Creating beautiful sculptures derived from the state of a persons mind.

The MindSculpture data visualisations use a combination of accelerometer sensor readings for movement and pulse sensors for heart rate. These are captured from a users wearable or smartphone using a logging app. This data is then processed in OpenOffice Calc to smooth, combine axis, adjust ranges, etc. It’s then imported into Blender using a custom Animation Node graph. This allows parametric mesh creation and animation. Each parameter influences the shape of a 3D sculpture model. The model is created from splines deformed by a 3D curl noise field which with parameters which can be animated over time. Once the meshes are ready they are uploaded to Sheepit, the crowdsourced distributed render farm which distributes the raytracing of each frame, creating beautiful stills and animated sequences. The final images are sent back to the user to enjoy or share. Each sculpture is a unique record of a meditation session and a visual insight into your state of mind.

This project was part of the Solarflare Labs series where we experiment with new ideas and develop a proof of concepts for potential commercial projects or products. Images and videos posted on Instagram. Curl noise based on this great example.