Background/aim: The smartphone application called Auto Train Brain aims to improve reading comprehension and speed for people with dyslexia through neurofeedback. Clinical trials have been conducted to examine the efficacy of neurofeedback on dyslexia. However, accurately measuring long-term outcomes with rapidly changing EEG data can be challenging without the use of psychometric tests. To overcome this issue, a novel measurement method was developed using the sample entropy variance calculated in the gamma band to compare different sessions.
Materials and methods: 40 children with dyslexia aged 7 to 10 consisted of the experimental group that was randomly assigned and they used Auto Train Brain for six months.
Results: Results of the study showed that after 100 sessions, the 14-channel neurofeedback with Auto Train Brain was more effective in increasing the gamma band entropy variance in the left temporal lobe (T7) compared to that of the right temporal lobe (T8).
Conclusion: Using the measurement of gamma band entropy variance was identified as a suitable approach to assess the success of neurofeedback.
Keywords: Neurofeedback, sample entropy, Auto Train Brain, learning disorders, dyslexia, EEG.