Clinical translation: Smart technologies for health assessment and intervention

Abstract

Smart technologies that can adapt, sense, infer, learn, anticipate and intervene offer possibilities for improving health care delivery. Continuous data collection afforded by smart technologies has the potential to enrich patients' clinical pictures by augmenting self- and informant-report data and testing data collected during an office visit. Smart technologies also offer possibilities for assisting in real-time with rehabilitation and proactive health interventions. This keynote will discuss issues of importance in creating technologies that can be translated into clinical practice. For example, improving clinical translation of smart technologies for use by health-care professionals will require demonstrating that developed health-related algorithms are reliable and valid, easily visualized and of value in clinical decision-making. The clinical translation of prompting interventions will require answers to questions regarding the best timing, content and delivery of prompts in addition to issues related to motivation and the changing clinical needs of patients. These points and others will be illustrated with examples from our research using sensor data and machine learning techniques to develop algorithms that recognize activities, provide insights on functional status and automate interventions.

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