Wave band spectrum timeline

[eMPee584]

When doing neurofeedback at a local ergotherapist, we had configured this screen for training: Notable useful features:

• colored frequency bands (togglable)
• graph smoothing through configurable time averaging (here: 30s moving average)
• adjustable time frame that gets overdrawn instead of scrolled

Also found some documentation for the µVoltage scale: Document MindWave™ sensor specs @neuro http://support.neurosky.com/kb/technology/eeg-band-frequencies

What are the different EEG Band Frequencies? Delta: 1-3Hz Theta: 4-7Hz Alpha1: 8-9Hz Alpha2: 10-12Hz Beta1: 13-17Hz Beta2: 18-30Hz Gamma1: 31-40Hz Gamma2: 41-50Hz Brainwave Type Frequency range Mental states and conditions Delta 0.1Hz to 3Hz Deep, dreamless sleep, non-REM sleep, unconscious heta 4Hz to 7Hz Intuitive, creative, recall, fantasy, imaginary, dream Alpha 8Hz to 12Hz Relaxed, but not drowsy, tranquil, conscious Low Beta 12Hz to 15Hz Formerly SMR, relaxed yet focused, integrated Midrange Beta 16Hz to 20Hz inking, aware of self & surroundings High Beta 21Hz to 30Hz Alertness, agitation Gamma 30Hz to 100Hz Motor Functions, higher mental activity

http://support.neurosky.com/kb/technology/thinkgear-measurements-mindset-protgem

ThinkGear measurements The single dry sensor and reference pick up potential differences (voltages) on the skin at the forehead and the ear. The two are subtracted through common mode rejection to serve as a single EEG channel, and amplified 8000x to enhance the faint EEG signals. The signals are passed through analog and digital low and high pass filters to retain signals generally in the 1-50Hz range. After correcting for possible aliasing, these signals are ultimately sampled at 128Hz or 512Hz.

Each second, the signal is analyzed in the time domain to detect and correct noise artifacts as much as possible, while retaining as much of the original signal as possible, using NeuroSky's proprietary algorithms. A standard FFT is performed on the filtered signal, and finally the signal is rechecked for noise and artifacts in the frequency domain, again using NeuroSky's proprietary algorithms.

http://support.neurosky.com/kb/technology/how-to-convert-raw-values-to-voltage

How to convert raw values to voltage? For TGAT-based hardware devices (such as TGAT, TGAM, MindSet, MindWave, and MindWave Mobile), the formula for converting raw values to voltage is: [ rawValue * (1.8/4096) ] / 2000

This is due to a 2000x gain, 4096 value range, and 1.8V input voltage.

Please note the gain on actual hardware may be slightly off from 2000x (maybe +/- 5%?), but unless you need to make ultra-sensitive measurements for some reason, that formula should be good enough.

Hope to get forward transforming this app into a fully adjustable Neurofeedback app C;

[nightscape]

Hi Marcel,

I'm still using the little time I have for Wavetuner to improve its infrastructure in order to make it easier for people to start working on it. I don't know when that will be finished (right now I'm waiting for a Pull Request to get merged) but I'll get back to you then!

[eMPee584]

Hi Martin, I fully understand the problem with scarce available time and appreciate your restructuring efforts. However the status display as shown above is IMHO the most effective and useful for neurofeedback and will transform wavetuner from a toy into a serious tool, and that will presumably bring a bunch of potential users and new developers. I really tried but I just don't grok scala and the needed math deep enough to implement it, but should you just make a rough stub implementation of the above graph (i.e. time-averaged frequency band power plot), I could definitely polish the UI and make it fit for real operation. Oh, and I would like to offer a 100DM bounty from my limited student budget ;)

[IkkAlpha]

When doing neurofeedback at a local ergotherapist, we had configured this screen for training: Notable useful features:

* colored frequency bands (togglable)

* graph smoothing through configurable time averaging (here: 30s moving average)

* adjustable time frame that gets overdrawn instead of scrolled

Also found some documentation for the µVoltage scale: Document MindWave™ sensor specs @neuro http://support.neurosky.com/kb/technology/eeg-band-frequencies

What are the different EEG Band Frequencies? Delta: 1-3Hz Theta: 4-7Hz Alpha1: 8-9Hz Alpha2: 10-12Hz Beta1: 13-17Hz Beta2: 18-30Hz Gamma1: 31-40Hz Gamma2: 41-50Hz Brainwave Type Frequency range Mental states and conditions Delta 0.1Hz to 3Hz Deep, dreamless sleep, non-REM sleep, unconscious heta 4Hz to 7Hz Intuitive, creative, recall, fantasy, imaginary, dream Alpha 8Hz to 12Hz Relaxed, but not drowsy, tranquil, conscious Low Beta 12Hz to 15Hz Formerly SMR, relaxed yet focused, integrated Midrange Beta 16Hz to 20Hz inking, aware of self & surroundings High Beta 21Hz to 30Hz Alertness, agitation Gamma 30Hz to 100Hz Motor Functions, higher mental activity

http://support.neurosky.com/kb/technology/thinkgear-measurements-mindset-protgem

ThinkGear measurements The single dry sensor and reference pick up potential differences (voltages) on the skin at the forehead and the ear. The two are subtracted through common mode rejection to serve as a single EEG channel, and amplified 8000x to enhance the faint EEG signals. The signals are passed through analog and digital low and high pass filters to retain signals generally in the 1-50Hz range. After correcting for possible aliasing, these signals are ultimately sampled at 128Hz or 512Hz. Each second, the signal is analyzed in the time domain to detect and correct noise artifacts as much as possible, while retaining as much of the original signal as possible, using NeuroSky's proprietary algorithms. A standard FFT is performed on the filtered signal, and finally the signal is rechecked for noise and artifacts in the frequency domain, again using NeuroSky's proprietary algorithms.

http://support.neurosky.com/kb/technology/how-to-convert-raw-values-to-voltage

How to convert raw values to voltage? For TGAT-based hardware devices (such as TGAT, TGAM, MindSet, MindWave, and MindWave Mobile), the formula for converting raw values to voltage is: [ rawValue * (1.8/4096) ] / 2000 This is due to a 2000x gain, 4096 value range, and 1.8V input voltage. Please note the gain on actual hardware may be slightly off from 2000x (maybe +/- 5%?), but unless you need to make ultra-sensitive measurements for some reason, that formula should be good enough.

Hope to get forward transforming this app into a fully adjustable Neurofeedback app C;

wow excellent info here

[nightscape]

Hey @IkkAlpha, please don't get your hopes to high... This app won't work anymore with modern Android versions and it would take a major effort to port it... You might have a look at https://github.com/neuromore/studio/ It's a desktop app, but it supports a wide range of Neurofeedback devices.