Chewing Jockey: Augmented food texture by using sound based on the cross-modal effect

We focus on the dining and show how to improve dining experience. We use sound effects to augment food texture, creating a cross-modal illusion. Our system is composed of a bone-conduction speaker, a microphone, a photoreflector to measure the motion of jaw, and a computer to design the sound effect or filtering. We focus on the texture of food, an important component of deliciousness, to enhance the eating experience without modifying the physical or chemical feature of the food. We use prevailing technologies to detect chewing action, feedback and process the chewing sound. In addition, we design some chewing augmentation filter for each foods. These combinations create the cross-modality effect for food texture. We have developed three elements. First is a bite-detection sensor, utilizing a photoreflector, to measure the movement of the lower jaw. Second is a sound filter for each type of food that will be used to control food texture. Third is a self-feedback system to enhance the chewing action that records the chewing sound and the jaw motion, and delivers it to the user using bone-conduction speakers. Our aim is to redesign the experience of eating. We believe this technology is useful for following situations. For a start, it is a challenge to improve the eating QoL for dentures users. As they cannot bite strongly, they get a reduced sensation of food. Chewing Jockey helps to restore that sensation. Another application is to moderate the chewing speed. Chewing too fast is not good for digestion and also leads to over-eating. With our technology, we can provide the most suitable chewing speed to alter such habits. Lastly, chewing can be a form of interaction for a novel game design, in which you could role-play a monster chewing on "living" things.