Simon Homölle1, Robert Oostenveld2. 1. Donders Institute for Brain, Cognition and Behaviour, Radboud University, Kapittelweg 29, 6525 EN Nijmegen, the Netherlands. Electronic address: s.homolle@donders.ru.nl. 2. Donders Institute for Brain, Cognition and Behaviour, Radboud University, Kapittelweg 29, 6525 EN Nijmegen, the Netherlands; NatMEG, Karolinska Institute, Solnavägen 1, 171 77 Solna, Sweden.
Abstract
BACKGROUND: In this study, we evaluated the use of a structured-light 3D scanner for EEG electrode digitization. We tested its accuracy, robustness and evaluated its practical feasibility. Furthermore, we assessed how 3D scanning of EEG electrode positions affects the accuracy of EEG volume conduction models and source localization. NEW METHOD: To assess the improvement in electrode positions and source results, we compared the electrode positions both at the scalp level and by quantifying source model accuracy between the 3D scanner, generic template, and cap-specific electrode positions. RESULTS AND COMPARISON WITH EXISTING METHODS: The use of the 3D scanner significantly improves the accuracy of EEG electrode positions to a median error of 9.4 mm and maximal error of 32.8 mm, relative to the custom (median error of 10.9 mm, maximal error 39.1 mm) and manufacturer's template positions (median error of 13.8 mm, maximal error 57.0 mm). The relative difference measure (RDM) of the EEG source model averaged over the brain improves from 0.18 to 0.11. The dipole localization error averaged over the brain improves from 11.4 mm to 7.0 mm. CONCLUSION: A structured-light 3D scanner improves the electrode position accuracy and thereby the EEG source model accuracy. It is more affordable than systems currently used for this, and allows for robust and fast digitization. Therefore, we consider it a cost and time-efficient way to improve EEG source reconstruction.
BACKGROUND: In this study, we evaluated the use of a structured-light 3D scanner for EEG electrode digitization. We tested its accuracy, robustness and evaluated its practical feasibility. Furthermore, we assessed how 3D scanning of EEG electrode positions affects the accuracy of EEG volume conduction models and source localization. NEW METHOD: To assess the improvement in electrode positions and source results, we compared the electrode positions both at the scalp level and by quantifying source model accuracy between the 3D scanner, generic template, and cap-specific electrode positions. RESULTS AND COMPARISON WITH EXISTING METHODS: The use of the 3D scanner significantly improves the accuracy of EEG electrode positions to a median error of 9.4 mm and maximal error of 32.8 mm, relative to the custom (median error of 10.9 mm, maximal error 39.1 mm) and manufacturer's template positions (median error of 13.8 mm, maximal error 57.0 mm). The relative difference measure (RDM) of the EEG source model averaged over the brain improves from 0.18 to 0.11. The dipole localization error averaged over the brain improves from 11.4 mm to 7.0 mm. CONCLUSION: A structured-light 3D scanner improves the electrode position accuracy and thereby the EEG source model accuracy. It is more affordable than systems currently used for this, and allows for robust and fast digitization. Therefore, we consider it a cost and time-efficient way to improve EEG source reconstruction.
Authors: Orsolya Györfi; Cheng-Teng Ip; Anders Bach Justesen; Maria Louise Gam-Jensen; Connie Rømer; Martin Fabricius; Lars H Pinborg; Sándor Beniczky Journal: Clin Neurophysiol Pract Date: 2022-05-02
Authors: Ryan M Hill; Elena Boto; Molly Rea; Niall Holmes; James Leggett; Laurence A Coles; Manolis Papastavrou; Sarah K Everton; Benjamin A E Hunt; Dominic Sims; James Osborne; Vishal Shah; Richard Bowtell; Matthew J Brookes Journal: Neuroimage Date: 2020-05-29 Impact factor: 6.556