RoamNeural Band
An open-source neural interface that reads your body, learns your patterns, and gives you precise control over any device—even under pressure.
Your Body. Your Interface. Your Control.
Roam is an open-source neural band that measures heart rate, muscle contractions, and electric signals—then uses AI to learn your unique patterns. It adapts to your stress and fatigue in real time, giving you reliable device control when it matters most. Built open, so every user can configure it to their needs.
Neural Control
EMG and electric signal sensing translates your muscle intent into precise device commands—no buttons, no screens, just you.
Adaptive Intelligence
AI/ML learns your specific patterns and adapts to fatigue and stress. When you're under pressure, the band dampens controls to prevent mistakes.
Open Source
Fully open hardware and software. Configure sensor thresholds, control mappings, and AI models to fit your exact use case. Run AI on-device to minimize costs.
Explore Our Features
Dive deep into each capability and discover how Roam gives you an edge in high-stress environments.
Control Devices With Your Body
EMG Signal Translation
Electromyography sensors capture the electrical activity in your muscles and translate micro-contractions into precise digital commands for connected devices.
Universal Device Control
Drones, robotic arms, industrial tools, surgical instruments—any Bluetooth-enabled device can be mapped to your muscle signals for hands-free operation.
Low-Latency Response
Sub-millisecond signal processing ensures your intent becomes action instantly—critical in high-stress, time-sensitive environments.
Stress-Aware Control Adjustment
Real-Time Fatigue Detection
The band continuously monitors muscle fatigue and stress biomarkers through EMG and heart rate variability, detecting when your performance may be compromised.
Adaptive Control Dampening
When stress or nervousness is detected, the band automatically adjusts control sensitivity—dampening inputs to prevent overcorrection and costly mistakes.
Safety Envelope
Configurable safety boundaries prevent extreme actions when the system detects you're operating outside your normal physiological range.
AI That Learns You
Personal Pattern Recognition
ML models train on your unique EMG signatures, heart rate patterns, and muscle responses—building a profile that gets more accurate over time.
On-Device Processing Option
Choose to run AI inference on your phone or computer's hardware instead of cloud APIs. Your data stays local, and your costs stay low.
Continuous Adaptation
The AI continuously refines its model as your patterns evolve—whether you're recovering from injury, building strength, or adapting to new equipment.
Break the Pattern
Habit Detection
The same EMG and muscle tracking sensors that enable device control can identify repetitive unwanted movements and behavioral patterns.
Real-Time Intervention
Gentle haptic feedback alerts you the moment a habit pattern is detected, creating awareness before the action completes.
Progress Tracking
Track your habit frequency over time. The AI learns which interventions work best for you and adapts its approach accordingly.
The Journey
From concept to reality—explore the evolution of Roam through our development milestones.
16 Iterations to Perfection
The path to the perfect prototype wasn't straightforward. It took 16 different iterations, each one teaching us something new about form, function, and sensor placement. Every prototype brought us closer to the ideal balance of comfort, wearability, and signal fidelity.
The First Working Prototype
This was the moment everything came together. The first working band that proved our concept was possible. It wasn't perfect, but it was real—a tangible proof that a neural control band could become reality.
Sensor Calibration & Testing
Extensive testing of various sensor configurations to understand signal quality, noise isolation, and optimal electrode placement. This phase was crucial for validating our approach and gathering training data for the AI models.
Dry Electrode EMG Sensing
Each link in the band contains a solid dry electrode that conforms to your wrist shape—no gels, no prep, no consumables. The chain-link design ensures consistent skin contact as you move, adapting to your unique anatomy for reliable signal capture.
These electrodes measure electrical signals from hand gestures, wrist movements, and muscle contractions. The array captures both surface EMG for gesture recognition and deeper muscle tension for fatigue monitoring, amplified by an LMP91000 analog front-end and streamed via the Seeed XIAO nRF52840 over Bluetooth.
What the Electrodes Measure
Join the Build
Roam is open source. Whether you're a hardware hacker, ML engineer, or someone who needs better device control—there's a place for you.
Currently in prototype development - Contribute or follow our progress!