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Passive vs. Active Electrode - Slew-Rate Problem New
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
FAQ: How shall I disinfect EEG caps and electrodes and what kind of disinfection solution shall I use after each recording sessions? New
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.
ActiView Online Cap Maps New
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.
New MMBT-S Video on our YouTube Channel! New
This is part 3 of our 3 series on how to install, set up, and use our MMBT-S Trigger Interface Box. In this part, we will show you how to use the MMBT-S together with the DSI-7 and DSI-24 EEG System from Wearable Sensing as well as E-Prime 3.0 Software from Psychology Software Tools (PST).
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.
February Newsletter 2023 New
Welcome to the February newsletter. This month we have news on MEG, an upcoming video on how to combine EEG & NIRS, and finally great prices on Polhemus Motion Trackers.
Fully Portable MEG System from France
MEG is a technology rarely found in research, until now. What is MEG? In many regards, it is very similar to EEG. One key distinction, however, is that, unlike EEG which records electrical activity, MEG records the magnetic signature of the electrical currents generated by the neuronal activity.
MEG fields pass through the head without any distortion. This is a significant advantage of MEG over EEG. MEG provides a high spatial and temporal resolution. Until recently, MEG technology was difficult and very costly to acquire and implement in research work. However, one company is challenging this norm.
The French company MAG4Health has developed a novel and revolutionary technology that circumvents these issues with highly innovative technology, to improve scientific research.
MAG4Health has developed an MEG system that is fully portable*, and works at room temperature. The company takes a modular approach to their system, enabling customers to upscale the amount of sensors in their system while retaining precise synchronisation, among both sensors and with stimulation devices, simple digital data acquisition and a user-friendly computer interface.
|Works at Room temperature, neither cooled, nor heated||Noise <40 fT/Hz1/2 on 2 of the 3 axis||Bandwidth of >2 kHz, detection of whole brain dynamics||Dynamic range: ±250 nT||High accuracy, operated in continuous offset compensation||Adaptable helmet, automatic localization of sensors|
Systems are configurable with number of sensors ranging from 16 up to 96 sensors (48 up to 288 channels).
The system starts at €350'000 for a 16 sensor OPM MEG system and €225’000 more per rack of 16 sensors (until 96 sensors).
So if you are already interested in this novel MEG technology and want to receive a quote for a system, write us an email by clicking the button below.
*Portability is given within the confines of a magnetically shielded room, as the utilised SQUID technology is a highly sensitive magnetometer.
Visiting the medical manufacturing giant from Japan
This month we wanted to highlight a milestone in the technology of neuroscientific research with you, the combination of EEG and NIRS in full synchrony!
In an upcoming video on our YouTube channel, we are going to show you exactly how you can combine the ActiveTwo from BioSemi together with the LIGHTNIRS from Shimadzu, together with the scientific engineers at Shimadzu Deutschland. Keep an eye on our YouTube channel and subscribe so you get notified when we upload a new video.
Polhemus Motion Trackers
Great new prices!
Get Started with Motion Tracking
We have talked about motion trackers from Polhemus in previous newsletters. Polhemus produces the very best in the motion tracking and with our special prices over on our webshop, there has never been a better time to get your own motion trackers. If you are doing biomechanics research, sports motion analysis or neuroscience, Polhemus has a variety of systems to enrich your research work.
BIOPAC T4 Conference New
If you want to enrich your work by learning the best practices while meeting industry experts in life science research and education, then BIOPAC's T4 Human Physiology Conference is where you need to be!
July 17th - 19th in Santa Barbara, California
There will be a series of how-to workshops as well as hands-on demonstrations on the 4 Ts: Tools, Trends, Techniques, and of course Technologies! These 4 tools will equip you with the knowledge and abilities to measure and analyse human physiology with the help of the research and teaching system provided by BIOPAC. Naturally, the integration with industry-leading third-party systems will be a big part of the event.
What You Will Learn:
- Practical “how-to” instruction on key skills necessary
for recording and analyzing great data.
- How to set up a lab, prepare a subject, place electrodes,
check signal quality, and collect quality data.
- Best practices and important techniques for collecting data,
analyzing data, and integrating third-party tools.
Take advantage of our early bird pricing by February 28th!
New BIOPAC Webinar (09.03.2023) New
Many studies have been published using a hand dynamometer both inside and outside the MRI to objectively quantify exerted effort during experiments most commonly related to the study of motivation. This webinar will focus on this topic and go over everything you need to know to record hand dynamometer data inside the MRI or in the lab. Join BIOPAC's Alex Dimov for this webinar in a week's time.
March 9th at 8 a.m. PT/11 a.m. ET/4 p.m. GMT
What you will learn:
- Setting up in the MRI and inside the lab
- Calibrating the signal in terms of maximum voluntary contraction (MVC)
- Real-time access to the hand dynamometer signal by third-party applications
- Overview of how researchers have used this equipment
- How to create a visual task that provides feedback on exerted effort as well as rewards to the participant
- Tips and tricks for good data
SOME OF OUR RANGE OF PRODUCTS
BIOSEMI - ActiveTwo
BIOSEMI - bringing EEG and ERP to a new level with the original Active Electrode and ActiveTwo EEG Amplifier.
BESA - Research 7.0
BESA - the leading innovators in digital EEG, MEG and MRI software for research and clinical applications.
SHIMADZU - LABNIRS
SHIMADZU - Next-Generation Optical Brain-Function Imaging with functional near-infrared spectroscopy (fNIRS)