Emolleia

Emolleia was inspired by a poem titled "Shy Flower"

To the little shy flower;
hiding beneath brush "
petals extended
smiles
pink-white colors
for the butterfly she drew

Emolleia is an emotive 3D-printed wearable that recognise and response to onlooker’s facial expressions by dynamically moves and illuminated. This project explores how wearable technology can support our unconscious emotional expression and enhance social interaction, while also emphasising a fashionable, aesthetically engaging design approach.

Inspired by the natural world, where animals shift their hues and plants morph in form to communicate or survive, this project ventures into the unspoken language of emotions. Like nature’s own silent dialogue, the wearable device mirrors these transformations, allowing users to express their inner feelings through fluid changes in colour, shape, and movement. We aim to explore the possibility between fashion garments, technology and design.

Three blooming transparent flowers form an accessory that can be worn around the shoulder. With a webcam turned on, the onlooker's facial expression will be detected and categorized. Each of the three flowers has been equipped with an LED light unit inside to enable color changes, aiding in better expressing the wearer's emotions.

- PROTOTYPE

The device was constructed by three main parts, flowers, servo motors case and a steel chain to fix the device on the body. The 3d printing flowers are fixed at the stem and consist of five petals with a diameter of 6 [cm]. We chose Elastic 50A resin as flower’s material since the softness allows the prototype to bend over and reform motion freely, the special transparency of this material also matched our designed sketch.

- USER STUDY

To explore potential use cases, self-expression possibilities and the general perception of the prototype, We conducted a user survey with 50 participants to elicit potential use and application cases. We evaluated 8 designed animated motions of Emolleia regarding their perceived emotional qualities using the self-assessment Manikin. Several animated motions show significant differences for perceived valence and arousal. Based on the mapping to the emotion model, we picked three obviously distinguishable animated motions for our next stage user studies.