@article{demarest2023novel,

title = {A Novel Theta-Controlled Vibrotactile Brain-Computer Interface To Treat Chronic Pain: A Pilot Study},

author = {Phillip Demarest and Nabi Rustamov and James Swift and Tao Xie and Markus Adamek and Hohyun Cho and Elizabeth Wilson and Zhuangyu Han and Alexander Belsten and Nicholas Luczak and others},

doi = {https://doi.org/10.21203/rs.3.rs-2973437/v1},

year  = {2023},

date = {2023-06-01},

urldate = {2023-01-01},

abstract = {Limitations in chronic pain therapies necessitate novel interventions that are effective, accessible, and safe. Brain-computer interfaces (BCIs) provide a promising modality for targeting neuropathology underlying chronic pain by converting recorded neural activity into perceivable outputs. Recent evidence suggests that increased frontal theta power (4–7 Hz) reflects pain relief from chronic and acute pain. Further studies have suggested that vibrotactile stimulation decreases pain intensity in experimental and clinical models. This longitudinal, non-randomized, open-label pilot study's objective was to reinforce frontal theta activity in six patients with chronic upper extremity pain using a novel vibrotactile neurofeedback BCI system. Patients increased their BCI performance, reflecting thought-driven control of neurofeedback, and showed a significant decrease in pain severity and pain interference scores without any adverse events. Pain relief significantly correlated with frontal theta modulation. These findings highlight the potential of BCI-mediated cortico-sensory coupling of frontal theta with vibrotactile stimulation for alleviating chronic pain.



},

keywords = {BCI, DSI-24, Neurofeedback},

pubstate = {published},

tppubtype = {article}

}

@article{mclaughlin2021methodology,

title = {Methodology and feasibility of neurofeedback to improve visual attention to letters in mild Alzheimer's disease},

author = {Deirdre McLaughlin and Daniel Klee and Tab Memmott and Betts Peters and Jack Wiedrick and Melanie Fried-Oken and Barry Oken},

url = {https://arxiv.org/abs/2111.12153},

year  = {2021},

date = {2021-11-23},

journal = {Human-Computer Interaction},

abstract = {Brain computer interfaces systems are controlled by users through neurophysiological input for a variety of applications including communication, environmental control, motor rehabilitation, and cognitive training. Although individuals with severe speech and physical impairment are the primary users of this technology, BCIs have emerged as a potential tool for broader populations, especially with regards to delivering cognitive training or interventions with neurofeedback. The goal of this study was to investigate the feasibility of using a BCI system with neurofeedback as an intervention for people with mild Alzheimer's disease. The study focused on visual attention and language since ad is often associated with functional impairments in language and reading. The study enrolled five adults with mild ad in a nine to thirteen week BCI EEG based neurofeedback intervention to improve attention and reading skills. Two participants completed intervention entirely. The remaining three participants could not complete the intervention phase because of restrictions related to covid. Pre and post assessment measures were used to assess reliability of outcome measures and generalization of treatment to functional reading, processing speed, attention, and working memory skills. Participants demonstrated steady improvement in most cognitive measures across experimental phases, although there was not a significant effect of NFB on most measures of attention. One subject demonstrated significantly significant improvement in letter cancellation during NFB. All participants with mild AD learned to operate a BCI system with training. Results have broad implications for the design and use of bci systems for participants with cognitive impairment. Preliminary evidence justifies implementing NFB-based cognitive measures in AD.},

keywords = {DSI-VR300, Neurofeedback},

pubstate = {published},

tppubtype = {article}

}

@article{jung2021effect,

title = {The Effect of a Mindfulness-Based Education Program on Brain Waves and the Autonomic Nervous System in University Students},

author = {Mijung Jung and Mikyoung Lee},

doi = {https://doi.org/10.3390/healthcare9111606},

year  = {2021},

date = {2021-11-22},

booktitle = {Healthcare},

journal = {Healthcare 2021},

volume = {9},

number = {11},

pages = {1606},

organization = {Multidisciplinary Digital Publishing Institute},

abstract = {Background: Mindfulness, defined as the awareness emerging from purposefully paying attention to the present moment, has been shown to be effective in reducing stress and, thus, promoting psychological well-being. This study investigated the effects of a mindfulness-based education program on mindfulness, brain waves, and the autonomic nervous system (ANS) in university students in Korea. Methods: This study is a quantitative and experimental research with a single-group pre-post design. Six sessions of mindfulness-based intervention were applied. In total, 42 students completed a mindfulness questionnaire before and after the intervention, and 28 among them completed pre-intervention and post-intervention measures of brain waves and ANS. Results: The level of mindfulness increased in the participants after intervention. Regarding brain waves, the alpha and theta waves increased, but the beta waves decreased. There was no significant difference in the ANS, presenting no change in heart rate variability. Conclusions: We identified the positive effects of the mindfulness-based education program for university students. The findings indicate that this program may help students not only relax, but also generate a mindfulness state in stressful situations, potentially leading to a successful university life. This study can be used as a basis for quality improvement and sustainability of mindfulness-based education programs for university students.},

keywords = {DSI-24, Neurofeedback},

pubstate = {published},

tppubtype = {article}

}