Physiological Artifacts and the Implications for Brain-Machine-Interface Design

Abstract

The accurate measurement of brain activity by Brain-Machine-Interfaces (BMI) and closed-loop Deep Brain Stimulators (DBS) is one of the most important steps in communicating between the brain and subsequent processing blocks. In conventional chest-mounted systems, frequently used in DBS, a significant amount of artifact can be induced in the sensing interface, often as a common-mode signal applied between the case and the sensing electrodes. Attenuating this common-mode signal can be a serious challenge in these systems due to finite common-mode-rejection-ratio (CMRR) capability in the interface. Emerging BMI and DBS devices are being developed which can mount on the skull. Mounting the system on the cranial region can potentially suppress these induced physiological signals by limiting the artifact amplitude. In this study, we model the effect of artifacts by focusing on cardiac activity, using a current- source dipole model in a torso-shaped volume conductor. Performing finite element simulation with the different DBS architectures, we estimate the ECG common mode artifacts for several device architectures. Using this model helps define the overall requirements for the total system CMRR to maintain resolution of brain activity. The results of the simulations estimate that the cardiac artifacts for skull-mounted systems will have a significantly lower effect than non-cranial systems that include the pectoral region. It is expected that with a pectoral mounted device, a minimum of 60-80 dB CMRR is required to suppress the ECG artifact, depending on device placement relative to the cardiac dipole, while in cranially mounted devices, a 0 dB CMRR is sufficient, in the worst-case scenario. In addition, the model suggests existing commercial devices could optimize performance with a right-hand side placement. The methods used for estimating cardiac artifacts can be extended to other sources such as motion/muscle sources. The susceptibility of the device to artifacts has significant implications for the practical translation of closed-loop DBS and BMI, including the choice of biomarkers, the system design requirements, and the surgical placement of the device relative to artifact sources.

Keywords: Cranial mounted DBS; Current- source dipole model; Deep brain stimulation; ECG artifact; Finite element method.

Fig. 1

DBS Brain-Machine-Interface placements. (a) Pectoral mounted DBS device with electrodes extensions through the neck to the area of interest in the brain. (b) Cranial mounted DBS device. Source: Adapted from [4], [10].

Fig. 2

An example of a LFP differential sensing circuit used in DBS devices (a) Tissue electrode interface equivalent circuit and lead/extension routing, (b) DC blocking/high-pass filter, (c) passive low-pass differential filter. Source: Adapted from [10].

Fig. 3

3D torso and heart model. (a) Torso and heart geometry used for the FEM. The purple sphere inside the chest indicates the heart model and the red spots denote the hypothetical locations of the current dipole. (b) The finite element mesh used to subdivide the torso model into m sub-domains (Ω_n,n = 1,2, …, m).

Fig. 4

Cardiac activation maps in the pectoral region. Induced current density (I) and electric field (II) for dipole oscillations: (a) Only in the X direction $\left({\overrightarrow{J}}_{source,X}\ne 0,{\overrightarrow{J}}_{source,Y}=0,{\overrightarrow{J}}_{source,Z}=0\right).$ (b) Only in the Y direction $\left({\overrightarrow{J}}_{source,X}=0,{\overrightarrow{J}}_{source,Y}\ne 0,{\overrightarrow{J}}_{source,Z}=0\right).$ (c) Only in the z direction $\left({\overrightarrow{J}}_{source,X}\ne 0,{\overrightarrow{J}}_{source,Y}\ne 0,{\overrightarrow{J}}_{source,Z}\ne 0\right),$ (d) In all directions, as a superposition.

Fig. 5

ECG artifact at the skull. Induced current density (a) and electric field (b) for dipole oscillations in all directions $\left({\overrightarrow{J}}_{source,X}\ne 0,{\overrightarrow{J}}_{source,Y}\ne 0,{\overrightarrow{J}}_{source,Z}\ne 0\right),$ as a superposition.

Fig. 6

Estimated artifact ratios in different areas of the skull; includes Frontal, Temporal and Parietal regions, where A_J1 and A_J2 denote the current density artifact ratios for the first and second scenarios, A_E1 and A_E2 indicate the E-field artifacts for the first and second scenarios, respectively.

Fig. 7

The estimated potential difference for the first and second scenarios. (a) Chest cavity to a distant point in the middle of the brain (V₁ and V₂), as a common-mode ECG artifact for a chest mounted DBS and BMI systems, as shown in Fig. 1a. (b) From the same centre point to the top of the head (V₃ and V₄), as a metric used to quantify common mode ECG artifact for a cranialmount DBS and BMI systems, as shown in Fig. 1b. (c) Measuring locations of potential differences in the FEM model. V₁ and V₂ measurements were performed at a depth of 3 cm inside the pectoral region (Y direction). V₃ and V₄ potential differences were executed at a depth of 4 cm inside the head (Y direction).