<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rustamov, Nabi</style></author><author><style face="normal" font="default" size="100%">Souders, Lauren</style></author><author><style face="normal" font="default" size="100%">Sheehan, Lauren</style></author><author><style face="normal" font="default" size="100%">Carter, Alexandre</style></author><author><style face="normal" font="default" size="100%">Leuthardt, Eric C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">IpsiHand Brain-Computer Interface Therapy Induces Broad Upper Extremity Motor Rehabilitation in Chronic Stroke.</style></title><secondary-title><style face="normal" font="default" size="100%">Neurorehabil Neural Repair</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Neurorehabil Neural Repair</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">brain-computer interfaces</style></keyword><keyword><style  face="normal" font="default" size="100%">Chronic Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gamma Rhythm</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Activity</style></keyword><keyword><style  face="normal" font="default" size="100%">Paresis</style></keyword><keyword><style  face="normal" font="default" size="100%">Prospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Recovery of Function</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke Rehabilitation</style></keyword><keyword><style  face="normal" font="default" size="100%">Theta Rhythm</style></keyword><keyword><style  face="normal" font="default" size="100%">Upper Extremity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2025 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">74-86</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Chronic hemiparetic stroke patients have very limited benefits from current therapies. Brain-computer interface (BCI) engaging the unaffected hemisphere has emerged as a promising novel therapeutic approach for chronic stroke rehabilitation.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;This study investigated the effectiveness of contralesionally-controlled BCI therapy in chronic stroke patients with impaired upper extremity motor function. We further explored neurophysiological features of motor recovery driven by BCI. We hypothesized that BCI therapy would induce a broad motor recovery in the upper extremity, and there would be corresponding changes in baseline theta and gamma oscillations, which have been shown to be associated with motor recovery.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Twenty-six prospectively enrolled chronic hemiparetic stroke patients performed a therapeutic BCI task for 12 weeks. Motor function assessment data and resting state electroencephalogram signals were acquired before initiating BCI therapy and across BCI therapy sessions. The Upper Extremity Fugl-Meyer assessment served as a primary motor outcome assessment tool. Theta-gamma cross-frequency coupling (CFC) was computed and correlated with motor recovery.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Chronic stroke patients achieved significant motor improvement in both proximal and distal upper extremity with BCI therapy. Motor function improvement was independent of Botox application. Theta-gamma CFC enhanced bilaterally over the C3/C4 motor electrodes and positively correlated with motor recovery across BCI therapy sessions.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;BCI therapy resulted in significant motor function improvement across the proximal and distal upper extremities of patients, which significantly correlated with theta-gamma CFC increases in the motor regions. This may represent rhythm-specific cortical oscillatory mechanism for BCI-driven rehabilitation in chronic stroke patients.&lt;/p&gt;&lt;p&gt;&lt;b&gt;TRIAL REGISTRATION: &lt;/b&gt;Advarra Study: https://classic.clinicaltrials.gov/ct2/show/NCT04338971 and Washington University Study: https://classic.clinicaltrials.gov/ct2/show/NCT03611855.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rueda-Parra, Sebastian</style></author><author><style face="normal" font="default" size="100%">Perry, Joel C</style></author><author><style face="normal" font="default" size="100%">Wolbrecht, Eric T</style></author><author><style face="normal" font="default" size="100%">Reinkensmeyer, David J</style></author><author><style face="normal" font="default" size="100%">Gupta, Disha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.</style></title><secondary-title><style face="normal" font="default" size="100%">Annu Int Conf IEEE Eng Med Biol Soc</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Annu Int Conf IEEE Eng Med Biol Soc</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Cluster Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Robotics</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke Rehabilitation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2024</style></volume><pages><style face="normal" font="default" size="100%">1-5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Norman, SL</style></author><author><style face="normal" font="default" size="100%">McFarland, DJ</style></author><author><style face="normal" font="default" size="100%">Miner, A</style></author><author><style face="normal" font="default" size="100%">Cramer, SC</style></author><author><style face="normal" font="default" size="100%">Wolbrecht, ET</style></author><author><style face="normal" font="default" size="100%">Jonathan Wolpaw</style></author><author><style face="normal" font="default" size="100%">Reinkensmeyer, DJ</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Controlling pre-movement sensorimotor rhythm can improve finger extension after stroke</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Neural Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">BCI</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor control</style></keyword><keyword><style  face="normal" font="default" size="100%">Rehabilitation</style></keyword><keyword><style  face="normal" font="default" size="100%">robot</style></keyword><keyword><style  face="normal" font="default" size="100%">sensorimotor rhythm</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://stacks.iop.org/1741-2552/15/i=5/a=056026</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">15</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Objective. Brain–computer interface (BCI) technology is attracting increasing interest as a tool for enhancing recovery of motor function after stroke, yet the optimal way to apply this technology is unknown. Here, we studied the immediate and therapeutic effects of BCI-based training to control pre-movement sensorimotor rhythm (SMR) amplitude on robot-assisted finger extension in people with stroke. Approach. Eight people with moderate to severe hand impairment due to chronic stroke completed a four-week three-phase protocol during which they practiced finger extension with assistance from the FINGER robotic exoskeleton. In Phase 1, we identified spatiospectral SMR features for each person that correlated with the intent to extend the index and/or middle finger(s). In Phase 2, the participants learned to increase or decrease SMR features given visual feedback, without movement. In Phase 3, the participants were cued to increase or decrease their SMR features, and when successful, were then cued to immediately attempt to extend the finger(s) with robot assistance. Main results. Of the four participants that achieved SMR control in Phase 2, three initiated finger extensions with a reduced reaction time after decreasing (versus increasing) pre-movement SMR amplitude during Phase 3. Two also extended at least one of their fingers more forcefully after decreasing pre-movement SMR amplitude. Hand function, measured by the box and block test (BBT), improved by 7.3  ±  7.5 blocks versus 3.5  ±  3.1 blocks in those with and without SMR control, respectively. Higher BBT scores at baseline correlated with a larger change in BBT score. Significance. These results suggest that learning to control person-specific pre-movement SMR features associated with finger extension can improve finger extension ability after stroke for some individuals. These results merit further investigation in a rehabilitation context.