Neurofeedback

Train your brain!

EEG technology can be used for neurofeedback, a technique that allows individuals to self-regulate their brain activity. During neurofeedback sessions, electrodes are placed on the scalp to measure brainwaves, which are then displayed on a monitor or through sound feedback. The individual can observe their brain activity and learn to consciously change it by using various techniques, such as visualization or relaxation. This process can be helpful for individuals with various neurological or psychological conditions, such as ADHD, anxiety, or depression. Neurofeedback has also been shown to improve cognitive performance, including memory, attention, and focus. EEG-based neurofeedback has the advantage of being non-invasive, portable, and customizable, making it a popular tool for both clinical and research settings.

Applications

Changes in Electroencephalogram (EEG) After Foot Stimulation with Embedded Haptic Vibrotactile Trigger Technology: Neuromatrix and Pain Modulation Considerations

This study aimed to compare electroencephalogram (EEG) patterns in subjects wearing cloth socks embedded with haptic vibrotactile trigger technology with those who wore regular socks. The neuromatrix of pain, which is a network of neuronal pathways and circuits responding to sensory stimulation, was targeted by the technology, and its effects on Brodmann areas associated with pain were examined. The DSI-24 and NeuroGuide software were used to record baseline EEG data from 19 scalp locations in 60 adult subjects. The results showed significant differences in EEG patterns between the two groups, indicating that the technology could potentially be considered a beneficial pain management option for patients.

Predicting hypoxic hypoxia using machine learning and wearable sensors

This study aimed to explore the feasibility of using a BCI system with neurofeedback as an intervention for people with mild Alzheimer’s disease. The study used wearable sensing DSI systems to enroll five adults in a nine to thirteen week EEG-based neurofeedback intervention to improve attention and reading skills. Pre and post assessment measures were used to evaluate the 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, and all participants learned to operate a BCI system with training. The results suggest that NFB-based cognitive measures could be useful in treating mild AD.

Wearable Sensing Testimonials

The video showcases several customers of the DSI-24 system who use the device for neurofeedback training. The customers express their satisfaction with the ease of use of the system, the quality of the data, and the comfort of the system.

Hardware

DSI Dry EEG

All of Wearable Sensing's Dry EEG systems can be utilized for Brain Computer Interfaces

Software

3rd Party Compatible Software

List of compatible software, including Neurofeedback, BCI, EEG Analysis, SDK's, and more

Publications

2022

Hu, Yuxia; Wang, Yufei; Zhang, Rui; Hu, Yubo; Fang, Mingzhu; Li, Zhe; Shi, Li; Zhang, Yankun; Zhang, Zhong; Gao, Jinfeng; others,

Assessing stroke rehabilitation degree based on quantitative EEG index and nonlinear parameters Journal Article

In: Cognitive Neurodynamics, pp. 1–9, 2022.

Abstract | Links | BibTeX

2021

Lim, Hyunmi; Ku, Jeonghun

Effect of repetitive neurofeedback training on brain activation during hand exercise Conference

2021 9th International Winter Conference on Brain-Computer Interface (BCI), IEEE 2021, ISBN: 978-1-7281-8486-9.

Abstract | Links | BibTeX

2019

Arakaki, Xianghong; Lee, Ryan; King, Kevin S; Fonteh, Alfred N; Harrington, Michael G

Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals Journal Article

In: PloS one, vol. 14, no. 1, pp. e0208517, 2019.

Abstract | Links | BibTeX

2017

Hunter, Aimee M; Nghiem, Thien X; Cook, Ian A; Krantz, David E; Minzenberg, Michael J; Leuchter, Andrew F

Change in quantitative EEG theta cordance as a potential predictor of repetitive transcranial magnetic stimulation clinical outcome in major depressive disorder Journal Article

In: Clinical EEG and Neuroscience, vol. 49, no. 5, pp. 306–315, 2017.

Abstract | Links | BibTeX

2016

Fridman, Igor; Cordeiro, Malaika; Rais-Bahrami, Khodayar; McDonald, Neil J; Jr, James J Reese; Massaro, An N; Conry, Joan A; Chang, Taeun; Soussou, Walid; Tsuchida, Tammy N

Evaluation of dry sensors for neonatal EEG recordings Journal Article

In: Journal of clinical neurophysiology: official publication of the American Electroencephalographic Society, vol. 33, no. 2, pp. 149, 2016.

Abstract | Links | BibTeX