Removal of Electrocardiogram Artifacts From Local Field Potentials Recorded by Sensing-Enabled Neurostimulator - Chen, Yue; Ma, Bozhi; Hao, Hongwei; Li, Luming (Frontiers in Neuroscience, 2021)
Sensing-enabled neurostimulator has been an advanced technology for chronic observation of brain activities. It shows great potentials in achieving closed-loop neuromodulation and implantable brain-computer interfaces. However, the local field potentials recorded by sensing-enabled neurostimulators could be contaminated with electrocardiogram (ECG) artifacts due to complex recording conditions and limited common-mode-rejection-ratio. In this study, we proposed a solution for removing the ECG artifacts in the local field potentials recorded by a sensing-enabled neurostimulator. A synchronized monopolar channel was added as ECG reference. Two pre-existing methods, i.e., template subtraction and adaptive filtering, were respectively applied. The results showed that the ECG artifacts could be successfully removed and the performance was not sensitive to residual stimulation artifacts. Our solution of ECG artifacts removal placed the sensing-enabled neurostimulator in a broader scheme of application.