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wisneski, Kimberly</style></author><author><style face="normal" font="default" size="100%">Nicholas R Anderson</style></author><author><style face="normal" font="default" size="100%">Gerwin Schalk</style></author><author><style face="normal" font="default" size="100%">Smyth, Matt</style></author><author><style face="normal" font="default" size="100%">Moran, D</style></author><author><style face="normal" font="default" size="100%">Leuthardt, E C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unique cortical physiology associated with ipsilateral hand movements and neuroprosthetic implications.</style></title><secondary-title><style face="normal" font="default" size="100%">Stroke</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Stroke</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Artificial Limbs</style></keyword><keyword><style  face="normal" font="default" size="100%">Bionics</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Dominance, Cerebral</style></keyword><keyword><style  face="normal" font="default" size="100%">Electroencephalography</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Hand</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Movement</style></keyword><keyword><style  face="normal" font="default" size="100%">Paresis</style></keyword><keyword><style  face="normal" font="default" size="100%">Prosthesis Design</style></keyword><keyword><style  face="normal" font="default" size="100%">Psychomotor Performance</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke</style></keyword><keyword><style  face="normal" font="default" size="100%">User-Computer Interface</style></keyword><keyword><style  face="normal" font="default" size="100%">Volition</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2008</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/18927456</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">3351-9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;BACKGROUND AND PURPOSE:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;&lt;span class=&quot;highlight&quot;&gt;Brain computer interfaces&lt;/span&gt;&amp;nbsp;(BCIs) offer little direct benefit to patients with hemispheric stroke because current platforms rely on signals derived from the contralateral motor cortex (the same region injured by the stroke). For BCIs to assist hemiparetic patients, the implant must use unaffected cortex ipsilateral to the affected limb. This requires the identification of distinct electrophysiological features from the motor cortex associated with ipsilateral hand movements.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;METHODS:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;In this study we studied 6 patients undergoing temporary placement of intracranial electrode arrays. Electrocorticographic (ECoG) signals were recorded while the subjects engaged in specific ipsilateral or contralateral hand motor tasks. Spectral changes were identified with regards to frequency, location, and timing.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;RESULTS:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Ipsilateral hand movements were associated with electrophysiological changes that occur in lower frequency spectra, at distinct anatomic locations, and earlier than changes associated with contralateral hand movements. In a subset of 3 patients, features specific to ipsilateral and contralateral hand movements were used to control a cursor on a screen in real time. In ipsilateral derived control this was optimal with lower frequency spectra.&lt;/p&gt;
&lt;h4 style=&quot;font-size: 13px; margin: 0px 0.25em 0px 0px; text-transform: uppercase; float: left; font-family: arial, helvetica, clean, sans-serif; line-height: 17px;&quot;&gt;CONCLUSIONS:&amp;nbsp;&lt;/h4&gt;
&lt;p style=&quot;margin: 0px 0px 0.5em; font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;There are distinctive cortical electrophysiological features associated with ipsilateral movements which can be used for device control. These findings have implications for patients with hemispheric stroke because they offer a potential methodology for which a single hemisphere can be used to enhance the function of a stroke induced hemiparesis.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brendan Z. Allison</style></author><author><style face="normal" font="default" size="100%">Wolpaw, Elizabeth Winter</style></author><author><style face="normal" font="default" size="100%">Jonathan Wolpaw</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Brain-computer interface systems: progress and prospects.</style></title><secondary-title><style face="normal" font="default" size="100%">Expert review of medical devices</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ALS</style></keyword><keyword><style  face="normal" font="default" size="100%">assistive communication</style></keyword><keyword><style  face="normal" font="default" size="100%">BCI</style></keyword><keyword><style  face="normal" font="default" size="100%">BMI</style></keyword><keyword><style  face="normal" font="default" size="100%">brain-acuated control</style></keyword><keyword><style  face="normal" font="default" size="100%">brain-computer interface</style></keyword><keyword><style  face="normal" font="default" size="100%">brain-machine interface</style></keyword><keyword><style  face="normal" font="default" size="100%">EEG</style></keyword><keyword><style  face="normal" font="default" size="100%">ERP</style></keyword><keyword><style  face="normal" font="default" size="100%">locked-in syndrome</style></keyword><keyword><style  face="normal" font="default" size="100%">slow cortical potential</style></keyword><keyword><style  face="normal" font="default" size="100%">SSVEP</style></keyword><keyword><style  face="normal" font="default" size="100%">Stroke</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2007</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/17605682</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">463–474</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Brain-computer interface (BCI) systems support communication through direct measures of neural activity without muscle activity. BCIs may provide the best and sometimes the only communication option for users disabled by the most severe neuromuscular disorders and may eventually become useful to less severely disabled and/or healthy individuals across a wide range of applications. This review discusses the structure and functions of BCI systems, clarifies terminology and addresses practical applications. Progress and opportunities in the field are also identified and explicated.</style></abstract></record></records></xml>