EEG Derived Laterality Metrics as a Biomarker for of Upper Limb Recovery in Stroke

An Explorative Study into EEG Biomarkers for Longitudinal Stroke Recovery

Master thesis (2021)

Authors

G.C. Prins Mechanical Engineering

Contributors

F.C.T. van der Helm Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 1)
K. Rassels Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 2)
J. van der Cruijsen Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (coach)
Faculty
Mechanical Engineering
Copyright: © 2021 Gertrand Prins
EEG Diffusion MRI Stroke Somatosensory Evoked Potentials
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Published Date

31-08-2021

Language

English

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Faculty

Mechanical Engineering

Abstract

Problem: A biomarker that accurately predicts recovery of ischemic stroke for patients with poor baseline Fugl-Meyer Assessment of the Upper Extremity (FMA-UE) is lacking. Biomarkers that predict recovery while providing functional insight into the underlying neural process are highly desired for optimal clinical care. Objectives: This explorative study aims to determine potential biomarkers from Somatosensory Evoked Potentials (SEP) using ElectroEncephaloGraphy (EEG). Brain asymmetry metrics are derived from high-density EEG recordings of five longitudinal stroke patients during the first six months of stroke recovery. In addition, EEG sources and their interactions, constrained by anatomical information from (d)MRI, are explored for a potential biomarker. Results: Subjects with low baseline FMA-UE show a trend of increased recovery as the Laterality Index (LI) of the infarcted hemisphere increases, although it is not significant within this small group. The LI of the non-infarcted hemisphere shows a significant trend of high LI values at baseline that decrease to lower values during recovery. This effect was tested on a different dataset of 17 longitudinal stroke patients (without dMRI data). The results in this second group showed strong variability between subjects and measurements. The non-infarcted hemisphere is able to significantly predict the FMA-UE for both datasets. On the other hand, estimated effects for the LI of the infarcted hemisphere did not show significant values. Biomarkers were not derived from EEG sources and their interactions. Conclusion: In this study, we have demonstrated the potential of the LI as a biomarker for stroke recovery. Small sample size and absence of controls make hard clinical conclusions impossible. However, our findings show that the LI might predict recovery of the FMA-UE, even at low baseline FMA-UE. The LI of the non-infarcted hemisphere is able to significantly predict the FMA-UE of the affected hand, a surprising discovery that might be attributed to background cortical activity or ipsilateral SEP components. Derivations from EEG sources and their interactions might lead to more sensitive metrics and novel insights into stroke rehabilitation. Significance: If the discovered trends apply to a larger sample size, asymmetry metrics from SEP’s have prognostic value in stroke recovery.