Steady-state analysis of somatosensory evoked potentials

Noss, Roger S.; Boles, Colby D.; Yingling, Charles D.

doi:10.1016/0168-5597(96)96011-6

Cited by 39 publications

(25 citation statements)

References 16 publications

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“…An alternative approach to elicit somatosensory SS-EPs is to bypass transduction processes altogether, by depolarizing directly afferent sensory nerve fibres. A number of studies have relied on transcutaneous electrical stimulation of a nerve trunk to selectively and directly activate large diameter thickly myelinated Aβ-fibres involved in the perception of touch [2,13,34,41,46,54,60]. Similarly, we recently showed that intra-epidermal electrical stimulation to deliver very focal currents restricted to the epidermis can be used to activate nociceptive free nerve endings selectively [47] and, thereby, elicit nociceptive SS-EPs [13].…”

Section: Rapid Periodic Stimulation Of Somatosensory Afferentsmentioning

confidence: 99%

“…Using either transcutaneous electrical stimulation [2,13,34,41,46,54,60] ERPs (e.g., the N20 wave following electrical stimulation of the median nerve) [15,61]. Nevertheless, through a direct comparison of both types of responses,…”

Section: Vibrotactile Somatosensory Steady-state Evoked-potentialmentioning

confidence: 99%

“…As compared to methods based on the recording of transient ERPs, but also as compared to other non-invasive methods to sample brain activity in humans such as functional MRI, investigating brain function using SS-EPs offers several outstanding advantages. First, studies performed in other sensory modalities have shown that SS-EPs exhibit a high signal-to-noise ratio [42,54,79]. Hence, nociceptive SS-EPs could be used to sample neural activity that cannot be sampled reliably using other techniques.…”

Section: Introductionmentioning

confidence: 99%

“…However, if such responses can be identified, they would open a new door to study directly the cortical mechanisms involved in multimodal perceptual integration [17,39].6. Clinical applicationsA small number of studies have highlighted the potential clinical usefulness of recording vibrotactile SS-EPs[54,60]. One advantage over the recording of transient ERPs is the high signal-to-noise ratio of the elicited responses and, hence, the short time required to obtain reliable signals.…”

mentioning

confidence: 99%

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Steady-state evoked potentials to study the processing of tactile and nociceptive somatosensory input in the human brain

Colon¹,

Legrain²,

Mouraux³

2012

Neurophysiologie Clinique/Clinical Neurophysiology

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Section: Rapid Periodic Stimulation Of Somatosensory Afferentsmentioning

confidence: 99%

Section: Vibrotactile Somatosensory Steady-state Evoked-potentialmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Steady-state evoked potentials to study the processing of tactile and nociceptive somatosensory input in the human brain

Colon¹,

Legrain²,

Mouraux³

2012

Neurophysiologie Clinique/Clinical Neurophysiology

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“…Efforts to reduce the number of trials have used techniques such as parametric decomposition (Bai et al, 2001), Bayesian analysis (Truccolo et al, 2003) and digital filters (Friedman et al, 1991). Another study reported the use of amplitude-modulated stimulus while performing steady-state analysis on the recorded signals (Noss et al, 1996). Also, the latency as the time difference between successive trials was used for noise removal (Kong and Oiu, 2001).…”

Section: Literature Surveymentioning

confidence: 99%

A Novel Signal Processing Method for Intraoperative Neurophysiological Monitoring in Spinal Surgeries

Vedala¹

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My mentor Dr. Malek Adjouadi has taught me a great deal in professional, personal and intellectual development. He has always had my best interest at heart and has provided me with every opportunity to grow. I am grateful for all the kindness and patience that he has shown me over the years. I would like to thank my gurus, Dr.Armando Barreto, Dr. Jean Andrian and Dr. Naphtalie Rishe, naming a few, whose trials to obtain an SSEP signal, which is excessive and introduces a significant delay to prevent potential neurological risks during surgery. The main objective of this dissertation is to develop a means to obtain the SSEP signal using a much reduced number of trials (20 trials or less) while still optimizing the effectiveness of the monitoring system. The preliminary research steps were to determine those characteristics that distinguish the SSEP with the ongoing brain activity. We first established that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded.A novel algorithm is subsequently developed using Chebyshev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasistationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised vii when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials.In this study, the analysis was performed on the data recorded in 29 patients who underwent surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp EEG. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm took on an average 4sec to extract an SSEP signal, as compared to conventional methods, which take up to several minutes.The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provided for a much improved and effective neurophysiological monitoring process.

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