Justin Asbee
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Postdoctoral Fellow
Also affiliated: University of North Texas (2019–2023); Victor (Japan) (2022); Innovative Research (United States) (2023–2026); Arizona State University (2022)
Postdoc Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Justin Asbee's research investigates the intersection of virtual reality, cognitive function, and physiological responses. His work has explored the use of virtual reality environments to assess cognitive load and reaction time, as demonstrated in studies on an adaptive virtual reality Stroop task and a virtual city environment. Asbee has also examined the application of neurofeedback techniques, specifically frontal theta neurofeedback, to study neural and behavioral adaptations. His research has included systematic reviews on transcranial direct current stimulation's effects on cognitive and affective outcomes using virtual stimuli. Additionally, Asbee has investigated the relationship between video game usage, substance use, and sleep patterns among college students, employing both frequentist and Bayesian statistical approaches. His recent work has also focused on the feasibility of using machine learning to predict outcomes within virtual environments, such as a virtual grocery store.
Metrics
- h-index: 5
- Publications: 14
- Citations: 204
Selected Publications
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Monitoring Eye Movements to Assess the impact of Sensory Feedback on Cognitive Workload During Myoelectric Prosthetic Hand Use (2026)Journal of the Arkansas Academy of Science OpenAlex
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Single-site non-invasive peripheral nerve stimulation with multidimensional encoding enables object differentiation using a myoelectric prosthetic hand (2026)
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Selective Activation of Nerve Fiber Subpopulations with Intrafascicular Stimulation (2026)
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Single-site non-invasive peripheral nerve stimulation with multidimensional encoding enables object differentiation using a myoelectric prosthetic hand (2025)
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Feasibility study to identify machine learning predictors for a Virtual Environment Grocery Store (2024)
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Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study (2023)
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Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students (2023)
Collaboration Network
Top Collaborators
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Feasibility study to identify machine learning predictors for a Virtual Environment Grocery Store
- Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students
- Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students
- Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Neural and behavioral adaptations to frontal theta neurofeedback training: A proof of concept study
- Feasibility study to identify machine learning predictors for a Virtual Environment Grocery Store
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