[luckham jerill]

Hello Orozco,

Thank you for your message and feedback. We will certainly look into improving our platform for more convenience for users.

Please send an email to support@emotiv.com so they can reallocate your device allowance. Please provide your EMOTIV ID so we can take a look at your account.

If you need anything else else, please let me know.

[luckham jerill]

Hello Dubcan,

Thank you for your question. We are sorry to hear you are experiencing these inconveniences. This connection dropout problems sometimes happens if the receiver is located close to a WiFi, Bluetooth or other 2.4GHz transmitters – which is often the case in a PC where the antenna is located conveniently next to the USB ports (Mac also has frankly awful electrical isolation so the entire case probably oscillates at 2.4GHz). We always use and strongly recommend using a USB extension lead or powered hub just to get the receiver out of the noisy environment next to the PC. Place it in clear air away from radio sources and in clear line of sight to the headset and your wireless issues may disappear. Hope this helps. Let us know if you need anything else.

[luckham jerill]

Hello Bandari,

Thank you for your question. ’emotivapps_2.7.1.beta_armhf.deb’ is Raspberry pi (beta) Emotiv Installer.

You can download installer from your Downloads section of your EMOTIV account page.

[luckham jerill]

Hello Steve,

Thank you for your message. EPOC and EPOC+ sensors can be replaced with the Hydrator pack. It comes with 16 fully assembled detacheble electrodes for the EEG headset. Here is the link to our store – https://www.emotiv.com/product/emotiv-epoc-hydrator-pack/

If you need anything else, please let us know.

[luckham jerill]

Hello Steiner,

Thank you for your question. The new design sensor with 3 prongs can replace any of the other detachable sensors. We added this 3 prong sensor so it can comb through thick hair easily. It is recommended to be used on the Pz electrode position (the electrode that goes on the back of the head). the sensor replacement pack fit with the kickstarter Insight headset.

The sensor that falls behind your ear are the reference sensors. We do not replace this.

If you have other questions, please let me know.

[luckham jerill]

Hello Bandari,

Thank you for your question. We currently do not support the Emotiv-BCI, and our System Development Kit called CORTEX for Raspberry Pi (either running Emotiv-BCI Node-RED Toolbox locally on Raspberry Pi or remotely to Raspberry Pi).

[luckham jerill]

Hello Chris, thank you for your question.

Yes, the free/trail software allows you to install the software in one computer. Each EMOTIV account allows for 1 device installation for the trial or free versions.

[luckham jerill]

Hello Anna,

Thank you for your question.

Please check the comparison chart for EMOTIV Headset to get an overview of the features and specs of EPOC X -https://www.emotiv.com/comparison/

The accuracy of our technology has been validated by independent studies many times over. The following graphs show an independent comparison of a clinical grade system alongside the EMOTIV EPOC+ in an N100 auditory evoked potential study. Click here – https://www.emotiv.com/independent-studies/validation-of-the-emotiv-epoc-eeg-gaming-system-for-measuring-research-quality-auditory-erps/ to access the journal paper by Badcock et al., PeerJ, 2013.

To view and record brain data, you need to pair the EEG headset with the licensed software. our integrated EEG recording & analysis software allowing:
– Measure and record your brain activity in real-time including raw EEG, and our machine learning algorithms identifying your brain’s Performance Metrics.
– Store data securely: Store, share and analyze EEG data anywhere by saving it to our secured cloud. We fully comply with GDPR, California Consumer Privacy Act (CCPA), and use industry-standard encryption to ensure the privacy of your data.
– Mark events: Define and insert timed markers into the data stream.
– Analyze data better: Customize and view frequency data with automatic FFT and power band graphs.

If you have other questions, please let us know.

[luckham jerill]

Hello Alex,

Thank you for your question.

At the moment, we do not support the feature to send marker via outlet of EmotivPro LSL. We will support it soon in next version. If you have other questions, please let us know. Kindly provide more information about your projects so we can provide the best solutions for your needs.

