Keynote: Wearable and IoT for cognitive health assessment: Significance and challenges

The U.S. Census Bureau reports that the U.S. population of people aged 65 and up will grow more than double in between 2010 and 2050. The market for remote patient monitoring is expected to grow from $10.6 billion in 2012 to $21.2 billion in 2017. This growing societal and economical needs revitalize the work on technology-assisted proactive and preventive health monitoring in smart home environments. In recent time the proliferation of commodity smart healthcare appliances and stand-alone and integrated sensing devices (Internet of Things) make it increasingly easier to ubiquitously and continuously monitor an individuals health-related vital signals, activities, and behaviors to provide just-in-time interventions for the aging population. Nevertheless, developing reliable and clinically equivalent point-of-care technologies to perform automated health assessment and intervention remain challenging. In this talk, I will discuss how signal processing and machine learning techniques help analyze the activity and physiological signals to gauge the cognitive and behavioral health of older adults. I will also discuss the comparative performance of technology-guided algorithmic methodology with clinically-driven survey, observation, and performance-based measurements. I will conclude the talk highlighting our experiences of deploying this smart home health service systems for Alzheimer's patients living in retirement community centers.