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1.
Adv Sci (Weinh) ; 8(19): e2101129, 2021 10.
Article in English | MEDLINE | ID: mdl-34272934

ABSTRACT

Motor imagery offers an excellent opportunity as a stimulus-free paradigm for brain-machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, a wireless scalp electronic system with virtual reality for real-time, continuous classification of motor imagery brain signals is introduced. This low-profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network-machine learning provides a real-time, continuous motor imagery-based brain-machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22 ± 1.33% for four classes), allowing wireless, real-time control of a virtual reality game.


Subject(s)
Brain-Computer Interfaces , Brain/physiology , Electroencephalography/instrumentation , Electroencephalography/methods , User-Computer Interface , Virtual Reality , Electrodes , Humans , Scalp
2.
JMIR Ment Health ; 6(2): e11517, 2019 Feb 21.
Article in English | MEDLINE | ID: mdl-30789353

ABSTRACT

BACKGROUND: Cognitive Bias Modification of Interpretations (CBM-I) is a computerized intervention designed to change negatively biased interpretations of ambiguous information, which underlie and reinforce anxiety. The repetitive and monotonous features of CBM-I can negatively impact training adherence and learning processes. OBJECTIVE: This proof-of-concept study aimed to examine whether performing a CBM-I training using mobile virtual reality technology (virtual reality Cognitive Bias Modification of Interpretations [VR-CBM-I]) improves training experience and effectiveness. METHODS: A total of 42 students high in trait anxiety completed 1 session of either VR-CBM-I or standard CBM-I training for performance anxiety. Participants' feelings of immersion and presence, emotional reactivity to a stressor, and changes in interpretation bias and state anxiety, were assessed. RESULTS: The VR-CBM-I resulted in greater feelings of presence (P<.001, d=1.47) and immersion (P<.001, ηp2=0.74) in the training scenarios and outperformed the standard training in effects on state anxiety (P<.001, ηp2=0.3) and emotional reactivity to a stressor (P=.03, ηp2=0.12). Both training varieties successfully increased the endorsement of positive interpretations (P<.001, drepeated measures [drm]=0.79) and decreased negative ones. (P<.001, drm=0.72). In addition, changes in the emotional outcomes were correlated with greater feelings of immersion and presence. CONCLUSIONS: This study provided first evidence that (1) the putative working principles underlying CBM-I trainings can be translated into a virtual environment and (2) virtual reality holds promise as a tool to boost the effects of CMB-I training for highly anxious individuals while increasing users' experience with the training application.

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