may make it possible to personalize and embed assessment methods into daily activities. No studies have yet examined what behavioral, cognitive and functional symptoms could be captured by sensors that monitor changes in movement, heart rate or global positioning.

Pascal Poupart, Ph.D., and colleagues will conduct a study using sensors to monitor people with Alzheimer's disease in their daily activities. The team will collect physiological, mobility, gait, behavioral, activity and speech data from both healthy people and people with mild to moderate Alzheimer's disease. They will also use a computer program to manually enter in information about the participants' symptoms.

The group will analyze the sensor data to determine if there are relevant markers to differentiate between healthy people and people with Alzheimer's disease. They will also compare the sensor data with the manually entered data.

The study will provide a proof of concept for the eventual development of automated monitoring techniques to unobtrusively assess Alzheimer symptoms and their progression. This will be particularly useful in monitoring the effectiveness of behavioral therapy and drug treatments.