TY - GEN
T1 - How many channels are enough?
T2 - 26th European Signal Processing Conference, EUSIPCO 2018
AU - Janani, Azin S.
AU - Grummett, Tyler S.
AU - Bakhshayesh, Hanieh
AU - Lewis, Trent W.
AU - Willoughby, John O.
AU - Pope, Kenneth J.
PY - 2018/11/29
Y1 - 2018/11/29
N2 - Scalp electrical recordings, or electroencephalograms (EEG), are heavily contaminated by cranial and cervical muscle activity from as low as 20 hertz, even in relaxed conditions. It is therefore necessary to reduce or remove this contamination to enable reliable exploration of brain neurophysiological responses. Scalp measurements record activity from many sources, including neural and muscular. Independent Component Analysis (ICA) produces components ideally corresponding to separate sources, but the number of components is limited by the number of EEG channels. In practice, at most 30% of components are cleanly separate sources. Increasing the number of channels results in more separate components, but with a significant increase in costs of data collection and computation. Here we present results to assist in selecting an appropriate number of channels. Our unique database of pharmacologically paralysed subjects provides a way to objectively compare different approaches to achieving an ideal, muscle free EEG recording. We evaluated an automatic muscle-removing approach, based on ICA, with different numbers of EEG channels: 21, 32, 64, and 115. Our results show that, for a fixed length of data, 21 channels is insufficient to reduce tonic muscle artefact, and that increasing the number of channels to 115 does result in better tonic muscle artefact reduction.
AB - Scalp electrical recordings, or electroencephalograms (EEG), are heavily contaminated by cranial and cervical muscle activity from as low as 20 hertz, even in relaxed conditions. It is therefore necessary to reduce or remove this contamination to enable reliable exploration of brain neurophysiological responses. Scalp measurements record activity from many sources, including neural and muscular. Independent Component Analysis (ICA) produces components ideally corresponding to separate sources, but the number of components is limited by the number of EEG channels. In practice, at most 30% of components are cleanly separate sources. Increasing the number of channels results in more separate components, but with a significant increase in costs of data collection and computation. Here we present results to assist in selecting an appropriate number of channels. Our unique database of pharmacologically paralysed subjects provides a way to objectively compare different approaches to achieving an ideal, muscle free EEG recording. We evaluated an automatic muscle-removing approach, based on ICA, with different numbers of EEG channels: 21, 32, 64, and 115. Our results show that, for a fixed length of data, 21 channels is insufficient to reduce tonic muscle artefact, and that increasing the number of channels to 115 does result in better tonic muscle artefact reduction.
KW - Electroencephalogram
KW - Electromyogram
KW - Independent Component Analysis
KW - Muscle reduction
KW - Number of channels
UR - http://www.scopus.com/inward/record.url?scp=85059824604&partnerID=8YFLogxK
U2 - 10.23919/EUSIPCO.2018.8553261
DO - 10.23919/EUSIPCO.2018.8553261
M3 - Conference contribution
AN - SCOPUS:85059824604
T3 - European Signal Processing Conference
SP - 101
EP - 105
BT - 2018 26th European Signal Processing Conference, EUSIPCO 2018
PB - European Signal Processing Conference, EUSIPCO
CY - Rome, Italy
Y2 - 3 September 2018 through 7 September 2018
ER -