In this section
@article{Hahne:2016:10.3389/fnins.2016.00114,
author = {Hahne, JM and Farina, D and Jiang, N and Liebetanz, D},
doi = {10.3389/fnins.2016.00114},
journal = {Frontiers in Neuroscience},
title = {A novel percutaneous electrode implant for improving robustness in advanced myoelectric control},
url = {http://dx.doi.org/10.3389/fnins.2016.00114},
volume = {10},
year = {2016}
}
TY - JOUR
AB - Despite several decades of research, electrically powered hand and arm prostheses are still controlled with very simple algorithms that process the surface electromyogram (EMG) of remnant muscles to achieve control of one prosthetic function at a time. More advanced machine learning methods have shown promising results under laboratory conditions. However, limited robustness has largely prevented the transfer of these laboratory advances to clinical applications. In this paper, we introduce a novel percutaneous EMG electrode to be implanted chronically with the aim of improving the reliability of EMG detection in myoelectric control. The proposed electrode requires a minimally invasive procedure for its implantation, similar to a cosmetic micro-dermal implant. Moreover, being percutaneous, it does not require power and data telemetry modules. Four of these electrodes were chronically implanted in the forearm of an able-bodied human volunteer for testing their characteristics. The implants showed significantly lower impedance and greater robustness against mechanical interference than traditional surface EMG electrodes used for myoelectric control. Moreover, the EMG signals detected by the proposed systems allowed more stable control performance across sessions in different days than that achieved with classic EMG electrodes. In conclusion, the proposed implants may be a promising interface for clinically available prostheses.
AU - Hahne,JM
AU - Farina,D
AU - Jiang,N
AU - Liebetanz,D
DO - 10.3389/fnins.2016.00114
PY - 2016///
SN - 1662-4548
TI - A novel percutaneous electrode implant for improving robustness in advanced myoelectric control
T2 - Frontiers in Neuroscience
UR - http://dx.doi.org/10.3389/fnins.2016.00114
UR - http://hdl.handle.net/10044/1/44388
VL - 10
ER -