Abstract
Altered activity patterns are often the general symptoms experienced by people with dementia. The quantity and quality of patient's daily activities such as their sleeping may be a reflection of their dementia condition and affect their quality of life. Monitoring patient's activity patterns over different periods of time may help healthcare professionals with determining the patient's cognitive impairment stage. In this research, we describe an activity pattern detection and visualization system developed to support the monitoring and assessment of activity patterns for people diagnosed with dementia, at the early stages of the disease. Analysis shows that rich information embedded in sensory data can provide useful knowledge for understanding patients' activity patterns, detect unusual events and may also be useful for examining cognitive status.
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