Ear-EEG Recording for Brain Computer Interface of Motor Task

Citation Author(s):
MindAmp Limited
MindAmp Limited
MindAmp Limited
Roy T.H
The Hong Kong Polytechnic University
Rosa H.M
The City University of Hong Kong
Submitted by:
Xiaoli Wu
Last updated:
Wed, 10/28/2020 - 02:30
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Ear-EEG recording collects brain signals from electrodes placed in the ear canal. Compared with existing scalp-EEG,  ear-EEG is more wearable and user-comfortable compared with existing scalp-EEG.

In this dataset, we collected ear-EEG signals and the scalp-EEG signals when subjects were performing a left/right hand grasping motor task.  We first validated the ear-EEG recordings by measuring the similarity of power ratio and channel correlation between ear-EEG and scalp-EEG signals. Then we applied  EEG  compact network  (EEGNet)  for classification of left/right-hand motor tasks using ear-EEG signals and scalp  EEG  signals separately.  Our results showed motor task classification based on ear-EEG has a high potential for the practical BCI applications in motor task. 



** Please note that this is under construction, and instruction is still being updated **




6 adults ( 2 males/ 4 females, age:22-28) participated in this experiment. The subjects were first given information about the study and then signed an informed consent form. The study was approved by the ethics committee at the  City  University of  Hong  Kong(Reference number:  2-25-201602_01).


Hardware and Software

We recorded the scalp-EEG using the a Neuroscan Quick Cap (Model C190) . Ear-EEG were recorded simultaneously with scalp-EEG. The 8 ear electrodes placed at the front and back ear canal (labeled as xF,  xB), and two upper and bottom positions in the concha (labeled as xOU and xOD). All ear and scalp electrodes were referenced to a  scalp  REF electrode.  The scalp  GRD  electrode  was  used as a  ground reference. The signals were sampled at 1000 Hz then filtered with a  bandpass filter between  0.5  Hz and  100  Hz together with a  notch filter to suppress the line noises.  The recording amplifier was SynAmps2,  and  Curry  7  was used for real-time data monitoring and collecting.


Experimental design

Subjects were seated  in front of a computer monitor. A fixation cross presented in  the center of  the monitor for 3s, followed by an arrow pseudo-randomly pointing to  the  right  or  left for 4s. During  the  4  s  arrow presentation, subjects needed to imagine and grasp the left or right hand according  to  the arrow direction. A short  warning beep was played  2  s  after the cross onset to call the subjects. 


Data Records

The data and the metadata from 6 subjects are stored in the IEEE Dataport. Note that Subject 1-4 completed 10 blocks of trials, subject 6 finished  only  5  blocks.  Each  block contained 16  trials.  In our dataset, each folder contain individual dataset from one subject.  For each individual dataset, there were four type of files (.dat, .rs3, .ceo, .dap). All four files were needed for EEGLAB and MNE package processing.  Each individual dataset contains the raw EEG data from 122 channels (from scale EEG recording), 8 channels (from ear EEG recording), and 1 channels (REF electrode). 

Individual dataset of subject 1,5,6 has different sub-datasets. The index indicates the time order of that sub-dataset (motor1, then followed by motor2, motor3, motor 4 etc).  While Individual dataset of subject 2,3,4 has one main dataset.

Each dataset has timestamps for epoch extraction. Two event labels marked the start of the arrow, which indicated the start of subject hand grasping (event number 1: left hand; event number 2: right hand).

Dataset Files

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