g.Nautilus fNIRS is a wearable headset that enables simultaneous recordings of EEG and fNIRS (functional near-infrared spectroscopy) signals. fNIRS measures the oxygenation level and hemodynamics of the brain non-invasively. The oxygenation level change as brain areas become more active. Researchers can identify brain activity in real-time based on changes in blood oxygenation and other factors.
The EEG indicates the electrical activity in the brain and provides high temporal resolution, unlike fNIRS. However, a simultaneous recording of both fNIRS and EEG signals in one single device is highly beneficial. EEG signals indicate motor imagery while fNIRS signals show long lasting changes like mental counting or pain. In other words, researchers can capture what might be missed when using only EEG or fNIRS.
The g.Nautilus fNIRS is a mobile device and compatible with EEG which sets a new standard of usability. In combination with g.tec’s active EEG electrode technology, researchers get top-quality EEG recordings from 64/32/16/8 g.SCARABEO EEG channels and 8 fNIRS channels within a few minutes.
|Combined fNIRS and EEG measurements with a single wearable headset|
|g.SCARABEO active wet EEG electrodes|
|Flexible positioning of EEG electrodes|
|LED based fNIRS sensors for the forehead and for central positions|
|64/32/16/8 channel wearable EEG with 3-axis accelerometer|
|24 bit accuracy at 250/500 Hz sampling rate for EEG, use only one device with 500 Hz in one room|
|10 Hz sampling rate for (8 channels) fNIRS|
|10 hours continuous EEG recording and 2-3 hours charging (32 channel version); 1.5 hours (high power LED) – 8 hours (low power LED) of fNIRS recording|
|Wireless digital transmission, range: 10 meters indoor|
|A new benchmark in usability|
|The only wearable EEG+fNIRS headset with active EEG technology|
|g.tec's unique internal impedance check|
|Full integration into g.tec's software environment|
|Used for research applications only|
|Weight||500 g without fNIRS battery box|
|Size||78 (L) x 122 (W) x 50 (H) mm|
|Sensitivity||±2.25 V, ±1.125 V, ±750 mV, ±562,5 mV, ±375 mV, ±187.5 mV (software selectable)|
|Interface||Wireless 2.4 GHz ISM band|
|Digital inputs||8 digital trigger inputs at Base Station|
|EEG Supply||Built-in lithium ion battery, runtime > 10 h, inductive charging according to the QI standard of the Wireless Power Consortium|
|fNIRS Supply||Exchangeable lithium ion battery|
|Amplifier type||Real DC coupled|
|32 × ADC||24 Bit (1.024 MHz internal sampling per channel)|
|Noise level||< 0.6 µV RMS between 1 and 30 Hz (at highest input sensitivity)|
|Input channels||Up to 32 mono-polar / 16 bi-polar channels with GND and REF (software selectable)|
|Input impedance||DC > 100 MOhm|
“We will witness more and more mixed fNIRS and EEG BCIs entering into the human augmentation arena, as more and more machine learning and AI will be coming into our lives.”Tomasz Rutowski, PhD - Research Scientist at RIKEN AIP, Japan
MEASURING EMOTIONAL RESPONSE
Dolby Laboratories is widely known for producing great sound in cinemas. Within their research, Dolby Labs use g.Nautilus wearable EEG headset to study their audience while they are watching videos. Their goal is to better understand what makes viewers engaged, what makes their skin blush, increase their heart-rate or give them goose bumps.
UNLIMITED POSSIBILITIES OF FNIRS & EEG
Wearable EEG headsets are becoming increasingly important in medical and clinical environments because more and more studies are conducted in the field instead of the lab. g.Nautilus is a tiny and lightweight EEG amplifier and attached to a wireless g.GAMMAcap in order to avoid artifacts from cable movements and to allow completely free movements.
Furthermore, g.Nautilus wearable EEG headsets are available with g.SAHARA hybrid active or g.SCARABEO active wet EEG electrodes. These unique EEG electrodes technologies enable top-quality EEG recordings from 8 to 64 channels within a few minutes.
USE FAST AND SLOW BRAIN RESPONSES
g.Nautilus fNIRS + EEG headset allows to record EEG signals and fNIRS signals from one single device. This can be used to decode information like motor imagery from the EEG and long lasting changes like mental counting or pain with the fNIRS. As a result, researchers can capture signals that might be missed when using EEG or fNIRS only.