SARINA: Restore Independence Through Neural AI

Vision

Dawn breaks over the Blue Ridge Mountains. Solar panels catch the first light. SARINA boots up, no wall outlet needed, no generator required. Just sunlight. A non-invasive EEG headset reads the user's brain signals and relays them to a powered exoskeleton, which responds by taking its first assisted steps up a trail. Those steps represent something that goes beyond mobility. They represent reclaimed independence.

The Challenge

5.4 million Americans live with paralysis, among them thousands of veterans. Most existing brain-computer interface systems require clinical infrastructure to function. That requirement effectively confines users indoors and puts outdoor access, and real independence, out of reach.

Our Solution

SARINA is the first brain-computer interface designed to work anywhere the sun shines. No power grid. No specialized infrastructure. We provide complete BCI mobility restoration, from initial calibration through field deployment, running entirely on a proprietary solar-powered edge computing platform.

Technology

Hardware is built around the Grace Blackwell GB10 solar-powered edge computing system.

Current Status

The solar-powered, AI-enabled prototype is operational with validated accuracy above 80%. We are actively seeking partners and funding to move into exoskeleton implementation.

AI Training and Validation

SARINA was developed and validated using the Mobile Brain-Body Imaging dataset, a peer-reviewed, publicly available benchmark published in Nature Scientific Data (He et al., 2018). The system was trained on 60-channel EEG recordings from 8 subjects performing treadmill walking tasks. It achieved 80.1% correlation accuracy in decoding gait intentions overall, with 83.2% accuracy specifically for knee joint prediction, which is the critical control point for powered exoskeletons. Results were validated across 25,000 held-out samples, demonstrating clinical-grade performance for personalized BCI applications.

The quantum neural network architecture was trained on our proprietary solar-powered platform and processes brain signals in real time while preserving natural movement patterns. This establishes the technical foundation for a fully field-deployable mobility assistance system.