Electroencephalography-based Motor Hotspot Detection

Ga-Young Choi, Chang-Hee Han, Hyunmi Lim, Jeonghun Ku, Won-Seok Kim, Han-Jeong Hwang

Abstract

The motor-evoked potential (MEP) induced by transcranial magnetic stimulation (TMS) has been generally used to identify a motor hotspot, and it has been used as a target location for transcranial electrical stimulation (tES). However, the traditional MEP-based method needs a bulky TMS device, and it involves the empirical judgement of an expert. In this study, we propose a machine-learning-based motor hotspot identification method using electroencephalography (EEG) that is portably acquired in a tES device. EEG data were measured from ten subjects while they performed a simple finger tapping task. Power spectral densities (PSDs) were extracted from the EEG data as features, and they were used to train and test artificial neural network (ANN). The 3D coordinate information of individual motor hotspots identified by TMS were also used as the ground-truth motor hotspot locations in ANN, and they were compared with those estimated by ANN. A minimum distance between the motor hotspots identified by TMS and EEG features was only 0.24 cm, demonstrating the feasibility of our proposed novel motor hotspot identification method based on EEG features.

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Paper Citation


in Harvard Style

Choi G., Han C., Lim H., Ku J., Kim W. and Hwang H. (2020). Electroencephalography-based Motor Hotspot Detection.In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, ISBN 978-989-758-398-8, pages 195-198. DOI: 10.5220/0008937201950198


in Bibtex Style

@conference{biosignals20,
author={Ga-Young Choi and Chang-Hee Han and Hyunmi Lim and Jeonghun Ku and Won-Seok Kim and Han-Jeong Hwang},
title={Electroencephalography-based Motor Hotspot Detection},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,},
year={2020},
pages={195-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008937201950198},
isbn={978-989-758-398-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS,
TI - Electroencephalography-based Motor Hotspot Detection
SN - 978-989-758-398-8
AU - Choi G.
AU - Han C.
AU - Lim H.
AU - Ku J.
AU - Kim W.
AU - Hwang H.
PY - 2020
SP - 195
EP - 198
DO - 10.5220/0008937201950198