[luckham jerill]

Hello!

Thank you for your question. We cannot disclose proprietary information like this. If you have other questions, please let us know.

[luckham jerill]

Hello,

Thank you for your reply.

Yes, you are correct. You still need to use the data in the ‘raw’ columns to re-compute the scaled values with the ‘global’ MIN and MAX.

Regarding EmotivPRO prividing the “final” scaling, this is a good suggestion. We considered it, but it may be confusing for people who recorded specific values of each PM at different times during the live recording. We decided it was better to export the data as originally displayed, but provide a means to rescale it to a more consistent scale.

The correlation between rescaled and raw values is very high. The rescaling formula is logistic, which maps -inf to +inf onto the 0-1 range. Outlying data points are compressed into the top and bottom few percent of the 0-1 scale, while retaining a strict monotonic mapping. That is, if raw(t1) > raw(t2) then rescaled(t1) > rescaled(t2) for all t1, t2

Whether you choose raw or rescaled data depends on the requirements of your analysis. Typically different subjects have widely differing range and and baseline values for the same performance metrics. The differences are due to both physical and psychological differences.

Anatomically, every brain is folded differently. Specific functional areas are not perfectly mapped onto the same regions of each cortex. Many major functions are located in ‘similar’ regions for anatomical or developmental reasons, but no two brains are mapped identically due to fairly chaotic developmental processes. The huge cortical area is densely folded to fit inside the very finite skull volume. Different fold patterns and deep, interlocked folds mean that any specific functional region of the cortical surface may be deeply buried in tissue or presented on the outer surface of the cortex, Differing skull thicknesses, location of muscles, blood vessels etc also contribute to wide variations in scale of different PMs.

Different personalities also express different ranges of emotions and different “operating levels” – think of the difference between an ex-fighter pilot who can calmly land a dead passenger plane on the Hudson River, and a cab driver (we’ve all had one) whose natural state is yelling at the traffic and gets enraged by someone daring to ride a bicycle on a city street.

If the target of your research is to compare between different types of stimulus across a population, it is more appropriate to use standardised data such as the rescaled PMs. If you are more interested in differences between individuals, then (perhaps) raw values are more appropriate.

Hope this helps. If you have other questions, please let me know.

[luckham jerill]

Hello,

At the moment, we are not considering to add this feature for remote connection to other OS for now.

[luckham jerill]

Hello Cui,

Thank you for your reply.
Raw performance metrics are usually values that are difficult to interpret as they are not 0-1 values. The reason the scaled values and the raw values are not exactly correlated is because the auto-scaler adjusts & changes in accordance to the min and max values as the recording goes on. This enables the LIVE output to be a better representation of the individuals personal “scale” of stress/focus/engagement relative to the rest of the recording. However, for scientific research and accurate correlation analysis, it is recommended to retrospectively rescale the PM’s when the recording is finished (on export). This can be done using the final max and min values of the PM. Find the last possible values of MAX and MIN where CQ has been continuously usable. Call them MAX_F and MIN_F. MIDDLE_F = (MAX_F + MIN_F) / 2
RANGE_F = ABS( MAX_F – MIN_F )
For each PM_Raw, calculate:
PM_Retro = 1 / ( 1 + exp ( -5 * ( PM_Raw – MIDDLE_F ) / RANGE_F ). @jerill
You can also scale to a baseline (eyes open) condition or express the PM values as a % of baseline levels. (condition – baseline) / baseline to understand how the performance metrics move from baseline levels.

[luckham jerill]

Hello!

Thank you for your questions. Please clarify if you are using high-resolution Performance Metrics or the low-resolution. May we also have your x-axis points?

On the second chart (blue & orange line PM) what type of data is “raw” & “scaled”?

Looking forward to your follow up

[luckham jerill]

Hello!

Thank you for your post. Currently, Cortex doesn’t allow a remote connection except Cortex on Raspberry. If you have other questions, please let us know.

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