Factors influencing the spatial precision of electromagnetic tracking systems used for MEG/EEG source imaging

Engels, Laurent; Tiège, Xavier De; Beeck, Marc Op De; Warzée, Nadine

doi:10.1016/j.neucli.2010.01.002

Cited by 22 publications

(36 citation statements)

References 8 publications

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“…However, the digitalizations take about 20–40 min or more when multiple electrodes systems are employed and are user dependent, as the user must touch each electrode in order to acquire it's position. A study from Engels et al (2010) further exposes some limitations and factors that influence the precision of systems such as FastTrack.…”

Section: Recording Hardware Software and Techniquesmentioning

confidence: 99%

Methodological aspects of EEG and body dynamics measurements during motion

Reis¹,

Hebenstreit

Gabsteiger

et al. 2014

Front. Hum. Neurosci.

130

111

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EEG involves the recording, analysis, and interpretation of voltages recorded on the human scalp which originate from brain gray matter. EEG is one of the most popular methods of studying and understanding the processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements that are performed in response to the environment. However, there are methodological difficulties which can occur when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions on how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics, and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determinating real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks.

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Section: Recording Hardware Software and Techniquesmentioning

confidence: 99%

Methodological aspects of EEG and body dynamics measurements during motion

Reis¹,

Hebenstreit

Gabsteiger

et al. 2014

Front. Hum. Neurosci.

130

111

View full text Add to dashboard Cite

show abstract

“…Furthermore, these methods are very user dependent, prone to user error even after extensive experience. Engels et al ( 2010 ) explores the factors influencing the precision of the FastTrack. In spite of these limitations, many laboratories, and manufacturers use the FastTrack system as the standard system to digitize electrodes.…”

Section: Introductionmentioning

confidence: 99%

Using a motion capture system for spatial localization of EEG electrodes

Reis¹,

Lochmann²

2015

Front. Neurosci.

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Electroencephalography (EEG) is often used in source analysis studies, in which the locations of cortex regions responsible for a signal are determined. For this to be possible, accurate positions of the electrodes at the scalp surface must be determined, otherwise errors in the source estimation will occur. Today, several methods for acquiring these positions exist but they are often not satisfyingly accurate or take a long time to perform. Therefore, in this paper we describe a method capable of determining the positions accurately and fast. This method uses an infrared light motion capture system (IR-MOCAP) with 8 cameras arranged around a human participant. It acquires 3D coordinates of each electrode and automatically labels them. Each electrode has a small reflector on top of it thus allowing its detection by the cameras. We tested the accuracy of the presented method by acquiring the electrodes positions on a rigid sphere model and comparing these with measurements from computer tomography (CT). The average Euclidean distance between the sphere model CT measurements and the presented method was 1.23 mm with an average standard deviation of 0.51 mm. We also tested the method with a human participant. The measurement was quickly performed and all positions were captured. These results tell that, with this method, it is possible to acquire electrode positions with minimal error and little time effort for the study participants and investigators.

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“…The Polhemus uses alternating current electromagnetic transmitters and sensors to measure positions in space. As a result, the surrounding electromagnetic environment, and even the Polhemus itself, can adversely affect the digitization result, making it error prone [9]. Furthermore, the low sampling rate of the device makes digitization of the whole head time consuming.…”

Section: Introductionmentioning

confidence: 99%

“…Laser scanners are insensitive to magnetic objects in the nearby environment and offer improved spatial sampling rate [9], [10]. However, the relative accuracy of laser scanning for surface and, consequently, source localization remains to be demonstrated.…”

Section: Introductionmentioning

confidence: 99%

Improved Localization Accuracy in Magnetic Source Imaging Using a 3-D Laser Scanner

Bardouille

Krishnamurthy

Hajra

et al. 2012

IEEE Trans. Biomed. Eng.

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Brain source localization accuracy in magnetoencephalography (MEG) requires accuracy in both digitizing anatomical landmarks and coregistering to anatomical magnetic resonance images (MRI). We compared the source localization accuracy and MEG-MRI coregistration accuracy of two head digitization systems-a laser scanner and the current standard electromagnetic digitization system (Polhemus)-using a calibrated phantom and human data. When compared using the calibrated phantom, surface and source localization accuracy for data acquired with the laser scanner improved over the Polhemus by 141% and 132%, respectively. Laser scan digitization reduced MEG source localization error by 1.38 mm on average. In human participants, a laser scan of the face generated a 1000-fold more points per unit time than the Polhemus head digitization. An automated surface-matching algorithm improved the accuracy of MEG-MRI coregistration over the equivalent manual procedure. Simulations showed that the laser scan coverage could be reduced to an area around the eyes only while maintaining coregistration accuracy, suggesting that acquisition time can be substantially reduced. Our results show that the laser scanner can both reduce setup time and improve localization accuracy, in comparison to the Polhemus digitization system.

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Factors influencing the spatial precision of electromagnetic tracking systems used for MEG/EEG source imaging

Abstract: The precision significantly decreases for this application in the following cases: (1) physical contacts between the stylus/transmitter/receiver cables, (2) presence of magnetic objects in the surrounding of the EMT system, (3) skin and hair softness and (4) subject's head movements.

Cited by 22 publications

References 8 publications

Methodological aspects of EEG and body dynamics measurements during motion

Methodological aspects of EEG and body dynamics measurements during motion

Using a motion capture system for spatial localization of EEG electrodes

Improved Localization Accuracy in Magnetic Source Imaging Using a 3-D Laser Scanner

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