"Comparing the Effect of Neurofeedback and Verbal Self-Instruction on Children Afflicted with Attention-Deficit Hyperactivity Disorder: A Cognitive-Behavioral Approach." | Pendar, Rahim & Bandar, Raheleh & Branch, Abbas & Shokrpour, Nasrin & Taghinezhad, Ali & Azadikhah, Mahboobeh & Nourinezhad, Hoda. | Brain | 2018 | Full Text |
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"Evaluation of Artifact-Controlled Electroencephalographic (EEG) Training: A Pilot Study"
The SmartMind 4 offers the option for home training and the data syncs with the office PC. It supports the Neurobit Optima, Physiodata and the MindWave Mobile 2 EEG devices.
The clinician can configure training exercises to up-train or down-train any specified EEG frequency band using a wide variety of visual and auditory feedback exercises. Results can be graphed: Both simple or multiple frequency bands can be trained at one or more sites.
The unique training feature of SmartMind 4 is that it filters out eye blinks, eye movements, facial muscle activity and heart beats “on-the-fly.” Thus, the feedback provided is Artifact Corrected (AC) Neurofeedback which was been found in an independent double-blind peer reviewed study to result in significant changes in the Theta-Beta Power ratio at the site changed, as well as, significant improvements in IVA-2 test scores.
The changes in the control group for this study was the traditional Neurofeedback training methodology which only excludes high peak EEG signals and excessive muscle tension. Thus, traditional Neurofeedback is only artifact corrected to a very limited degree. In this study referenced above the Limited Artifact Corrected (LAC) group did not demonstrate learned control of the targeted EEG frequency bands and made only minimal improvements in their IVA-2 test scores post training.
It is recognized in published research that QEEG collected under eyes open resting condition generally contains artifact about 80% of the time. This is a result of eye blinks which occur every 2-4 seconds, natural shifts in eye focus resulting in eye movement artifacts and facial muscle activity that masks EEG every time the individual frowns, squints, swallows or smiles.
SmartMind 4 resolves the issue of the high level of naturally occurring artifact which impairs the accuracy of Neurofeedback training by identifying artifact at the sample level and only including in the computation of the EEG amplitude samples which are identified to not be contaminated by any of the numerous types of artifact that frequently occur.
Joseph A. Sandford Ph.D
CEO, BrainTrain, Inc. |
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