2019
DOI: 10.3390/s19235200
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AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning

Abstract: Information about a person’s engagement and attention might be a valuable asset in many settings including work situations, driving, and learning environments. To this end, we propose the first prototype of a device called AttentivU—a system that uses a wearable system which consists of two main components. Component 1 is represented by an EEG headband used to measure the engagement of a person in real-time. Component 2 is a scarf, which provides subtle, haptic feedback (vibrations) in real-time when the drop … Show more

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Cited by 45 publications
(48 citation statements)
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“…The HDEMG with 64 + electrodes may be convenient for automatic and real-time information processing in neural recording for brain computer interfaces [26], but presented a challenge for biofeedback. Therefore we shrank the information to only 4 regions for each muscle group and demonstrated the feasibility of the approach in a single person after stroke.…”
Section: Hdemg Biofeedback As a Rehabilitation Toolmentioning
confidence: 99%
“…The HDEMG with 64 + electrodes may be convenient for automatic and real-time information processing in neural recording for brain computer interfaces [26], but presented a challenge for biofeedback. Therefore we shrank the information to only 4 regions for each muscle group and demonstrated the feasibility of the approach in a single person after stroke.…”
Section: Hdemg Biofeedback As a Rehabilitation Toolmentioning
confidence: 99%
“…This index E is modeled from Pope et al [32], in which we input the averaged power of alpha, beta, and theta frequency components obtained from the Power Spectral Density (PSD) over 5-second sliding windows. We refer the reader to [22] for a full review of the engagement index, and its extensive usage with EEG bands of 1 to 6 channels. Next, we smooth E using an Exponentially Weighted Moving Average.…”
Section: Bci System Used During Stage 3 Heroa Conditionmentioning
confidence: 99%
“…Especially important for operational domains such as the military, principles of affective computing can be implemented in virtual reality (VR) systems for the purpose of training human performance outcomes (e.g., shooting marksmanship) [8], [9], [10], [11]. In addition to simulating real-world stressors, VR may enhance training because it can be integrated into closed-loop systems that adapt to the user [12], [13]. Such systems aim to customize stimuli (e.g., training aids) to changes in performance and psychological states (e.g., stress, workload) that are inferred from physiological responses [14], [15], [16], [17], [18], [19].…”
Section: Introductionmentioning
confidence: 99%