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oai:figshare.com:article/13626395 2021-09-20T10:12:10Z category_26299 category_26407 portal_918 item_type_3 month_year_09_2021

ECG, EEG and IMU data for local motion artefact removal Christopher Beach (9981602) Mingjie Li (10018120) Ertan Balaban (10020330) Alex Casson (9979847) Biomedical engineering not elsewhere classified Signal processing EEG data electrocardiograms electroencephalogram (EEG) motion artefacts wearable sensors IMUs inertial measurement unit (IMU) Adaptive filtering multichannel adaptive filtering ECG Biomedical Engineering not elsewhere classified Signal Processing <div>ECG and EEG data collected from a single participant using our custom device with inertial measurement units (IMUs) placed on each electrode, to enable recording of local motion activity (accelerometer and gyroscope) during electrophysiological recordings. This is to enable improved motion artefact removal. Please see paper for description of the device, placement of the electrodes and testing procedure. </div><div><br></div><div>Data is in CSV format, with a sample rate of 220 Hz.</div><div><br></div>If using this data please cite:<div>C. Beach, M. Li, E. Balaban, and A. J. Casson, “Motion artefact removal in electroencephalography and electrocardiography by using multichannel inertial measurement units and adaptive filtering,” <i>Healthc. Technol. Lett.</i>, vol. 8, no. 5, pp. 128–138, 2021, doi: 10.1049/htl2.12016.</div><div><br><div><div>The columns of the csv files correspond as follows:<br></div><div><b>ECG:</b></div><div>x: Internal system timestamp</div><div>eeg1: V1 electrode</div><div>eeg2: V2 electrode</div><div>ax1: x-axis of accelerometer on V1</div><div>ay1: y-axis of accelerometer on V1</div><div>az1: z-axis of accelerometer on V1</div><div><div>gx1: x-axis of gyroscope on V1</div><div>gy1: y-axis of gyroscope on V1</div><div>gz1: z-axis of gyroscope on V1</div><div><div>ax2: x-axis of accelerometer on V2</div><div>ay2: y-axis of accelerometer on V2</div><div>az2: z-axis of accelerometer on V2</div><div><div>gx2: x-axis of gyroscope on V2</div><div>gy2: y-axis of gyroscope on V2</div><div>gz2: z-axis of gyroscope on V2</div><div><div>ax3: x-axis of accelerometer on REF</div><div>ay3: y-axis of accelerometer on REF</div><div>az3: z-axis of accelerometer on REF</div><div><div>gx3: x-axis of gyroscope on REF</div><div>gy3: y-axis of gyroscope on REF</div><div>gz3: z-axis of gyroscope on REF</div></div></div><div><div>ax4: x-axis of accelerometer on DRL</div><div>ay4: y-axis of accelerometer on DRL</div><div>az4: z-axis of accelerometer on DRL</div><div><div>gx4: x-axis of gyroscope on DRL</div><div>gy4: y-axis of gyroscope on DRL</div><div>gz4: z-axis of gyroscope on DRL</div></div></div><div><br></div></div></div><div><div><b>EEG:</b></div><div>x: Internal system timestamp</div><div>eeg1: T3 electrode</div><div>eeg2: T5 electrode</div><div>ax1: x-axis of accelerometer on T3</div><div>ay1: y-axis of accelerometer on T3</div><div>az1: z-axis of accelerometer on T3</div><div><div>gx1: x-axis of gyroscope on T3</div><div>gy1: y-axis of gyroscope on T3</div><div>gz1: z-axis of gyroscope on T3</div><div><div>ax2: x-axis of accelerometer on T5</div><div>ay2: y-axis of accelerometer on T5</div><div>az2: z-axis of accelerometer on T5</div><div><div>gx2: x-axis of gyroscope on T5</div><div>gy2: y-axis of gyroscope on T5</div><div>gz2: z-axis of gyroscope on T5</div><div><div>ax3: x-axis of accelerometer on REF</div><div>ay3: y-axis of accelerometer on REF</div><div>az3: z-axis of accelerometer on REF</div><div><div>gx3: x-axis of gyroscope on REF</div><div>gy3: y-axis of gyroscope on REF</div><div>gz3: z-axis of gyroscope on REF</div></div></div><div><div>ax4: x-axis of accelerometer on DRL</div><div>ay4: y-axis of accelerometer on DRL</div><div>az4: z-axis of accelerometer on DRL</div><div><div>gx4: x-axis of gyroscope on DRL</div><div>gy4: y-axis of gyroscope on DRL</div><div>gz4: z-axis of gyroscope on DRL</div></div></div></div></div></div></div></div><div><br></div><div>In our paper we take plot the following sections of data:<br></div><div><b>ECG:</b></div><div>Lines 1939:5039 (for the good filtering case)</div><div>Lines 7100:10200 (for the poor filtering case)</div><div><b>EEG:</b></div><div>Lines 7279:10439<br><div><br></div><div><br></div></div></div></div> 2021-09-20T10:12:10Z Dataset Dataset 10.48420/13626395 https://figshare.com/articles/dataset/ECG_EEG_and_IMU_data_for_local_motion_artefact_removal/13626395 CC BY 4.0