Design of a Neurofeedback Training System for Meditation Based on EEG Technology

Vallejo, Andrés Eduardo Nieto; Ramírez-Pérez, Omar Fernando; Ballesteros-Arroyave, Luis Eduardo; Aragón, Angela

doi:10.19053/01211129.v30.n55.2021.12489

Cited by 2 publications

(2 citation statements)

References 30 publications

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“…This is especially important in assistive applications, where the user must have confidence in the system. Tactile feedback can be particularly useful for users with visual or auditory limitations [63]. Additionally, the feedback system can include adaptive learning elements, where the user receives feedback on how to improve the effectiveness of their commands, increasing the efficiency and satisfaction of the user with the system over time.…”

Section: • User Feedback Systemmentioning

confidence: 99%

Architectural Proposal for Low-Cost Brain–Computer Interfaces with ROS Systems for the Control of Robotic Arms in Autonomous Wheelchairs

Rivas,

Sierra,

Cámara

2024

Electronics

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Neurodegenerative diseases present significant challenges in terms of mobility and autonomy for patients. In the current context of technological advances, brain–computer interfaces (BCIs) emerge as a promising tool to improve the quality of life of these patients. Therefore, in this study, we explore the feasibility of using low-cost commercial EEG headsets, such as Neurosky and Brainlink, for the control of robotic arms integrated into autonomous wheelchairs. These headbands, which offer attention and meditation values, have been adapted to provide intuitive control based on the eight EEG signal values read from Delta to Gamma (high and low/medium Gamma) collected from the users’ prefrontal area, using only two non-invasive electrodes. To ensure precise and adaptive control, we have incorporated a neural network that interprets these values in real time so that the response of the robotic arm matches the user’s intentions. The results suggest that this combination of BCIs, robotics, and machine learning techniques, such as neural networks, is not only technically feasible but also has the potential to radically transform the interaction of patients with neurodegenerative diseases with their environment.

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Section: • User Feedback Systemmentioning

confidence: 99%

Architectural Proposal for Low-Cost Brain–Computer Interfaces with ROS Systems for the Control of Robotic Arms in Autonomous Wheelchairs

Rivas,

Sierra,

Cámara

2024

Electronics

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show abstract

“… 16 Neurofeedback, one of the techniques for training brain self-regulation, has the potential to increase the effectiveness of meditation. 17 …”

Section: Introductionmentioning

confidence: 99%

Modest Effects of Neurofeedback-Assisted Meditation Using a Wearable Device on Stress Reduction: A Randomized, Double-Blind, and Controlled Study

Lee,

Hong,

Choi

et al. 2024

J Korean Med Sci

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Background To evaluate the therapeutic effectiveness and safety of a neurofeedback wearable device for stress reduction. Methods A randomized, double-blind, controlled study was designed. Participants had psychological stress with depression or sleep disturbances. They practiced either neurofeedback-assisted meditation (n = 20; female, 15 [75.0%]; age, 49.40 ± 11.76 years) or neurofeedback non-assisted meditation (n = 18; female, 11 [61.1%]; age, 48.67 ± 12.90 years) for 12 minutes twice a day for two weeks. Outcome variables were self-reported questionnaires, including the Korean version of the Perceived Stress Scale, Beck Depression Inventory-II, Insomnia Severity Index, Pittsburgh Sleep Quality Index, and State Trait Anxiety Index, quantitative electroencephalography (qEEG), and blood tests. Satisfaction with device use was measured at the final visit. Results The experimental group had a significant change in PSS score after two weeks of intervention compared with the control group (6.45 ± 0.95 vs. 3.00 ± 5.54, P = 0.037). State anxiety tended to have a greater effect in the experimental group than in the control group ( P = 0.078). Depressive mood and sleep also improved in each group, with no significant difference between the two groups. There were no significant differences in stress-related physiological parameters, such as stress hormones or qEEG, between the two groups. Subjective device satisfaction was significantly higher in the experimental group than in the control group ( P = 0.008). Conclusion Neurofeedback-assisted meditation using a wearable device can help improve subjective stress reduction compared with non-assisted meditation. These results support neurofeedback as an effective adjunct to meditation for relieving stress. Trial Registration Clinical Research Information Service Identifier: KCT0007413

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Design of a Neurofeedback Training System for Meditation Based on EEG Technology

Cited by 2 publications

References 30 publications

Architectural Proposal for Low-Cost Brain–Computer Interfaces with ROS Systems for the Control of Robotic Arms in Autonomous Wheelchairs

Architectural Proposal for Low-Cost Brain–Computer Interfaces with ROS Systems for the Control of Robotic Arms in Autonomous Wheelchairs

Modest Effects of Neurofeedback-Assisted Meditation Using a Wearable Device on Stress Reduction: A Randomized, Double-Blind, and Controlled Study

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