The sensitivity of ECG contamination to surgical implantation site in brain computer interfaces.

Abstract

BACKGROUND:

Brain sensing devices are approved today for Parkinson's, essential tremor, and epilepsy therapies. Clinical decisions for implants are often influenced by the premise that patients will benefit from using sensing technology. However, artifacts, such as ECG contamination, can render such treatments unreliable. Therefore, clinicians need to understand how surgical decisions may affect artifact probability.

OBJECTIVES:

Investigate neural signal contamination with ECG activity in sensing enabled neurostimulation systems, and in particular clinical choices such as implant location that impact signal fidelity.

METHODS:

Electric field modeling and empirical signals from 85 patients were used to investigate the relationship between implant location and ECG contamination.

RESULTS:

The impact on neural recordings depends on the difference between ECG signal and noise floor of the electrophysiological recording. Empirically, we demonstrate that severe ECG contamination was more than 3.2x higher in left-sided subclavicular implants (48.3%), when compared to right-sided implants (15.3%). Cranial implants did not show ECG contamination.

CONCLUSIONS:

Given the relative frequency of corrupted neural signals, we conclude that implant location will impact the ability of brain sensing devices to be used for "closed-loop" algorithms. Clinical adjustments such as implant location can significantly affect signal integrity and need consideration.

• Authors: Wolf-Julian Neumann, Majid Memarian Sorkhabi, Moaad Benjaber, Lucia K Feldmann, Assel Saryyeva, Joachim K Krauss, Maria Fiorella Contarino, Tomas Sieger, Robert Jech, Gerd Tinkhauser, Claudio Pollo, Chiara Palmisano, Ioannis U Isaias, Daniel D Cummins, Simon J Little, Philip A Starr, Vasileios Kokkinos, Schneider Gerd-Helge, Todd Herrington, Peter Brown, R Mark Richardson, Andrea A Kühn, Timothy Denison
• Journal: Brain stimulation (Brain Stimul) 2021 Sep-Oct Vol. 14 Issue 5 Pg. 1301-1306 ISSN: 1876-4754 [Electronic] United States
• PMID: 34428554 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Topics

• Algorithms
• Artifacts
• Brain-Computer Interfaces
• Electrocardiography
• Essential Tremor
• Humans