Date of Award

5-31-2016

Document Type

Thesis (Undergraduate)

Department

Department of Computer Science

Abstract

In recent years, significant progress has been made in health technology through advancements in mobile technology, wearable computing, and connected devices. These advancements have created lightweight or even automated experiences for users in vital aspects of health such as exercise and sleep tracking. Despite these advancements, one area of health, nutrition, remains stifled by cumbersome user interaction. We present Nutrition Buddy, a novel approach to nutrition tracking which utilizes a simplified data model that allows for lightweight interactions, effective wearable technology, and relevant recommendations provided by a digital nutritionist "buddy" to facilitate behavior change.

Comments

Originally posted in the Dartmouth College Computer Science Technical Report Series, number TR2016-808.

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