“Applications of Mobile Sensing for Behavioral Studies”

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Date(s) - Nov 8, 2011
2:00 PM - 3:00 PM

UCLA Center for Community Health


Applications of Mobile Sensing for Behavioral Studies

Presented by:

Nithya Ramanathan, Ph.D.

UCLA Department of Computer Science

Co-Founder, Nexleaf Analytics

CHIPTS Methods Core

Tuesday, November 8, 2011
2pm – 3pm

Center for Community Health, UCLA Wilshire Center
10920 Wilshire Blvd., Suite 350, Conference Room

We will begin promptly at 2:00 p.m.

Click here for PDF of Slide Presentation

ABSTRACT: Advances in mobile and Internet technologies allow individuals to use their personal phones as a convenient platform for realtime and scientifically credible assessment of their health and environment, regardless of individual economic status. The ‘always-on’ and ‘always-worn’ status of mobile phones make it possible to collect real-time behavioral and environmental signatures as inputs into patient-self-care, clinical treatment, and research. In this talk I will describe Ohmage, a smartphone-to-web based system designed by a team at the UCLA Center for Embedded Networked Sensing for personalized health monitoring, with feedback from a diverse population of users through interviews, focus groups, and short pilots.

BIO:  Nithya Ramanathan is an Assistant Research Faculty in Computer Science at UC Los Angeles, Co-Founder of Nexleaf Analytics, and a member of the CHIPTS Methods Core. Developing innovations in wireless sensor networks for the study of water, her doctoral work led to key advances in the understanding of arsenic contamination of groundwater wells in Bangladesh. Nithya’s current research focuses on transforming everyday objects like mobile phones into scientific data collection instruments that can be used to engage citizens in monitoring and improving personal and public health, climate, and the environment. With funding from a highly competitive NIH Challenge Grant, Nithya began development of a smartphone application to improve the cardiovascular health of women. Her work is funded by Google, the National Institute of Health, the National Science Foundation, USAID, and the Switzer Foundation.