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Xensor

Manufactured by ANT Neuro
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Xensor is a high-performance, multi-channel EEG amplifier developed by ANT Neuro. It is designed to provide reliable and accurate data acquisition for a wide range of neuroscience research and clinical applications. The Xensor features low-noise, high-resolution analog-to-digital conversion, and flexible channel configurations to accommodate various recording needs.

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Lab products found in correlation

Eego mylab system, by ANT Neuro (1 mentions) Waveguard, by ANT Neuro (1 mentions)

Close spelling variants of this product

Xensor™ digitizer (2 citations) Xensor digitizier (2 citations)

4 protocols using xensor

1

Digitization of Optode Positions

Cited 1 time
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Optode positions and fiducial points were digitized with an optical digitizer (Xensor, ANT Neuro, The Netherlands). Because most of the digitizer data of the SIM data set was corrupted due to missing or inaccurate optode locations, digitzer data was not further considered. Moreover, the data sets contain electromyography data that were used in a previous publication28 (link) but are of no relevance for the present study.
Klein F., Lührs M., Benitez-Andonegui A., Roehn P, & Kranczioch C. (2022). Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short distance channels. Neurophotonics, 10(1), 013503.
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2

Ambulatory EEG with Implanted Neural Devices

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Participants with chronically implanted neural devices can also wear a scalp EEG cap that allows for ambulatory behaviors. We integrated, with the Mo-DBRS platform, a mobile 64-channel scalp EEG system (Wave Guard and eego™ mylab system, ANT Neuro, The Netherlands) that includes a lightweight amplifier (~ 2 lbs) which connects to the EEG cap and a small tablet to which data is being transmitted, and which can both be carried in a backpack. For electrode digitization and localization, we used ANT Neuro’s xensor™, a system for real-time EEG electrode pinpointing, digitization, and visualization based on infrared high-accuracy measurements (< 2 mm accuracy). Measurements were performed using a pointer and reference tools (infrared-reflective objects) relative to the head and underlying brain (if MRI was available). Accuracy was further improved by using xensor’s built-in feature for individual head shape generation (ANT Neuro, 2018). Scalp EEG and iEEG data were then synchronized (see the Mo-DBRS Synchronization section below) and analyzed offline.
Topalovic U., Aghajan Z.M., Villaroman D., Hiller S., Christov-Moore L., Wishard T.J., Stangl M., Hasulak N.R., Inman C.S., Fields T.A., Rao V.R., Eliashiv D., Fried I, & Suthana N. (2020). Wireless Programmable Recording and Stimulation of Deep Brain Activity in Freely Moving Humans. Neuron, 108(2), 322-334.e9.
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3

High-Density EEG Recording Protocol

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EEG data were recorded at 1000 Hz via the software eego64 (ANT Neuro, The Netherlands), using a 124-electrode ANT EEG system (ANT Neuro, The Netherlands) with an extended 10/20 layout. The ground electrode was placed on the left mastoid, whereas the reference electrode was located at CPz. All electrodes showed an impedance of <20 kΩ before the recording started. Individual electrode locations as well as fiducials (nasion, right, and left interauricular points) were recorded prior to the experiment using the software Xensor (ANT Neuro, The Netherlands).
Sokoliuk R., Degano G., Melloni L., Noppeney U, & Cruse D. (2021). The Influence of Auditory Attention on Rhythmic Speech Tracking: Implications for Studies of Unresponsive Patients. Frontiers in Human Neuroscience, 15, 702768.
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4

Digitizing Electrode Locations for MRI Coregistration

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We recorded the electrode locations of each participant relative to the surface of the head using the infrared camera system device Xensor (ANT Neuro, The Netherlands). Because we did not acquire individual T1-weighted MRI images for all our participants, we used the template files provided by FieldTrip (MRI file, headmodel and grid) and co-registered the standard T1-weighted anatomical scan of the FieldTrip template (1 mm voxel resolution) to the digitised electrode locations using Fieldtrip (Oostenveld et al., 2011 (link)).
Sokoliuk R., Degano G., Melloni L., Noppeney U, & Cruse D. (2021). The Influence of Auditory Attention on Rhythmic Speech Tracking: Implications for Studies of Unresponsive Patients. Frontiers in Human Neuroscience, 15, 702768.
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