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It was brought to our attention that a rumour is buzzing around among EEG researchers that there may be an inherent noise problem with active electrodes. The source of this rumour is a paper published by Sarah Laszlo et al. in 2014 (see A direct comparison of active and passive amplification electrodes in the same amplifier system). In this paper, the authors compare the performance of one particular brand (not BioSemi) active electrodes with passive electrodes, both connected to a conventional EEG amplifier (also not BioSemi). Both active and passive electrodes setups were tested with low (2 kOhm) and high (50 kOhm) electrode-to-skin impedances.

The authors find that the total noise (250 Hz bandwidth) for passive electrodes is higher with high electrode impedance, whereas the total noise with the active electrodes is equal (and nearly as low as with passive electrodes with low impedance) for both low and high electrode impedances. However, they also determine that the number of sweeps needed to achieve a reliable ERP result is higher with high electrode impedances for both the active and passive setups. Note though, that the number of required sweeps did not show significant differences between active and passive setups.

The paper starts to derail when the authors attempt to explain why in the tests with high skin-to-electrode impedances, the number of sweeps required for reliable ERP is similar for active and passive setups, instead of a lower number of sweeps for the active case as they would expect on the basis of the better total noise results. So although the active electrodes do not perform any worse than passive electrodes, they basically wonder why the performance is not better than it is.

A logical first step in analyzing the above discrepancy would have been to analyze the noise spectra (for example a relatively small band of extra noise with frequencies around the ERP waveform would explain that the total noise number is hardly influenced whereas the number of required sweeps would certainly be affected). Instead, the authors choose to introduce a hypothesis without any support by measurements or references. The authors suggest that the amplifier in the used active electrodes has a slew rate that is limited to such an extent that it causes distortion of the ERP wave, leading to a higher required number of sweeps than would be expected on the basis of the total noise figures.

It is certainly true that slew rate limitations can lead to signal distortion. The effect usually plays a role only with large (several volts) signals at high (several MHz) frequencies. Suggesting slew rate limitations as a problem for EEG signals (amplitudes in the hundreds of uV range and frequencies below a few hundred Hz) sounds far fetched.

How extreme the hypothesis actually is, can be illustrated by some numbers. The paper shows ERP results with a bandwidth of 250 Hz and an amplitude of 6 uV. The required slew rate to acquire this waveform without distortion is approx. 0.01 V/s (min SR = 2*pi*f*Vpk-pk, see for example the Wikipedia page on Slew Rate). Now consider the standard BioSemi ActiveTwo EEG system with active electrodes. At 16 kHz sample rate, this system can acquire a 3 kHz, 0.5 Vpk-pk wave without significant distortion. The complete system (active electrodes, post-amplifier, analog-to-digital converter) therefore has a slew rate of at least 10,000 V/s (or 0.01 V/us in the more usual notation). The standard BioSemi active electrodes are also applied in a high-frequency version of the ActiveTwo system with 262 kHz sample rate. The setup accurately acquires a maximal sine wave of 80 kHz, 0.5 Vpk-pk, leading to a slew rate estimate for the standard BioSemi active electrodes of at least 0.2 V/us. This is a factor of 20 million faster than in the Laszlo hypothesis. Refer to the following result for a 20 kHz, 40 mVpk-pk input signal acquired with standard BioSemi electrodes and a 262 kHz sample rate version of the ActiveTwo system (the dots indicate sample points at 3.8 us intervals). Note the fast rise and fall times of the square wave edges indicating good slew rate performance (the plot shows rise/fall times of approx 10 us, this is a limitation for step responses of the decimation filter in the ADC).

Designers of EEG systems, with or without active electrodes, all make use of a relatively small pool of quite similar Op-amps (building blocks for amplifier circuits) and ADCs provided by a handful of semiconductor manufacturers. These components all offer slew rates far beyond what is minimally required for EEG signals. I am therefore quite sure that our competitors can present results similar as found for the BioSemi setup. This is supported by the input range and bandwidth figures published by various manufacturers. While I would not hesitate to spread doubts about performance aspects of products by BioSemi's competitors, the limited slew rate argument is so unlikely for any currently available EEG system (with or without active electrodes) that I would never consider using it.

