Objective
In functional electrophysiological imaging, signals are often contaminated by interference that can be of considerable magnitude compared to the signals of interest. This paper proposes a novel algorithm for removing such interferences that does not require separate noise measurements.
Approach
The algorithm is based on a dual definition of the signal subspace in the spatial- and time-domains. Since the algorithm makes use of this duality, it is named the dual signal subspace projection (DSSP). The DSSP algorithm first projects the columns of the measured data matrix onto the inside and outside of the spatial-domain signal subspace, creating a set of two preprocessed data matrices. The intersection of the row spans of these two matrices is estimated as the time-domain interference subspace. The original data matrix is projected onto the subspace that is orthogonal to the interference subspace
Main results
The DSSP algorithm is validated first by using the computer generated data, and then by using two sets of real biomagnetic data: SCEF data measured from a healthy volunteer and MEG data from a patient with a vagus nerve stimulator.
Significance
The proposed DSSP algorithm is effective for removing overlapped interference in a wide variety of biomagnetic measurements.
This paper develops a novel method to reduce the influence of stimulus-induced artifacts in functional spinal cord imaging. The developed method employes a two-step procedure. The first step acquires artifact data, which contain artifacts but do not contain spinal cord evoked magnetic field (SCEF). The second step applies a method called common-mode subspace projection (CSP). The effectiveness of the developed method is validated using SCEF data measured from a healthy volunteer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.