315 research outputs found

    Feasibility and Safety of Bilateral Hybrid EEG/EOG Brain/Neural–Machine Interaction

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    Cervical spinal cord injuries (SCIs) often lead to loss of motor function in both hands and legs, limiting autonomy and quality of life. While it was shown that unilateral hand function can be restored after SCI using a hybrid electroencephalography/electrooculography (EEG/EOG) brain/neural hand exoskeleton (B/NHE), it remained unclear whether such hybrid paradigm also could be used for operating two hand exoskeletons, e.g., in the context of bimanual tasks such as eating with fork and knife. To test whether EEG/EOG signals allow for fluent and reliable as well as safe and user-friendly bilateral B/NHE control, eight healthy participants (six females, mean age 24.1 +/- 3.2 years) as well as four chronic tetraplegics (four males, mean age 51.8 +/- 15.2 years) performed a complex sequence of EEG-controlled bilateral grasping and EOG-controlled releasing motions of two exoskeletons visually presented on a screen. A novel EOG command performed by prolonged horizontal eye movements (>1 s) to the left or right was introduced as a reliable switch to activate either the left or right exoskeleton. Fluent EEG control was defined as average "time to initialize" (TTI) grasping motions below 3 s. Reliable EEG control was assumed when classification accuracy exceeded 80%. Safety was defined as "time to stop" (TTS) all unintended grasping motions within 2 s. After the experiment, tetraplegics were asked to rate the user-friendliness of bilateral B/NHE control using Likert scales. Average TTI and accuracy of EEG-controlled operations ranged at 2.14 +/- 0.66 s and 85.89 +/- 15.81% across healthy participants and at 1.90 +/- 0.97 s and 81.25 +/- 16.99% across tetraplegics. Except for one tetraplegic, all participants met the safety requirements. With 88 +/- 11% of the maximum achievable score, tetraplegics rated the control paradigm as user-friendly and reliable. These results suggest that hybrid EEG/EOG B/NHE control of two assistive devices is feasible and safe, paving the way to test this paradigm in larger clinical trials performing bimanual tasks in everyday life environments

    Restoration of Gait using Personalized Brain/Neural-Controlled Exoskeletons

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    The development of brain/neural-controlled exoskeletons allow for restoration of movements in paralysis. By translating brain activity associated with the intention to move, such systems enabled, e.g., quadriplegic patients with complete finger paralysis to eat and drink in an outside restaurant. However, noninvasive means to record brain activity often lack sufficient signal quality for reliable and safe operation, particularly in noisy, uncontrolled environments or presence of muscle artifacts due to whole body movements. Thus, hybrid control paradigms were developed that merge different biosignals to increase reliability of exoskeleton control. Here, we introduce such control paradigm for restoration of gait using a personalized exoskeleton based on electroencephalographic and electrooculographic (EEG/EOG) signals. While exoskeleton movements were initiated by event-related desynchronization (ERD) of sensorimotor rhythms (SMR) associated with the intention to walk, the exoskeleton was stopped by a specific EOG signal. Using such paradigm does not only provide intuitive control, but may also trigger neural recovery when used repeatedly over a longer period of time. Further validation of this approach in a larger clinical study on gait assistance and rehabilitation will be needed

    Identification and Energy Measurements of Light Particles with a CsI(Tl)-Photodiode Combination

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    This research was sponsored by the National Science Foundation Grant NSF PHY-931478

    An Attempt to Study T=2 States in 16-N

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    This research was sponsored by the National Science Foundation Grant NSF PHY 87-1440

    Synchronization of Slow Cortical Rhythms During Motor Imagery-Based Brain–Machine Interface Control

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    Modulation of sensorimotor rhythm (SMR) power, a rhythmic brain oscillation physiologically linked to motor imagery, is a popular Brain–Machine Interface (BMI) paradigm, but its interplay with slower cortical rhythms, also involved in movement preparation and cognitive processing, is not entirely understood. In this study, we evaluated the changes in phase and power of slow cortical activity in delta and theta bands, during a motor imagery task controlled by an SMR-based BMI system. In Experiment I, EEG of 20 right-handed healthy volunteers was recorded performing a motor-imagery task using an SMR-based BMI controlling a visual animation, and during task-free intervals. In Experiment II, 10 subjects were evaluated along five daily sessions, while BMI-controlling same visual animation, a buzzer, and a robotic hand exoskeleton. In both experiments, feedback received from the controlled device was proportional to SMR power (11–14 Hz) detected by a real-time EEG-based system. Synchronization of slow EEG frequencies along the trials was evaluated using inter-trial-phase coherence (ITPC). Results: cortical oscillations of EEG in delta and theta frequencies synchronized at the onset and at the end of both active and task-free trials; ITPC was significantly modulated by feedback sensory modality received during the tasks; and ITPC synchronization progressively increased along the training. These findings suggest that phase-locking of slow rhythms and resetting by sensory afferences might be a functionally relevant mechanism in cortical control of motor function. We propose that analysis of phase synchronization of slow cortical rhythms might also improve identification of temporal edges in BMI tasks and might help to develop physiological markers for identification of context task switching and practice-related changes in brain function, with potentially important implications for design and monitoring of motor imagery-based BMI systems, an emerging tool in neurorehabilitation of stro

    Spectroscopy with the (d,n) Reaction at 80 MeV

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    This work was supported by the National Science Foundation Grant NSF PHY 81-14339 and by Indiana Universit
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