January 23, 2018


  • Course

    Design <> Research

  • Coach

    Annika Hupfeld

  • Collaboration

    Maud Berbé, Noa Fischer, Syben van der Meer

When people are eating alone they tend to distract themselves with technology that is available to them, think of their laptop and the possibility to watch Netfix or a video on Youtube at any moment when they are bored, or the smartphone and all the apps available (e.g Instagram, WhatsApp, LinkedIn, Facebook). Indirectly resulting in the fact that those people, further referred to as technology- using consumers’ are not focusing on the action of eating, but more on all the data and other services elsewhere in the room. Technology with focused interaction causes different problems, one of them is that people will consume more than 15% more food than necessary. Tere is no doubt, technology can also be used to enhance the dining experience. Different ways are possible, and in our opinion when the product or service is designed in a way that it uses implicit or peripheral attention, and therefore the user itself can focus on the action of eating, while the technology in the product and/or service does its ‘job’ as may say.

We came up with Fo-ex, a product that will increase and/or alter the food experience with two different soundscapes; the soundscape of the cutlery and the soundscape of the ingredients of the meal. Designed for people that will eat
alone and are usually distracted by the surrounded technologies. Fo-ex is to be used on a daily base, and thus needs to ft into most dining experiences to motivate the user to add it to their current dining experiences. Its interaction asks peripheral or implicit attention, in order to let you focus on your food as much as possible. To make the implicit or peripheral attention possible it will use machine learning and three pressure sensors on top of three independent round sticks (for more, read ‘machine learning’). On those sticks lies a plate where the meal is served on.

The manner in which it affects the dining experience best, is to place it close to the user. This is needed since we’re working with sound, and thus need to take distances and the behaviour of sound waves into account. In order to do
this, a speaker will be implemented into Fo-ex. A point for attention is that the soundscapes need to be subtle enough that it won’t let to any distractions from the food, because that, in fact, will contradict with our goal.

In the pilot, several things were made very clear. One of those things required us to drastically change the way how the tests were done (e.g Wizard of Oz, pressing buttons to play different songs), and indirectly the design of Fe-Ox. An automatic system that would replace the “Wizard of Oz” prototype was the
solution to this problem. However, measuring how a person eats is quite difficult for a machine to do. This required more advanced programming. Te decision was made to use machine learning to learn different eating patterns and from these choose a song. A linear “support vector machine” learning model was used, because with this it is possible to train ‘it’ before serving each meal to the participant and updates to the model’s dataset were not required. Te input to the model were three pressure sensitive sensors which gave input to a Arduino that sends it further to a computer that runs a program on processing.

One of the most important aspects of our design are the soundscapes, for which we decided to use Chopin nocturnes’ with several instruments. With the main
reason the have a more fluent transition between the changes in soundscapes. There was made use of three instruments, that reflected three movements. Violin for
cutting, piano for pricking and guitar for stirring.

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