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Related Experiment Video

Updated: May 9, 2026

Assessment and Communication for People with Disorders of Consciousness

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

Sensors and decoding for intracortical brain computer interfaces.

Mark L Homer¹, Arto V Nurmikko, John P Donoghue

¹Biomedical Engineering, Brown University, Providence, RI 02912, USA.

Annual Review of Biomedical Engineering

|July 19, 2013

Summary

This summary is machine-generated.

Intracortical brain computer interfaces (iBCIs) use implanted sensors and decoding software to translate neural activity into device control. Recent innovations enhance iBCI capability, accuracy, and longevity for clinical use.

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Area of Science:

Biomedical Engineering
Neuroscience
Rehabilitation Technology

Background:

Intracortical brain computer interfaces (iBCIs) offer a pathway for individuals with severe paralysis to control external devices.
Effective iBCI functionality relies on high-performance neural sensors and sophisticated decoding algorithms.

Purpose of the Study:

To review recent advancements in sensor technology and decoding software for iBCIs.
To highlight innovations poised for adoption within the iBCI research community.
To discuss the impact of these advancements on iBCI performance and clinical applicability.

Main Methods:

Focus on recent developments in implanted neural sensors.
Analysis of advancements in software algorithms for neural signal decoding.
Review of research contributions relevant to the iBCI community.

Main Results:

Innovations are improving the capability and accuracy of iBCI systems.
Progress in sensor and decoding technologies is enhancing system longevity.
These advancements are expanding the potential for future clinical applications of iBCIs.

Conclusions:

Recent technological progress in sensors and decoding is crucial for iBCI development.
Enhanced iBCI performance is paving the way for broader clinical adoption.
Continued innovation is key to realizing the full potential of iBCIs for individuals with motor impairments.