3,983 research outputs found

    A Wearable EEG System for Closed-Loop Neuromodulation of High-Frequency Sleep-Related Oscillations

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    In healthy sleepers, cortical alpha oscillations are present during the transition from wakefulness to sleep, and dissipate at sleep onset. For individuals with insomnia, alpha power is elevated during the wake-sleep transition and can persist throughout the night. Neuromodulation techniques using phase-locked stimulation have been put forth as alternatives to drugs for improving slow-wave sleep quality. Due to technical limitations, this approach has not been tested on faster frequency alpha oscillations. Here we examine the feasibility of using an endpoint-corrected version of the Hilbert Transform (ecHT) algorithm implemented on-device to measure alpha phase and deliver phase-locked auditory stimulation to modulate alpha and promote sleep initiation. First, the ecHT algorithm is implemented on a tabletop electroencephalogram (EEG) device and used to measure the timing of the auditory evoked response and its delivery at precise phases of the alpha oscillation. Secondly, a pilot at-home study tests feasibility to use a wearable version of the neuromodulation device for real-time phase-locked stimulation in the alpha (8-12 Hz) frequency range. Auditory stimulation was delivered at the intended phases of alpha with high precision, and alpha oscillations were affected differently by stimuli delivered at opposing phases. Our wearable system was capable of measuring sleep micro- and macro-events present in the EEG that were appropriate for clinical sleep scoring. Sleep onset latencies were reduced for a subset of subjects displaying sleep onset insomnia symptoms in the stimulation condition. This study demonstrates the feasibility of closed-loop tracking and neuromodulation of alpha oscillations using a wearable EEG device. Preliminary results suggest that this approach could be used to accelerate sleep initiation in individuals with objective insomnia symptoms.Comment: 31 pages, 10 main figures, 5 supplementary figure

    Design of Cognitive Interfaces for Personal Informatics Feedback

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    Identifying Electrophysiological Components of Covert Awareness in Patients with Disorders of Consciousness

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    Naturalistic stimuli evoke synchronous patterns of neural activity between individuals in sensory and higher cognitive, ā€œexecutiveā€ networks of the brain. fMRI paradigms developed to measure this inter-subject synchronization have been extended to test for executive processing in behaviourally non-responsive patients as a neural marker of awareness. This thesis adapted one such paradigm for use in EEG, a low-cost, portable neuroimaging technique that can be administered at a patientā€™s bedside. Healthy participants listened to a suspenseful auditory narrative during EEG recording. Significant inter-subject synchronization was found throughout the audio but was significantly reduced during a scrambled control condition. This paradigm was then used to evaluate executive processing in a cohort of patients. One locked-in patient and one patient in a vegetative state were significantly synchronized to healthy controls during the audio. EEG is a suitable tool to detect executive processing, a proxy measure of awareness, in patients who are behaviourally non-responsive

    Psychologie und Gehirn 2007

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    Die Fachtagung "Psychologie und Gehirn" ist eine traditionelle Tagung aus dem Bereich psychophysiologischer Grundlagenforschung. 2007 fand diese Veranstaltung, die 33. Jahrestagung der ā€žDeutschen Gesellschaft fĆ¼r Psychophysiologie und ihre Anwendungen (DGPA)ā€œ, in Dortmund unter der Schirmherrschaft des Instituts fĆ¼r Arbeitsphysiologie (IfADo) statt. Neben der Grundlagenforschung ist auch die Umsetzung in die Anwendung erklƤrtes Ziel der DGPA und dieser Tradition folgend wurden BeitrƤge aus vielen Bereichen moderner Neurowissenschaft (Elektrophysiologie, bildgebende Verfahren, Peripherphysiologie, Neuroendokrinologie, Verhaltensgenetik, u.a.) prƤsentiert und liegen hier in Kurzform vor

    A Large-Scale Study of a Sleep Tracking and Improving Device with Closed-loop and Personalized Real-time Acoustic Stimulation

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    Various intervention therapies ranging from pharmaceutical to hi-tech tailored solutions have been available to treat difficulty in falling asleep commonly caused by insomnia in modern life. However, current techniques largely remain ill-suited, ineffective, and unreliable due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, an ability to keep people asleep during the night, and a large-scale effectiveness evaluation. Here, we introduce a novel sleep aid system, called Earable, that can continuously sense multiple head-based physiological signals and simultaneously enable closed-loop auditory stimulation to entrain brain activities in time for effective sleep promotion. We develop the system in a lightweight, comfortable, and user-friendly headband with a comprehensive set of algorithms and dedicated own-designed audio stimuli. We conducted multiple protocols from 883 sleep studies on 377 subjects (241 women, 119 men) wearing either a gold-standard device (PSG), Earable, or both concurrently. We demonstrate that our system achieves (1) a strong correlation (0.89 +/- 0.03) between the physiological signals acquired by Earable and those from the gold-standard PSG, (2) an 87.8 +/- 5.3% agreement on sleep scoring using our automatic real-time sleep staging algorithm with the consensus scored by three sleep technicians, and (3) a successful non-pharmacological stimulation alternative to effectively shorten the duration of sleep falling by 24.1 +/- 0.1 minutes. These results show that the efficacy of Earable exceeds existing techniques in intentions to promote fast falling asleep, track sleep state accurately, and achieve high social acceptance for real-time closed-loop personalized neuromodulation-based home sleep care.Comment: 33 pages, 8 figure

    Effects of dance therapy on balance, gait and neuro-psychological performances in patients with Parkinson's disease and postural instability

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    Postural Instability (PI) is a core feature of Parkinsonā€™s Disease (PD) and a major cause of falls and disabilities. Impairment of executive functions has been called as an aggravating factor on motor performances. Dance therapy has been shown effective for improving gait and has been suggested as an alternative rehabilitative method. To evaluate gait performance, spatial-temporal (S-T) gait parameters and cognitive performances in a cohort of patients with PD and PI modifications in balance after a cycle of dance therapy

    Seizure Detection, Seizure Prediction, and Closed-Loop Warning Systems in Epilepsy

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    Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy
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