@article {4295, title = {BCI-based sensorimotor rhythm training can affect individuated finger movements }, journal = {Brain Computer Interface Society}, volume = {7}, year = {2020}, month = {06/2020}, chapter = {38}, abstract = {Brain-computer interface (BCI) technology can restore communication and control to people who are severely paralyzed. BCI technology might also be able to enhance rehabilitation of motor function. We have previously shown that pre-movement sensorimotor rhythm (SMR) amplitude affects reaction time and performance on a joystick-based cursor movement task. The present study explores in adults without motor impairment the possibility that pre-movement SMR amplitude affects performance of individuated finger movements. In Phase 1, 8 individuals performed a finger flexion task that was monitored by an exoskeleton. During a 1-sec preparatory period, two colored targets on a video monitor cued flexion of the index finger, middle finger, both fingers, or neither finger; sudden color change then triggered the movement (or non-movement). SMR features (i.e. EEG amplitudes in specific frequency bands at specific scalp locations) in the pre-movement EEG that correlated with movement versus no movement were identified. In Phase 2, the participants learned to increase or decrease these SMR features to control a two-target BCI task. Finally, in Phase 3, they were asked to increase or decrease the SMR features to initiate the finger flexion task of Phase 1 and the impact on finger flexion performance was assessed. After BCI training, pre-movement SMR feature amplitude affected performance in a subset of individuals: lower amplitude was associated with shorter movement onset. In a subset of individuals, the beneficial effect on performance of lower SMR amplitude was greater when both fingers were flexed than when one was flexed and the other remained extended; thus, the impact of SMR amplitude modulation depended on the specificity of the subsequent motor task. These results indicate that BCI-based training of SMR activity in the pre-movement preparatory period can affect finger movements in a subset of individuals. They encourage studies that integrate such training into rehabilitation protocols and examine its capacity to enhance restoration of useful hand function.}, keywords = {BCI, movement preparation, Rehabilitation, Robotics, sensorimotor beta rhythms}, doi = {10.1080/2326263X.2020.1763060}, url = {https://www.tandfonline.com/doi/abs/10.1080/2326263X.2020.1763060?journalCode=tbci20}, author = {D.J. McFarland and S.L. Norman and W.A. Sarnacki and E.T. Wolbrecht and D.J. Reinkensmeyer and J.R. Wolpaw} } @article {2132, title = {Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.}, journal = {J Neural Eng}, volume = {8}, year = {2011}, month = {06/2011}, pages = {036005}, abstract = {

The combination of\ brain-computer interfaces\ (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular\ brain\ damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a\ BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.

}, keywords = {Brain, Evoked Potentials, Motor, Evoked Potentials, Somatosensory, Feedback, Physiological, Female, Humans, Imagination, Male, Movement, Robotics, Touch, User-Computer Interface}, issn = {1741-2552}, doi = {10.1088/1741-2560/8/3/036005}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21474878}, author = {Gomez-Rodriguez, M and Peters, J and Jeremy Jeremy Hill and Sch{\"o}lkopf, B and Gharabaghi, A and Grosse-Wentrup, Moritz} } @article {2185, title = {Non-invasive brain-computer interface system: towards its application as assistive technology.}, journal = {Brain Res Bull}, volume = {75}, year = {2008}, month = {04/2008}, pages = {796-803}, abstract = {

The quality of life of people suffering from severe motor disabilities can benefit from the use of current assistive technology capable of ameliorating communication, house-environment management and mobility, according to the user{\textquoteright}s residual motor abilities.\ Brain-computer interfaces\ (BCIs) are systems that can translate\ brain\ activity into signals that control external devices. Thus they can represent the only technology for severely paralyzed patients to increase or maintain their communication and control options. Here we report on a pilot study in which a system was implemented and validated to allow disabled persons to improve or recover their mobility (directly or by emulation) and communication within the surrounding environment. The system is based on a software controller that offers to the user a communication interface that is matched with the individual{\textquoteright}s residual motor abilities. Patients (n=14) with severe motor disabilities due to progressive neurodegenerative disorders were trained to use the system prototype under a rehabilitation program carried out in a house-like furnished space. All users utilized regular assistive control options (e.g., microswitches or head trackers). In addition, four subjects learned to operate the system by means of a non-invasive EEG-based BCI. This system was controlled by the subjects{\textquoteright} voluntary modulations of EEG sensorimotor rhythms recorded on the scalp; this skill was learnt even though the subjects have not had control over their limbs for a long time. We conclude that such a prototype system, which integrates several different assistive technologies including a BCI system, can potentially facilitate the translation from pre-clinical\ demonstrations to a\ clinical\ useful BCI.

}, keywords = {Activities of Daily Living, Adolescent, Adult, Brain, Child, Electroencephalography, Evoked Potentials, Motor, Female, Humans, Learning, Male, Middle Aged, Motor Skills, Muscular Dystrophy, Duchenne, Pilot Projects, Prostheses and Implants, Robotics, Self-Help Devices, Software, Spinal Muscular Atrophies of Childhood, User-Computer Interface, Volition}, issn = {0361-9230}, doi = {10.1016/j.brainresbull.2008.01.007}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18394526}, author = {Cincotti, F and Mattia, Donatella and Aloise, Fabio and Bufalari, Simona and Gerwin Schalk and Oriolo, Giuseppe and Cherubini, Andrea and Marciani, Maria Grazia and Babiloni, Fabio} }