Movement Artifact Suppression in Wearable Low-Density and Dry EEG Recordings Using Active Electrodes and Artifact Subspace Reconstruction
Movement Artifact Suppression in Wearable Low-Density and Dry EEG Recordings Using Active Electrodes and Artifact Subspace Reconstruction
Blog Article
Wearable low-density dry electroencephalogram (EEG) headsets facilitate multidisciplinary applications of brain-activity decoding and brain-triggered interaction for healthy people in real-world scenarios.However, movement artifacts pose a great challenge to their validity in users with naturalistic behaviors (i.e., tanks without highly controlled settings in a laboratory).High-precision, high-density EEG instruments commonly embed an active electrode infrastructure and/or incorporate an auxiliary artifact subspace reconstruction (ASR) pipeline to handle movement artifact interferences.
Existing endeavors motivate this study to explore the efficacy of both hardware and software solutions in low-density and dry EEG recordings against non-tethered settings, which are rarely found in the literature.Therefore, this study employed a LEGO-like electrode-holder assembly grid to coordinate three 3-channel system designs (with passive/active dry vs.passive wet electrodes).It also conducted a simultaneous EEG recording while performing an oddball task during treadmill walking, with speeds of 1 and 2 KPH.The quantitative metrics of pre-stimulus noise, signal-to-noise ratio, and inter-subject correlation from the collected event-related potentials of 18 subjects were assessed.
Results indicate that while treating a passive-wet system as benchmark, only the active-electrode design more or less rectified movement artifacts for dry electrodes, whereas the ASR pipeline was substantially compromised by limited electrodes.These findings suggest that a lightweight, minimally obtrusive SENNA LEAVES dry EEG headset should at least equip an active-electrode infrastructure to withstand realistic movement artifacts for potentially sustaining its validity and applicability in real-world scenarios.