In other words: it is doubtful that the particular (non BioSemi) active electrode evaluated in the paper has a slew rate with a factor of 20 million slower than the BioSemi active electrode. Anyway, such an extremely slow slew rate would have been immediately apparent in the waveforms generated by relatively large and fast artifacts in the EEG signal, such as eyeblinks. In addition, the phenomenon would have been straight forward to measure by connecting the active electrodes to a signal generator. The paper does not indicate that any attempt was made to verify the hypothesis with measurements. Given that the particular active electrodes as tested in the paper are quite widespread under EEG researchers, it is hard to imagine that a slew rate limitation of 0.01 V/s would have remained unnoticed for years among these researchers.

The authors make things worse by stating that slew rate limitations are more severe for amplifiers "at very low output impedance". They even refer to BioSemi to support this claim. In reality, BioSemi never has made such a statement and with good reason: it simply is not true. There are numerous amplifier designs with high slew rate and low output impedance, the BioSemi active electrode as presented above is just an example.

The last sentence of the paragraph is the most bizarre. While it is, of course, true that passive electrodes do not have the slew rate limitations associated with amplifier circuitry, the authors overlook that the input stage of an EEG amplifier for passive electrodes also has high input impedance, low output impedance and slew rate limitations. In terms of amplifier noise, input and output impedances and slew rate, the only principle difference between the active and the passive setup is the location of the first amplifier stage. The statement that "slew rate [..] is simply not an issue for passive electrodes" is therefore surprising. In reality, both active electrodes and input stages for passive electrodes have the same slew rate limitations, although as outlined above, it is unlikely that any EEG system (active or passive) using currently available electronic components will present a problem in this respect. Instead, the authors suggest that slew-rate limitation is an inherent problem encountered with all active electrodes (regardless of brand and design), whereas the effect is totally eliminated in all amplifiers for passive electrodes.

To summarize: the paper presents an unlikely hypothesis that is not verified and not supported by any valid reference. The authors fail to do the simple measurements or numerical evaluation that would have readily falsified the hypothesis. Nevertheless, they find themselves qualified to apply this questionable hypothesis not only to the particular active electrode evaluated in the paper but to the active electrode design in general. In effect, they disqualify all active electrodes, including the successful BioSemi design, and confuse the scientific discussion about the merits of the active electrode principle. It is peculiar to see that such an unjustified accusation, that may affect legitimate manufacturers who put a lot of effort in improving EEG acquisition systems, can make it through the review process of Journal of Neuroscience Methods.

This is an article published by Coen Metting van Rijn, PhD, director, BioSemi, 5-December 2019

Soap is a lipophilic substance, meaning that it has the ability to chemically bind to fatty/oily substances. The weakest link of the novel SARS-CoV-2 (a.k.a. COVID-19 virus) is the lipid (fatty) bilayer membrane. Due to this fact, soap will resolve the fatty outer layer of the virus and it becomes inactive. We advise cleaning the head-caps with warm water and soap. A shampoo optimized for delicate fabric is advised, such as Ivory Shampoo (which can be purchased from our online shop: https://shop.neurospec.com/ivory-electrode-cap-shampoo-750ml), or similar. When cleaning, use a soft brush to clean and degrease the inside of the electrode holders.

According to literature, alcohol (ethanol or isopropanol) makes the virus inactive within 30 seconds. The electrodes can be submerged in alcohol without damage. Hence, submerging the electrodes for five minutes in alcohol should be the most effective way to prevent COVID-19 infections. Furthermore, the U.S. Food and Drug Administration (FDA) recommends using alcohol-based disinfectant solutions with greater than 60% ethanol or 70% isopropanol. 

Browse Disinfectants

All of us here at NEUROSPEC AG are proud to bring you the ActiView Online Cap Maps, which we have developed in collaboration with BioSemi to work together with the ActiveTwo.

The ActiView Online Cap Maps allow you to view the offsets of your online connected ActiveTwo through your browser on your desktop computer and even mobile devices. With coloured offsets, you will be able to easily identify the quality of your connected electrodes.

Simply download and install the latest version (current version 8.12) of ActiView, connect your ActiveTwo with plugged in electrode sets and navigate to Offset > Upload to Cloud in the ActiView software.
The offsets are streamed via a secured connection to the BioSemi servers. The offsets are then made available here.

After loading ActiView Online Cap Maps enter your device ID (found in About/Configure > Server ID) and select desired electrode layout (16, 32, 64 or 128 layout available). After saving these settings, offsets are displayed in different colours. Green indicates low offset values, purple high offset values and grey indicates that CMS/DRL is not connected.

If you wish to check multiple ActiveTwos simultaneously, simply open an additional private browser window and set the appropriate device ID and electrode layout.

Cap Maps

This is part 2 of our series on combining a NIRS and EEG experiment in a single setup and merging the data.

