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Activity Recognition and Healthier Food Preparation

  • Thomas PlötzEmail author
  • Paula Moynihan
  • Cuong Pham
  • Patrick Olivier
Chapter
Part of the Atlantis Ambient and Pervasive Intelligence book series (ATLANTISAPI, volume 4)

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.

Keywords

Healthy Eating Activity Recognition Food Preparation Pervasive Computing Cooking Skill 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Atlantis Press 2011

Authors and Affiliations

  • Thomas Plötz
    • 1
    Email author
  • Paula Moynihan
    • 2
  • Cuong Pham
    • 1
  • Patrick Olivier
    • 1
  1. 1.School of Computing ScienceNewcastle UniversityNewcastle upon TyneUK
  2. 2.Institute for Ageing and HealthNewcastle UniversityNewcastle upon TyneUK

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