Detection of EMG onset in ERP research

Boxtel, G.J.M. van; Geraats, L.H.D.; Berg-Lenssen, M.M.C. van den; Brunia, C.H.M.

doi:10.1111/j.1469-8986.1993.tb02062.x

Cited by 118 publications

(62 citation statements)

References 19 publications

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“…The signal was digitized at 1000 counts per second, full-wave rectified and filtered (bandwidth 25-300 HZ). The onset and cessation of muscle activity were both visually and mathematically determined by computing the EMG threshold voltage as described by Van Boxtel et al [13]. The EMG activity of each muscle was normalized to 100% time of pedalling cycle.…”

Section: Muscle Activitymentioning

confidence: 99%

Efficiency of work production by spastic muscles

et al. 2005

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Section: Muscle Activitymentioning

confidence: 99%

Efficiency of work production by spastic muscles

et al. 2005

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“…It was amplified, high-pass filtered at 20 Hz, full-wave rectified, and low-pass filtered at 50 Hz. The onset of muscle activity is gradual rather than discrete, and therefore computed off-line on single trials by an accurate statistical method described by Van Boxtel et al (1993). This method relies on a threshold voltage comparison supplemented with temporal analysis of each EMG burst, and results in an average absolute error of less than 5 ms.…”

Section: Recording and Analysis Of Psychophysiological Signalsmentioning

confidence: 99%

A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm

Boxtel

Molen

Jennings

et al. 2001

Biological Psychology

248

177

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A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm van Boxtel, Geert; van der Molen, M.; Jennings, J.R.; Brunia, Cees General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim. AbstractWe examined two potential inhibitory mechanisms for stopping a motor response. Participants performed a standard visual two-choice task in which visual stop signals and no-go signals were presented on a small proportion of the trials. Psychophysiological measures were taken during task performance to examine the time course of response activation and inhibition. The results were consistent with a horse race model previously proposed to account for data obtained using a stop-signal paradigm. The pattern of psychophysiological responses was similar on stop-signal and no-go trials suggesting that the same mechanism may initiate inhibitory control in both situations. We found a distinct frontal brain wave suggesting that inhibitory motor control is instigated from the frontal cortex. The results are best explained in terms of a single, centrally located inhibition mechanism. Results are discussed in terms of current neurophysiological knowledge.

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“…However, it is felt that researchers should look into the accuracy oftheir method and report these accuracy findings in their papers. This survey and the study ofvan Boxtel, Geraats, et al (1993) merely provide some useful suggestions to this end.…”

Section: The Detection Ofemg Onsetmentioning

confidence: 99%

Computational and statistical methods for analyzing event-related potential data

Boxtel

1998

Behavior Research Methods, Instruments, & Computers

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Some computational and statistical techniques that can be used in the analysis of event-related potential (ERP) data are demonstrated. The techniques are fairly elementary but go one step further than do simple area measurement or peak picking, which are most often used in ERP analysis. Both amplitude and latency measurement techniques are considered. Principal components analysis (peA) and methods for electromyographic onset determination are presented in detail, and Woodyfiltering is discussed briefly. The techniques are introduced in a nontechnical, tutorial review style. One and the same existing data set is presented, to which the techniques are applied, and practical guidelines for their use are given. The methods are demonstrated against a background of theoretical notions that are related to the definition of ERP components.The electroencephalogram (EEG) is the record of the potential differences between electrodes placed on the (human) scalp. EEG records can be classified into two categories: the spontaneous or background EEG and event-related potentials (ERPs). The background EEG consists of periodic voltage fluctuations, which can be classified according to their frequency content-for instance, alpha (8-12 Hz), beta (13-30 Hz), gamma (31-50 Hz), delta (0.5-4 Hz), and theta (5-7 Hz). ERPs are discrete waveforms that are associated with an event. They are hidden within the background EEG and are visualized by averaging discrete EEG epochs that are synchronized to meaningful task events, such as the presentation ofa stimulus or the occurrence ofa response. Since the background EEG is not assumed to have a temporal relationship to the synchronization event, averaging of discrete EEG epochs will, when a sufficiently large number of epochs (trials) are averaged, result in its attenuation. The activity that does have a temporal relation to the event-the ERP-will then be enhanced in relation to the background EEG and thus become visible. If plotted in time, ERPs appear as a series of positive and negative deflections, which are thought to be the manifestation of underlying ERP components.This paper was prepared while the author was supported by NWO Grant 575-270-082B, awarded to M. W van der Molen and C. H. M. Brunia. The section on principal components analysis benefited from discussions with Marcel Croon of the Department of Statistics, Tilburg University. The useful suggestions ofMartin Eimer, Emanuel Donchin, and two anonymous reviewers are gratefully acknowledged. Correspondence concerning this paper should be addressed to G. 1. M. van Boxtel, Department of Psychology (P607), Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands (e-mail: g.j.m.vboxtel@kub.nl). 87ERP components may be exogenous or endogenousthat is, evoked by events that are extrinsic or intrinsic to the nervous system. The exogenous ERP components occur near the eliciting event, and the time relation to that event is very stable. When a stimulus is presented, for instance, the exogenous ERP components have an early onset l...

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Detection of EMG onset in ERP research

Cited by 118 publications

References 19 publications

Efficiency of work production by spastic muscles

Efficiency of work production by spastic muscles

A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm

Computational and statistical methods for analyzing event-related potential data

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