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Subscribe to stay up-to-date with future releases. In EEG experiments, timing is everything. As a researcher, you need to know the precise moment an event happens. This is why we here at NEUROSPEC came up with the MMBT-S Trigger Interface Box. The MMBT-S allows for sending 8-bit trigger markers via the USB socket on your computer with sub-millisecond precision.

What you will learn:

• How to use the MMBT-S with the DSI-7/DSI-24 EEG Systems from Wearable Sensing
• How to use the MMBT-S with E-Prime 3.0 Software from Psychology Software Tools (PST)

One last thing:

Want to stay up to date with future releases? We regularly produce new content on all the subjects and questions neuroscience researchers come across every day. Please consider subscribing to our channel as this massively helps out the growth and quality of our productions.

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After a long wait, we are thrilled to officially announce the third iteration of the industry-leading active EEG system from BioSemi - the ActiveThree!

With improvements in capabilities, form factor, weight, and energy consumption, this is the future of active EEG systems. Learn more on our website.

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Here's what our CEO, Marc Mosimann has to say about the new system:

“A few weeks ago, we received the very first ActiveThree system and were highly impressed by the size, intuitive design, weight, and of course the technical features of this system compared to the ActiveTwo. We are very excited for researcher to experience the new features in this new technology available from us.”

- Marc Mosimann, CEO NEUROSPEC AG

Finding just the right cable to connect the various systems and accessories available can oftentimes be a challenge for our customers. That is why we often assemble high-quality, bespoke cables that fit any need that can arise.

Order a custom cable with the form below

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All we require from you is the following information:

• Splitter Cable? Yes/No
• Cable Length (cm or in)
• Cable Thickness (cm or in)
• Connector Type A (i.e. D-Sub 25)
• Connector Type B (i.e. 3.5mm jack)

 We will put together an estimate on lead-time and price, make the cable and ship it out to you as quickly as possible.

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It is always exciting to see the work our customers do with the systems we supply them with. Seeing researchers go from an initial concept and idea of what they would like to do to completing their research and making incredible articles and videos like these

EPFL making use of a DS5 supplied by NEUROSPEC AG

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This particular customer approached us a while ago, interested in a DS5 Isolated Bipolar Constant Current Stimulator and combined it together with VR technology to improve spatial navigation. This study aims to address the growing issue of dementia in an aging population. If you are also interested in conducting a new research project but don't know how to get started, then reach out to us and let us know! 

4T: TOOLS, TRENDS, TECHNIQUES, AND TECHNOLOGY

Join BIOPAC for three days of hands-on, small-group human physiology workshops, presented by renowned experts, on the beautiful UC Santa Barbara campus in California, USA. Learn how to collect great data from experts in their field.

Monday, July 14 – Wednesday, July 16, 2025

4T Human Physiology Conference

WHO SHOULD ATTEND

If you measure physiology from human subjects or work with those who do, you should attend!

Anyone who records and analyzes human physiology data as part of their research and/or those who teach human physiology or related subjects: academic scientists, industry applied researchers and educators. 

WHAT YOU WILL LEARN

The 4T Conference is unique in that attendees will receive practical “how-to” instruction in key skills necessary for recording and analyzing great life science data.

Workshops are interactive and include the tools, tips, and strategies for recording high-quality data from study participants. The conference focuses on technology and trends in the industry and provides physiologists with an opportunity to develop their skills and knowledge. The workshops cover preparation, acquiring data, and analysis. Physiology educators will learn-by-doing the proven, high engagement, student-centred strategies for incorporating physiology education into their program of instruction. Use the Justification Toolkit to justify and gain support from your supervisor or department head.

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Join us for BIOPAC's newest webinar on enhancing psychophysiological research by integrating multimodal data acquisition. Attend this webinar if you are interested in integrating data from various hardware devices into a unified data acquisition and analysis platform. Learn how to collect data from multiple participants and multiple hardware devices both in and out of the lab. AcqKnowledge has a range of tools that help with hardware and signal integration and control, plus it can broadcast data in real-time to third-party software and applications.

November 21^st at 8 a.m. PT/11 a.m. ET/ 3 p.m. GMT

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What You Will Learn:

• How to combine physiological data with multichannel EEG, eye tracking, facial expressions, and video
• Explore use cases that require extensive data channels and participant numbers
• How to integrate different hardware and data sources
• Discover how this software enables the combination and control of multiple hardware devices from a single interface, including triggering third-party devices for synchronized data streams

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