Guggenberger R, Trunk BH, Canbolat S, Ziegler L, Gharabaghi A. Evaluation of signal analysis algorithms for ipsilateral motor-evoked potentials induced by transcranial magnetic stimulation.
J Neural Eng 2022;
19. [PMID:
35525187 DOI:
10.1088/1741-2552/ac6dc4]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 05/07/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE
Evaluating ipsilateral motor-evoked potentials (iMEP) induced by transcranial magnetic stimulation (TMS) is challenging. In healthy adults, isometric contraction is necessary to facilitate iMEP induction; therefore, the signal may be masked by the concurrent muscle activity. Signal analysis algorithms for iMEP evaluation need to be benchmarked and evaluated.
APPROACH
An open analysis toolbox for iMEP evaluation was implemented on the basis of eleven previously reported algorithms, which were all threshold based, and a new template-based method based on data-driven signal decomposition. The reliability and validity of these algorithms were evaluated with a dataset of 4244 iMEP from 55 healthy adults.
MAIN RESULTS
iMEP estimation varies drastically between algorithms. Several algorithms exhibit high reliability, but some appear to be influenced by background activity of muscle preactivation. Especially in healthy subjects, template-based approaches might be more valid than threshold-based ones. Measurement of iMEP persistence requires algorithms that reject some trials as MEP negative. The stricter the algorithms reject trials, the less reliable they generally are. Our evaluation identifies an optimally strict and reliable algorithm.
SIGNIFICANCE
We show different benchmarks and propose application for different use cases.
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