Andrew Decker

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About

Andrew Decker is a leading researcher in neural engineering and brain-computer interfaces (BCIs), with a focus on noninvasive neuroprosthetics for motor rehabilitation. His most-cited work, "Noninvasive control of a robotic arm in multiple dimensions using scalp electroencephalogram" (2013, 13 citations), demonstrated that scalp-recorded EEG signals could be harnessed to control a robotic arm in multiple dimensions, offering a promising avenue for individuals with impaired motor function, including those recovering from stroke. This study challenged the prevailing assumption that invasive implants were necessary for high-dimensional prosthetic control, showing that healthy and post-stroke participants could achieve real-time, multidimensional manipulation of a robotic limb without surgical intervention. Decker’s contributions bridge fundamental neuroscience and translational engineering, advancing the feasibility of accessible, low-risk assistive technologies. His work has been cited in subsequent BCI and rehabilitation robotics studies, underscoring its influence on noninvasive motor decoding. By prioritizing practical, user-centered designs, Decker continues to shape the future of neurorehabilitation, empowering individuals with severe motor disabilities to regain interaction with their physical environment.