Ear-EEG allows extraction of neural responses in challenging listening scenarios — A future technology for hearing aids?

@article{Fiedler2016EarEEGAE,
  title={Ear-EEG allows extraction of neural responses in challenging listening scenarios — A future technology for hearing aids?},
  author={Lorenz Fiedler and Jonas Obleser and Thomas Lunner and Carina Graversen},
  journal={2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year={2016},
  pages={5697-5700}
}
  • L. Fiedler, J. Obleser, C. Graversen
  • Published 2016
  • Computer Science
  • 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Advances in brain-computer interface research have recently empowered the development of wearable sensors to record mobile electroencephalography (EEG) as an unobtrusive and easy-to-use alternative to conventional scalp EEG. One such mobile solution is to record EEG from the ear canal, which has been validated for auditory steady state responses and discrete event related potentials (ERPs). However, it is still under discussion where to place recording and reference electrodes to capture best… 

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References

SHOWING 1-10 OF 14 REFERENCES
A Study of Evoked Potentials From Ear-EEG
TLDR
The outcomes of this study demonstrate conclusively that the ear-EEG signals, in terms of the signal-to-noise ratio, are on par with conventional EEG recorded from electrodes placed over the temporal region.
An in-the-ear platform for recording electroencephalogram
  • D. Looney, C. Park, D. Mandic
  • Computer Science
    2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
  • 2011
TLDR
The proposed in-the-ear (ITE) recording platform promises a number of advantages including ease of implementation, minimally intrusive electrodes and enhanced accuracy (fixed electrode positions), which facilitates a crucial step towards the design of brain computer interfaces that integrate naturally with daily life.
Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG.
TLDR
It is shown that single-trial unaveraged EEG data can be decoded to determine attentional selection in a naturalistic multispeaker environment and a significant correlation between the EEG-based measure of attention and performance on a high-level attention task is shown.
Magnetic brain activity phase-locked to the envelope, the syllable onsets, and the fundamental frequency of a perceived speech signal.
During speech perception, acoustic correlates of syllable structure and pitch periodicity are directly reflected in electrophysiological brain activity. Magnetoencephalography (MEG) recordings were
Selective cortical representation of attended speaker in multi-talker speech perception
TLDR
It is demonstrated that population responses in non-primary human auditory cortex encode critical features of attended speech: speech spectrograms reconstructed based on cortical responses to the mixture of speakers reveal the salient spectral and temporal features of the attended speaker, as if subjects were listening to that speaker alone.
BCI2000: a general-purpose brain-computer interface (BCI) system
TLDR
This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BCI2000 system is based upon and gives examples of successful BCI implementations using this system.
FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data
TLDR
FieldTrip is an open source software package that is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data.
Some Experiments on the Recognition of Speech, with One and with Two Ears
This paper describes a number of objective experiments on recognition, concerning particularly the relation between the messages received by the two ears. Rather than use steady tones or clicks
...
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