San Francisco, California
London, United Kingdom
Please join us on Tuesday April 23rd for a discussion with Professor Deborah Estrin about her experiences with mobile health. The discussion will be followed by a reception. Location NYU Abu Dhabi (NYC Office) 19 Washington Square North, New York, NY (between 5th Ave. and Washington Square West)
This talk will present Professor Deborah Estrin's experiences to date with mHealth pilots and prototypes including areas most in need of further exploration: analysis and visualization (sense-making) across diverse data streams, standardizing measures and methods, an open modular architecture to promote innovation, and privacy mechanisms.
Deborah Estrin, is a Professor of Computer Science at the new Cornell Tech campus in New York City and a Professor of Public Health at Weill Cornell Medical College. She is co-founder of the non-profit startup, Open mHealth. She was previously on faculty at UCLA and Founding Director of the NSF Center for Embedded Networked Sensing (CENS). Estrin is a pioneer in networked sensing, which uses mobile and wireless systems to collect and analyze real time data about the physical world and the people who occupy it. Estrin’s current focus is on mobile health (mhealth), leveraging the programmability, proximity, and pervasiveness of mobile devices and the cloud for health management.
The most significant health and wellness challenges increasingly involve multiple chronic conditions, from diabetes, hypertension, and asthma to depression, chronic-pain, sleep and neurological disorders. The promise of mobile health (mHealth) is that we can leverage the power and ubiquity of mobile and cloud technologies to monitor and understand symptoms, side effects and treatment outside the clinical setting, thereby closing the feedback loops of self-care, clinical-care, and personal-evidence-creation. However, to realize this promise, we must develop new data capture, processing and modeling techniques to convert the ‘digital exhaust’ emitted by mobile phone use into behavioral biomarkers.