We have created a method that will easily allow product developers to add four highly effective protocols to their software by inserting an SDK (software library) developed from our previous published research.
There is a genuine need for a simple way to spread easy-to-use neurofeedback technology with face validity to a wide variety of professional and school training markets that are currently not reached by manufacturers. One of the most important for the field is the addition of modules on neurofeedback in high school and college physiology courses. This will spread knowledge about the field more quickly. In addition, there is a huge market for neurofeedback in the home which can be performed inexpensively for issues such as focus, happiness, depression, and cognitive decline, after appropriate training. There are major potential markets involving incorporating appropriate EEG measurements in fitness tracking devices such as smart watches, smart glasses, and phone apps.
For many years, my colleagues and I have been working to develop four simple protocols for monitoring and training EEG. Each of them is understandable within three minutes of testing following instructions and produces remarkably fast training results.
The presentation will first review the four protocols and the research behind them:
1. Single-pointed focus–the Inhibit All protocol unfortunately nicknamed “squash” (Collura, 2017)
2. Alertness or Arousal (Hillard et al. 2013)
3. Neureka!–The clarified 40 Hz. thalamocortical rhythm which enhances attention and memory, and produces positive feelings as a reward for this effort. (Sokhadze & Daniels, 2016). It also improves autistic issues (Wang et al. 2016; Sokhadze et al. 2019).
4. Mood Elevator–an adaptation of Walker’s (Walker & Lawson, 2013) system for improving treatment-resistant depression in six sessions.
We developed all of these protocols using BioExplorer, which has been basically abandoned by its developer, who has not provided reliable supplies or support for years.
The current effort involved reproducing the combination of standardized EEG processing functions, which are not patented, in BioExplorer, using original code, not from BioExplorer. This was done according to our algorithms outside of Bio Explorer, by creating independent software libraries in C++ and translating them into Windows, Android, and iOS, so that they can easily be inserted and implemented in platforms by many other companies. The input to these libraries is the raw EEG from our headband or from other sources. The output for each protocol is a series of floating point double precision numbers which are displayed in a Demo program from 0-100. We will show videos of this, and also the development stage where we were able to compare the waveforms of the BioExplorer outputs and the new ones and generally obtain sequential correlations of over .95.We believe that this justifies the conclusion that the new libraries will be just as effective. Although all of our research was performed on single-channel systems and we do not see the need to offer anything more complex to a manufacturer seeking effective neurofeedback, we are interested in developing a multichannel research version through collaboration.
Presented by Jonathan Cowan and Tato Sokhadze