CTRL-labs developed a non-invasive neural interface wristband designed to decode hand and finger movement intent from peripheral neural signals. The system focused on capturing surface electromyography (sEMG) signals from the wrist to infer motor commands before physical movement occurs. Its hardware form factor enabled continuous, wearable use without requiring surgical intervention. The technology was developed as an input interface for digital devices rather than as a medical product.

The wristband records sEMG signals generated by motor neurons as they activate muscles in the hand and forearm. These signals are processed using machine learning algorithms to decode intended finger and hand movements in real time. By interpreting neural commands upstream of actual motion, the system enables low-latency control without relying on cameras or physical gestures. This approach allows subtle, gesture-free interaction with digital systems.

CTRL-labs positioned its technology as an input modality for human–computer interaction, particularly in augmented and virtual reality contexts. The platform was intended to enable more natural and precise control of digital environments compared to traditional controllers. Its acquisition by Meta reflects broader interest in neural and neuromuscular interfaces as foundational components for next-generation computing and immersive interfaces.