03078nas a2200313   4500008004100000022001400041245013800055210006900193260001600262490000700278520206400285653001002349653002102359653002502380653002702405653003702432653001102469653001102480653000902491653001702500653001602517653003102533653002502564653001602589100001702605700002102622700001302643856010802656       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://neurotechcenter.org/publications/2026/methodological-optimization-eliciting-robust-median-nerve02165nas a2200301   4500008004100000022001400041245015400055210006900209260001300278300000800291490000900299520119500308653000901503653002101512653001101533653001101544653000901555653001601564653001301580653001101593653002601604100002701630700001901657700002301676700002801699700001701727856011901744       2024                        eng d  a2694-060400aMultidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.0 aMultidimensional feature analysis shows stratification in roboti  c2024 Jul  a1-50 v20243 a<p>Stroke involves heterogeneity in injury and ongoing endogenous recovery, which are seldom stratified before testing post-stroke robot assisted motor training (RAMT). Pretraining variations, especially sensory-motor differences may also affect the gains achieved from the RAMT. Moreover, one assessment test may not effectively characterize the baseline sensory-motor status or the RAMT gains. Pre-therapy stratification may help personalize therapy and increase therapy gains. Towards this goal, we propose a data-driven approach to assess multiple functional scores with t-distributed stochastic neighbor embedding and affinity propagation clustering, both for pre-therapy and RAMT gains. Data included behavioral scores from 27 people with chronic stroke who underwent RAMT for finger movement. Three clusters were observed at start-of-therapy (SoT), concurrent with the overall impairment level. Four clusters were observed for the RAMT gains, indicating specific improvements. The SoT clusters showed agreement with the RAMT gain clusters, suggesting that the pre-therapy state, assessed across multiple domains, could be useful in guiding RAMT interventions to improve outcomes.</p>10aAged10aCluster Analysis10aFemale10aHumans10aMale10aMiddle Aged10aRobotics10aStroke10aStroke Rehabilitation1 aRueda-Parra, Sebastian1 aPerry, Joel, C1 aWolbrecht, Eric, T1 aReinkensmeyer, David, J1 aGupta, Disha  uhttps://neurotechcenter.org/publications/2024/multidimensional-feature-analysis-shows-stratification-robotic-motor03126nas a2200313   4500008004100000022001400041245013900055210006900194260001500263520206900278653002002347653002602367653002102393653002202414653001302436653001102449653002702460653002502487100001702512700001702529700001902546700002402565700002302589700002102612700001402633700002402647700002202671856011902693       2022                        eng d  a1940-087X00aThe Evoked Potential Operant Conditioning System (EPOCS): A Research Tool and an Emerging Therapy for Chronic Neuromuscular Disorders.0 aEvoked Potential Operant Conditioning System EPOCS A Research To  c2022 08 253 a<p>The Evoked Potential Operant Conditioning System (EPOCS) is a software tool that implements protocols for operantly conditioning stimulus-triggered muscle responses in people with neuromuscular disorders, which in turn can improve sensorimotor function when applied appropriately. EPOCS monitors the state of specific target muscles-e.g., from surface electromyography (EMG) while standing, or from gait cycle measurements while walking on a treadmill-and automatically triggers calibrated stimulation when pre-defined conditions are met. It provides two forms of feedback that enable a person to learn to modulate the targeted pathway's excitability. First, it continuously monitors ongoing EMG activity in the target muscle, guiding the person to produce a consistent level of activity suitable for conditioning. Second, it provides immediate feedback of the response size following each stimulation and indicates whether it has reached the target value. To illustrate its use, this article describes a protocol through which a person can learn to decrease the size of the Hoffmann reflex-the electrically-elicited analog of the spinal stretch reflex-in the soleus muscle. Down-conditioning this pathway's excitability can improve walking in people with spastic gait due to incomplete spinal cord injury. The article demonstrates how to set up the equipment; how to place stimulating and recording electrodes; and how to use the free software to optimize electrode placement, measure the recruitment curve of direct motor and reflex responses, measure the response without operant conditioning, condition the reflex, and analyze the resulting data. It illustrates how the reflex changes over multiple sessions and how walking improves. It also discusses how the system can be applied to other kinds of evoked responses and to other kinds of stimulation, e.g., motor evoked potentials to transcranial magnetic stimulation; how it can address various clinical problems; and how it can support research studies of sensorimotor function in health and disease.</p>10aChronic Disease10aConditioning, Operant10aElectromyography10aEvoked Potentials10aH-Reflex10aHumans10aNeuromuscular Diseases10aSpinal Cord Injuries1 aHill, Jeremy1 aGupta, Disha1 aEftekhar, Amir1 aBrangaccio, Jodi, A1 aNorton, James, J S1 aMcLeod, Michelle1 aFake, Tim1 aWolpaw, Jonathan, R1 aThompson, Aiko, K  uhttps://neurotechcenter.org/publications/2022/evoked-potential-operant-conditioning-system-epocs-research-tool-and01698nas 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/1996510401751nas a2200229   4500008004100000022001400041245012300055210006900178260001200247300001100259490000900270520101400279653001501293653002701308653001101335653003001346653001301376653004101389100001701430700002601447856004801473       2007                        eng d  a1557-170X00aNarrowband vs. broadband phase synchronization analysis applied to independent components of ictal and interictal EEG.0 aNarrowband vs broadband phase synchronization analysis applied t  c08/2007  a3864-70 v20073 aThis paper presents a comparison of the use of broadband and narrow band signals for phase synchronization analysis as applied to Independent Components of ictal and interictal scalp EEG in the context of seizure onset detection and prediction. Narrow band analysis for phase synchronization is found to be better performed in the present context than the broad band signal analysis. It has been observed that the phase synchronization of Independent Components in a narrow band (particularly the Gamma band) shows a prominent trend of increasing and decreasing synchronization at seizure onset near the epileptogenic area (spatially). This information is not always found to be consistent in analysis with the raw EEG signals, which may show spurious synchronization happening due to volume conduction effects. These observations lead us to believe that tracking changes in phase synchronization of narrow band activity, on continuous data records will be of great value in the context of seizure prediction.10aAlgorithms10aElectroencephalography10aHumans10aPredictive Value of Tests10aSeizures10aSignal Processing, Computer-Assisted1 aGupta, Disha1 aJames, Christopher, J  uhttp://www.ncbi.nlm.nih.gov/pubmed/1800284202201nas 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