This hybrid art + science experiment coalesces three topics - (1) embodied cognition, (2) EEG neurofeedback, and (3) meditating on Light. It is an artistic project to explore the subject of meditation and self-awareness through embodied cognition and brain waves.
Inner Light provides guided audio-visual cues based on a player’s brain activity (EEG) to induce a relaxed but focused mental state. It offers an unique conceptualization of the body-mind complex, asking questions about who we are in relation to our body + mind, and who we are beyond it. Through this experience, I invite participants to embody their own mental frequencies and, at the climax, discover the feeling of ascending the body.
See full documentation or explainer video.
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Onboarding for EEG Calibration in VR
I designed a UI to onboard users to the EEG calibration process while wearing the VR headset. This was essential to connect the EEG data session to the start of the meditation. Also the UI gives direct feedback on the "focus", "stress" and "relaxation" levels to the user.
Setup: Hardware + Software
- Emotiv Insight (hardware) is an EEG headset with 5 channels (AF3, AF4, T7, T8, Pz) and it transmits the raw signal data wirelessly through bluetooth to the computer.
- Emotiv Launcher (software) connects with the EEG headset and streams data over the cloud for processing/decoding using JSON and websockets to send/receive data.
- Cortex API for Unity (software) plugs into Unity and communicates with the Emotiv Launcher to receive processed data from the cloud. This data can then be utilized within the game engine to control parameters.
- Oculus Rift / HTC Vive (hardware) as PC VR setup, currently running on a MSI laptop. My input system (XRTK) within Unity is agnostic to hardware.
- VR application (game) is the prototype itself in which all the components come together audio-visually. It deals with the context and experiential aspect. The design decisions are based on my research and artistic vision.
User Testing
The VR experience was extensively tested with a range of people and iteratively improved through user testing and feedback. I also encountered challenges like variability in EEG data and had to adapt my VR experience to account for that variability without losing fidelity.
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Github Repo
