Toggle Main Menu Toggle Search

ePrints

Activity Recognition and Healthier Food Preparation

Lookup NU author(s): Dr Thomas Ploetz, Professor Paula Moynihan, Cuong Pham, Professor Patrick Olivier

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

Obesity is an increasing problem for modern societies, which implies enormous financial burdens for public health-care systems. There is growing evidence that a lack of cooking and food preparation skills is a substantial barrier to healthier eating for a significant proportion of the population. We present the basis for a technological approach to promoting healthier eating by encouraging people to cook more often. We integrated tri-axial acceleration sensors into kitchen utensils (knifes, scoops, spoons), which allows us to continuously monitor the activities people perform while acting in the kitchen. A recognition framework is described, which discriminates ten typical kitchen activities. It is based on a sliding-window procedure that extracts statistical features for contiguous portions of the sensor data. These frames are fed into a Gaussian mixture density classifier, which provides recognition hypotheses in real-time. We evaluated the activity recognition system by means of practical experiments of unconstrained food preparation. The system achieves classification accuracy of ca. 90% for a dataset that covers 20 persons’ cooking activities.


Publication metadata

Author(s): Ploetz T, Moynihan P, Pham C, Olivier P

Editor(s): Chen, L., Nugent, C.D., Biswas, J., Hoey, J.

Publication type: Book Chapter

Book Title: Activity Recognition in Pervasive Intelligent Environments

Year: 2011

Pages: 313-339

Edition: 1st

Series Title: Atlantis Ambient and Pervasive Intelligence

Publisher: Atlantis Press

Place Published: Amsterdam, Netherlands

URL: http://dx.doi.org/10.2991/978-94-91216-05-3_14

DOI: 10.2991/978-94-91216-05-3_14

Library holdings: Search Newcastle University Library for this item

ISBN: 9789078677420


Actions

Link to this publication


Share