A neural interface is a system that establishes a communication pathway between the nervous system and an external device, translating neural activity into machine-readable signals or delivering stimulation back to neural tissue. Interfaces range from non-invasive surface electrodes that read muscle or scalp potentials to implanted electrodes that record from or stimulate individual neurons. They enable direct neural control of prosthetics, robots, and computers, and the restoration of sensory feedback.
Overview
- Bridges biological neural activity and engineered systems in both the read and write directions.
- Spans a spectrum from non-invasive surface sensing to fully implanted electrode arrays.
- Couples neuroscience, signal processing, and machine learning to decode intent from noisy signals.
Key aspects
- Signal acquisition from electromyographic, electroencephalographic, or intracortical sources.
- Decoding pipelines, often machine-learned, that map neural patterns to control commands.
- Sensory feedback channels delivering stimulation to restore touch or proprioception.
- Biocompatibility, longevity, and safety constraints on implanted electrodes.
- Real-time, low-latency control loops linking the user, decoder, and device.
Applications
- Myoelectric control of advanced prosthetic limbs.
- Brain-controlled robots, wheelchairs, and assistive devices.
- Restoring communication for people with severe motor impairment.
- Closed-loop neurostimulation and sensory-feedback systems.