Hybrid Body
Hybrid Body is building a wearable EEG headband that lets people control everyday devices using signals from their brain!
Background
Large medical companies face real costs and risks, so promising ideas may never get a chance to be explored when their commercial value is unclear. We started Hybrid Body to give students the freedom to explore these ideas in human health and turn their curiosity and lived experiences into physical engineering prototypes.
For people with limited motor control, everyday actions like using a mouse, typing on a keyboard, or operating a remote can be difficult. What if they could control these devices using signals from their brain?
Our current project explores this possibility as we are designing a wearable neural interface. The idea is to build a wearable EEG band with electrodes that sit against the scalp to record the brain’s electrical activity. Alongside the cap, we’re developing software that uses signal processing and machine learning to identify patterns associated with imagined movement and translate them into device commands. We’re starting with computer cursor control, with the longer-term goal of extending this approach to devices such as custom prosthetic joints.
Goals
Our first milestone is a working prototype that connects an EEG headset to a computer and demonstrates basic cursor control. We’re designing an adjustable headband, exploring dry electrodes, and developing the electronics needed to collect and transmit signals from eight EEG channels.
Alongside the hardware, we’re building software to process recordings, reduce interference from movement and eye activity, and identify patterns that can be mapped to commands. We’ll use existing motor-imagery datasets and explore calibration for individual users as we develop and test the system.
Through prototyping and integration, we aim to improve signal quality, responsiveness, comfort, and ease of use, building a foundation for future control of other everyday electronic devices.
Relevant Skills
Python, C/C++, EEG signal processing, machine learning, data analysis and visualization, microcontrollers, wireless communication, circuit and PCB design, KiCad, CAD modeling, FreeCAD, 3D printing, soldering, human-centered design, and UI/UX.