Individual finger control of a modular prosthetic limb using high-density electrocorticography in a human subject

2016205 citationsJournal Articlegreen Open Access

Authors

Guy Hotson · Johns Hopkins University

David P. McMullen · Johns Hopkins University

Matthew S. Fifer · Johns Hopkins University

Matthew S. Johannes · Johns Hopkins University Applied Physics Laboratory

Kapil D. Katyal · Johns Hopkins University Applied Physics Laboratory

Matthew P. Para · Johns Hopkins University Applied Physics Laboratory

Robert S. Armiger

Abstract

Our results demonstrate the ability of ECoG-based BMIs to leverage the native functional anatomy of sensorimotor cortical populations to immediately control individual finger movements in real time.

Topics & Keywords

EEG and Brain-Computer Interfaces Neuroscience and Neural Engineering Advanced Memory and Neural Computing

UN Sustainable Development Goals

Reduced inequalities

Publication Details

Published in: Journal of Neural Engineering

Volume 13, Issue 2, pp. 026017-026017

DOI: 10.1088/1741-2560/13/2/026017

Field-Weighted Citation Impact: 13.66