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

Abstract

Objective We used native sensorimotor representations of fingers in a brain-machine interface to achieve immediate online control of individual prosthetic fingers. Approach Using high gamma responses recorded with a high-density ECoG array, we rapidly mapped the functional anatomy of cued finger movements. We used these cortical maps to select ECoG electrodes for a hierarchical linear discriminant analysis classification scheme to predict: 1) if any finger was moving, and, if so, 2) which digit was moving. To account for sensory feedback, we also mapped the spatiotemporal activation elicited by vibrotactile stimulation. Finally, we used this prediction framework to provide immediate online control over individual fingers of the Johns Hopkins University Applied Physics Laboratory (JHU/APL) Modular Prosthetic Limb (MPL). Main Results The balanced classification accuracy for detection of movements during the online control session was 92% (chance: 50%). At the onset of movement, finger classification was 76% (chance: 20%), and 88% (chance: 25%) if the pinky and ring finger movements were coupled. Balanced accuracy of fully flexing the cued finger was 64%, and 77% had we combined pinky and ring commands. Offline decoding yielded a peak finger decoding accuracy of 96.5% (chance: 20%) when using an optimized selection of electrodes. Offline analysis demonstrated significant finger-specific activations throughout sensorimotor cortex. Activations either prior to movement onset or during sensory feedback led to discriminable finger control. Significance 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.

Histological evaluation of a chronically-implanted electrocorticographic electrode grid in a non-human primate

“…Encouraged by these findings, researchers have begun to investigate ECoG as a potential source of control signals for BMI devices. Human and non-human primate subjects have demonstrated up to three-dimensional control of computer cursors or prosthetic limbs using ECoG (Leuthardt et al, 2011; Schalk and Leuthardt, 2011; Leuthardt et al, 2004; Schalk et al, 2008; Wilson et al, 2006; Yanagisawa et al, 2012; Wang et al, 2013; Hotson et al, 2016). …”

Safety Assessment Strategy for Collaborative Robot Installations

“…Thought control of prosthetics has not only proved possible, but also has advanced to the level where individual fingers can be moved using thoughts only [18]. There is limited reason to believe that this trend will not continue towards a future where all machines that require human instruction, not only prostheses, will be the subject of studies of mind control.…”

Bioelectric Medicine and Devices for the Treatment of Spinal Cord Injury

“…Recent advances in microfabrication technology utilizing polyimide have enabled rapid improvements on ECoG electrode arrays [Rubehn et al, 2009]. High-density ECoG electrode arrays have recently been used to control individual articulating fingers [Hotson et al, 2016]. To date, the use of this technology in the clinic has been limited due to required surgery, and the reliance on transcutaneous electrical tethering.…”