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scores
Did you know that by tracking and analyzing your brain’s activity, enophones can help surface unique insifghts on how to improve your over all mental fitness?
Learn how to read the data of your tuning sessions and achieve your desired mind states more easily.
Contributors, the relative values of
your brain frequencies.
Wave Activity offers an unprocessed glimpse into your brain's activity during your session. View the relative behavior of Delta, Theta, Alpha, Beta, and Gamma frequencies during your session.
Brain power, measured in microvolts, varies among individuals and session contexts. The Enophones app provides values tailored to you. By examining these frequencies, you can vsiualize how each one contributed to your mindset during the session.
Evaluate your mind state
with brain frequencies ratios
Focus
Wave Activity is processed to evaluate focus & cognitive engagement by analyzing the ratio of Beta to Alpha frequencies during the session. Studies in neurofeedback, like the one by Bujar Raufi and Luca Longo that is referenced to multiple studies that indicates that shifts in this ratio are linked to shifts in the levels of mental workload (4), meaning an active mind.
Tracking only
Wave Activity is processed to evaluate wakefulness by analyzing the ratio of Alpha + Beta to Delta frequencies during the session. Neurofeedback research indicates that shifts in this ratio correspond to changes in wakeful states.
Calm
Wave Activity is processed to gauge mental tranquility by analyzing the ratio of Alpha to Beta frequencies during the session. Neurofeedback studies like the one by Tee Yi Wen and Siti Armiza Mohd Aris suggest that this ratio decreases in stress condition (3), which is oposite to a calm state of mind.
Sleep
Wave Activity is processed to assess sleep over wake by analyzing the ratio of Delta to Alpha(1) frequencies during the session. Neurofeedback research like the one by K. Šušmáková, A. and Krakovská shows that shifts in this ratio are indicative of a state of sleep, and in this case, the use of the Delta frequency on the ratio calculation, asesess deep sleep.
Wind-down
Wave Activity is processed to assess sleep over wake by analyzing the ratio of Theta to Alpha(1) frequencies during the session. Neurofeedback research like the one by K. Šušmáková, A. and Krakovská shows that shifts in this ratio are indicative of a state of sleep, and in this case, the use of the Theta frequency on the ratio calculation, asesess an early stage of a sleep state.
Flow
Wave Activity is processed to evaluate cognitive engagement by analyzing the synchronization between Theta and Beta frequencies during the session. Neurofeedback research suggests that there is a correlation between this two frequencies during flow state as it is linked to encoding process of data, long term memory, concentration, satisfaction, pleasure and joy, which are some of the described characteristics of flow state (2).
Energy
Wave Activity is processed to assess active mental engagement by analyzing the ratio of Beta to Alpha frequencies during the session. Neurofeedback studies indicate that variations in this ratio reflect active cognitive states.
One single
score to understand
your performance on each session.
Total Score in any session is based on the ratio of each mind state, its specific frequencies and their relative behavior. This score is adjusted to account for factors such as signal quality, your level of stillness, etc. For the most accurate score, all sensors should be making contact with your head during the session.
References
(1) Classification of Waking, Sleep Onset and Deep Sleep by Single Measures, K. Šušmáková, A. Krakovská, Institute of Measurement Science, Slovak Academy of Sciences, Dúbravská cesta 9, 842 19 Bratislava, Slovak Republic, E-mail: kristina.susmakova@savba.sk, P.36
(2) EEG FINDINGS DURING FLOW STATE, AKIŞ DURUMUNDA EEG BULGULARI, Baris Metin1*, Ayse, Kaya Goktepe2, Bernis Sutcubasi Kaya1, Emin Serin3, Cumhur Tas1, FatmanurDolu1, Nevzat Tarhan1, P.50
(3) Electroencephalogram (EEG) stress analysis on alpha/beta ratio and theta/beta ratio, Tee Yi Wen, Siti, Armiza Mohd Aris, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Malaysia, P.179
(4) An Evaluation of the EEG Alpha-to-Theta and Theta-to-Alpha Band Ratios as Indexes of Mental Workload, Bujar Raufi* and Luca Longo, Artificial Intelligence and Cognitive Load Lab, Applied Intelligence Research Centre, School of Computer Science, Technological University Dublin, Dublin, Ireland, P.3