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. This talk will present our 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.
Co-sponsored by the Center for Technology and Economic Development, NYUAD