@article {4609,
	title = {Methodological optimization for eliciting robust median nerve somatosensory evoked potentials for realtime single trial applications.},
	journal = {J Neural Eng},
	volume = {23},
	year = {2026},
	month = {2026 Jan 09},
	abstract = {<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 {\textpm} 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>},
	keywords = {Adult, Computer Systems, Electric Stimulation, Electroencephalography, Evoked Potentials, Somatosensory, Female, Humans, Male, Median Nerve, Middle Aged, Reproducibility of Results, Spinal Cord Injuries, Young Adult},
	issn = {1741-2552},
	doi = {10.1088/1741-2552/ae30ac},
	author = {Gupta, Disha and Brangaccio, Jodi and Hill, NJ}
}
@article {2845,
	title = {Seizure prediction for epilepsy using a multi-stage phase synchrony based system.},
	journal = {Conf Proc IEEE Eng Med Biol Soc},
	volume = {2009},
	year = {2009},
	month = {09/2009},
	pages = {25-8},
	abstract = {Seizure 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.},
	keywords = {Algorithms, Artificial Intelligence, Diagnosis, Computer-Assisted, Electroencephalography, Epilepsy, Humans, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity},
	issn = {1557-170X},
	doi = {10.1109/IEMBS.2009.5334898},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/19965104},
	author = {Christopher J James and Disha Gupta}
}
@article {2846,
	title = {Space-time ICA versus Ensemble ICA for ictal EEG analysis with component differentiation via Lempel-Ziv complexity.},
	journal = {Conf Proc IEEE Eng Med Biol Soc},
	volume = {08/2007},
	year = {2007},
	month = {2007},
	pages = {5473-6},
	abstract = {In 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.},
	keywords = {Algorithms, Artificial Intelligence, Diagnosis, Computer-Assisted, Electroencephalography, Epilepsy, Humans, Pattern Recognition, Automated, Principal Component Analysis, Reproducibility of Results, Sensitivity and Specificity},
	issn = {1557-170X},
	doi = {10.1109/IEMBS.2007.4353584},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/18003250},
	author = {Christopher J James and Ab{\'a}solo, Daniel and Disha Gupta}
}
