@article{wand2013application,
  title={Application of Electrode Arrays for Artifact Removal in an Electromyographic Silent Speech Interface},
  pages={300 - 312},
  year={2013},
  note={BIOSTEC 2013},
  journal={Biomedical Engineering Systems and Technologies International Joint Conference, Barcelona, Spain (Also in: Revised Selected Papers Communications in Computer and Information Science, Vol. 452)},
  url={https://www.csl.uni-bremen.de/cms/images/documents/publications/WandJankeSchultz_Application_Electrode_Arrays.pdf},
  abstract={An electromygraphic (EMG) Silent Speech Interface is a system which recognizes speech by capturing the electric potentials of the human articulatory muscles, thus enabling the user to communicate silently. This study deals with the introduction of multi-channel electrode arrays to the EMG recording system, which requires meticulous dealing with the resulting high-dimensional data. As a first application of the technology, Independent Component Analysis (ICA) is applied for automated artifact detection and removal. Without the artifact removal component, the system achieves optimal average Word Error Rates of 40.1% for 40 training sentences and 10.9% for 160 training sentences on EMG signals of audible speech. On a subset of the corpus, we evaluate the ICA artifact removal method, improving the Word Error Rate by 10.7% relative.},
  author={Wand, Michael and Janke, Matthias and Heistermann, Till and Schulte, Christopher and ,  and Himmelsbach, Adam and Schultz, Tanja}
}