03082nas a2200313   4500008004100000022001400041245013800055210006900193260001600262490000700278520206400285653001002349653002102359653002502380653002702405653003702432653001102469653001102480653000902491653001702500653001602517653003102533653002502564653001602589100001702605700002102622700001302643856011202656       2026                        eng d  a1741-255200aMethodological optimization for eliciting robust median nerve somatosensory evoked potentials for realtime single trial applications.0 aMethodological optimization for eliciting robust median nerve so  c2026 Jan 090 v233 a<p>Single-trial measurement of median nerve somatosensory evoked potentials (SEPs) with noninvasive electroencephalography (EEG) is challenging due to low signal-to-noise ratio (SNR), limiting its use in real-time neurorehabilitation applications. We describe and evaluate methodological optimizations for eliciting reliable median nerve SEPs measurable in real time, with reduced reliance on post-processing.In twelve healthy participants, two sessions each, SEPs were assessed at three pulse widths (0.1, 0.5, 1 ms), at a low-frequency stimulation (0.5 Hz ± 10%), and at an intensity sufficient to evoke consistent and robust sensory nerve action potentials and compound muscle action potentials. The evoked potential operant conditioning system platform was used to monitor responses in real time. Feasibility was also evaluated in a participant with incomplete spinal cord injury (iSCI).SEP P50 and N70 were reliably elicited in healthy participants, and in individual with iSCI, across all tested pulse widths with minimal discomfort. N70 amplitude increased significantly with pulse width (χ2= 17.64,= 0.0001,= 0.80), while P50 amplitude remained unchanged. SNR showed a significant pulse width-dependent increase (χ2= 7.82,= 0.02,= 0.35) with improvements of 40% and 52% at 0.5 and 1 ms, respectively. N70 single-trial separability significantly improved at 1 ms (AUC of 0.83,χ2= 8.17,= 0.017), including the iSCI participant (0.84-less impaired hand, 0.79-more impaired hand). Test-retest reliability (intraclass correlation coefficient = 0.70-0.84,< 0.05) was highest at 0.5 ms, indicating more consistent N70 and P50 measurements across sessions at a longer pulse width.Robust median nerve SEPs can be measured at single trials with methodological optimizations such as a longer pulse width (0.5-1 ms), low frequency (0.5 Hz), a consistent afferent excitation guided by nerve and muscle responses, and a robust EEG acquisition system. This setup can be useful for real time SEP-based brain computer interface applications for rehabilitation.</p>10aAdult10aComputer Systems10aElectric Stimulation10aElectroencephalography10aEvoked Potentials, Somatosensory10aFemale10aHumans10aMale10aMedian Nerve10aMiddle Aged10aReproducibility of Results10aSpinal Cord Injuries10aYoung Adult1 aGupta, Disha1 aBrangaccio, Jodi1 aHill, NJ  uhttps://www.neurotechcenter.org/publications/2026/methodological-optimization-eliciting-robust-median-nerve01698nas a2200265   4500008004100000022001400041245008600055210006900141260001200210300000900222490000900231520087600240653001501116653002801131653003301159653002701192653001301219653001101232653003501243653003101278653003201309100002601341700001701367856004801384       2009                        eng d  a1557-170X00aSeizure prediction for epilepsy using a multi-stage phase synchrony based system.0 aSeizure prediction for epilepsy using a multistage phase synchro  c09/2009  a25-80 v20093 aSeizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques. Here we present a multi-stage phase synchrony based system that brings to bear the advantages of many techniques in each substage. The 1(st) stage of the system unmixes continuous long-term (2-4 days) multichannel scalp EEG using spatially constrained Independent Component Analysis and estimates the long term significant phase synchrony dynamics of narrowband (2-8 Hz and 8-14 Hz) seizure components. It then projects multidimensional features onto a 2-D map using Neuroscale and evaluates the probability of predictive events using Gaussian Mixture Models. We show the possibility of seizure onset prediction within a prediction window of 35-65 minutes with a sensitivity of 65-100% and specificity of 65-80% across epileptic patients.10aAlgorithms10aArtificial Intelligence10aDiagnosis, Computer-Assisted10aElectroencephalography10aEpilepsy10aHumans10aPattern Recognition, Automated10aReproducibility of Results10aSensitivity and Specificity1 aJames, Christopher, J1 aGupta, Disha  uhttp://www.ncbi.nlm.nih.gov/pubmed/1996510402201nas a2200289   4500008004100000022001400041245012000055210006900175260000900244300001100253490001200264520126500276653001501541653002801556653003301584653002701617653001301644653001101657653003501668653003301703653003101736653003201767100002601799700002101825700001701846856004801863       2007                        eng d  a1557-170X00aSpace-time ICA versus Ensemble ICA for ictal EEG analysis with component differentiation via Lempel-Ziv complexity.0 aSpacetime ICA versus Ensemble ICA for ictal EEG analysis with co  c2007  a5473-60 v08/20073 aIn this proof-of-principle study we analyzed intracranial electroencephalogram recordings in patients with intractable focal epilepsy. We contrast two implementations of Independent Component Analysis (ICA) - Ensemble (or spatial) ICA (E-ICA) and Space-Time ICA (ST-ICA) in separating out the ictal components underlying the measurements. In each case we assess the outputs of the ICA algorithms by means of a non-linear method known as the Lempel-Ziv (LZ) complexity. LZ complexity quantifies the complexity of a time series and is well suited to the analysis of non-stationary biomedical signals of short length. Our results show that for small numbers of intracranial recordings, standard E-ICA results in marginal improvements in the separation as measured by the LZ complexity changes. ST-ICA using just 2 recording channels both near and far from the epileptic focus result in more distinct ictal components--although at this stage there is a subjective element to the separation process for ST-ICA. Our results are promising showing that it is possible to extract meaningful information from just 2 recording electrodes through ST-ICA, even if they are not directly over the seizure focus. This work is being further expanded for seizure onset analysis.10aAlgorithms10aArtificial Intelligence10aDiagnosis, Computer-Assisted10aElectroencephalography10aEpilepsy10aHumans10aPattern Recognition, Automated10aPrincipal Component Analysis10aReproducibility of Results10aSensitivity and Specificity1 aJames, Christopher, J1 aAbásolo, Daniel1 aGupta, Disha  uhttp://www.ncbi.nlm.nih.gov/pubmed/18003250