Wearable Sensing’s wireless DSI-7 is the leading dry electrode EEG system in terms of signal quality and comfort. The DSI-7 takes on average less than 1 minute to set up, making it the ideal solution for scientists in need of a simple, easy to use, EEG system. Our patented sensor technology not only delivers uncompromised signal quality but also enables our system to be virtually immune against motion and electrical artifacts. As a result, the DSI-7 can be utilized in virtual or augmented reality, while also allowing researchers to take their experiments out of the lab, and into the real world.
The DSI-7 has sensor locations covering the frontal, center, and posterior areas of the brain. There are 7 sensors whose locations can be customized upon order, and 2 earclip sensors. It also has a 4-bit trigger input to synchronize with other devices such as Eye-Tracking, Motion (IMU), and more.
Used around the world by leaders in Research, Neurofeedback, Neuromarketing, Brain-Computer Interfaces, & Neuroergonomics.
With over 90% correlation to research-grade wet EEG systems, the dry sensor interface (DSI) offers unparalleled quality and performance
Multiple adjustment points and a foam pad lined interior enable the system to be worn for up to 8 hours on any head shape or size
All DSI systems include free, unlimited licenses of DSI-Streamer, our data acquisition software which can record raw data, in .csv and .edf file formats
Faraday cage's, spring-loaded electrodes, and our patented common-mode follower technology, provides near immunity against electrical and motion artifacts
Using 70% isopropyl alcohol and a cleaning brush, the DSI-24 only takes a minute to clean, 3 minutes to dry, and can be up and running on the next subject in minutes
All DSI systems include our free C based .dll API, which enables users to pull the raw data directly from the headset, for custom software on Windows, Mac OS, Linux, and ARM
The DSI-7 was designed for ultra-rapid setup, taking on average less than 1 minute to don, and works on any type of hair, including long hair, thick hair, afros, and more
DSI headsets have active sensors, amplifiers, digitizers, batteries, onboard storage, and wireless transmission, making them complete, mobile, wearable EEG systems
DSI systems exclusively work with QStates, a machine learning algorithm for cognitive classification on states such as mental workload, engagement, and fatigue
Our Wireless Trigger Hub simplifies the synchronization of DSI headsets with other devices. It features:
An additional benefit of the Trigger Hub design is that it allows synchronization across multiple data sources that are distributed across multiple systems, each of which running at its own clock rate. One such case commonly experienced in EEG experiments involves the synchronization of EEG and eye-tracking measurements, where the inevitable clock drift that arises between two systems during extended measurements creates difficulty in aligning data to events across the two systems.
The DSI-7 can be customized to have ECG, EMG, EOG, GSR, RESP, & TEMP. To do this, you can choose to either remove an EEG sensor in exchange for an auxiliary sensor, or you can modify the earclips to record ExG. The sensor data is collected and recorded in our data acquisition software, DSI-Streamer, where you can view the EEG and Aux sensors in real-time.
EEG Channels
Can be customized on demand by manufacturer
Reference / Ground
Common Mode Follower / Fz
Head Size Range
Adult Size: 52cm – 62cm circumference
Child Size: 48cm – 54cm circumference
Sampling Rate
300 Hz (600Hz upgrade available)
Bandwidth
0.003 – 150 Hz
A/D resolution
0.317 μV referred to input
Input Impedance (1Hz)
47 GΩ
CMRR
> 120 dB
Amplifier / Digitizer
16 bits / 7 channels
Wireless
Bluetooth
Wireless Range
10 m
Run-time
> 12 Hours
Onboard Storage
~ 68 Hours (available option)
Data Acquisition
Real time, evoked potentials
Signal Quality Monitoring
Continuous impedance, Baseline offset, Noise (1-50 Hz)
Data Type
Raw and Filtered Data available
File Type
.CSV and .EDF
Data Output Streaming
TCP/IP socket, API (C Based), LSL
Cognitive State Classification
Brain Computer Interface
SSVEP BCI Algorithms; BCI2000; OpenViBE; PsychoPy; BCILab
Data Integration / Analysis
CAPTIV; Lab Streaming Layer; NeuroPype; BrainStorm; NeuroVIS
Neurofeedback
Brainmaster Brain Avatar; EEGer
Neuromarketing
CAPTIV Neurolab
Presentation
Presentation; E-Prime
Rice, Merrill G; Snider, Dallas; Drollinger, Sabrina; Greil, Chris; Bogni, Frank; Phillips, Jeffrey; Raj, Anil; Marco, Katherine; Linnville, Steven
Dry-EEG Manifestations of Acute and Insidious Hypoxia During Simulated Flight Journal Article
In: Aerospace Medicine and Human Performance, vol. 90, no. 2, pp. 92-100, 2019.
@article{rice2019dry,
title = {Dry-EEG Manifestations of Acute and Insidious Hypoxia During Simulated Flight},
author = {Merrill G Rice and Dallas Snider and Sabrina Drollinger and Chris Greil and Frank Bogni and Jeffrey Phillips and Anil Raj and Katherine Marco and Steven Linnville},
doi = {https://doi.org/10.3357/AMHP.5228.2019},
year = {2019},
date = {2019-02-01},
journal = {Aerospace Medicine and Human Performance},
volume = {90},
number = {2},
pages = {92-100},
publisher = {Aerospace Medical Association},
abstract = {INTRODUCTION: Recently, portable dry electroencephalographs (dry-EEGs) have indexed cognitive workload, fatigue, and drowsiness in operational environments. Using this technology this project assessed whether significant changes in brainwave frequency power occurred in response to hypoxic exposures as experienced in military aviation.
METHODS: There were 60 (30 women, 30 men) student Naval Aviators or Flight Officers who were exposed to an intense (acute) high-altitude (25,000 ft) normobaric hypoxic exposure, and 20 min later, more gradual (insidious) normobaric hypoxic exposure up to 20,000 ft while flying a fixed-wing flight simulation and monitored with a dry-EEG system. Using MATLAB, EEG frequencies and power were quantified and analyzed. Cognitive performance was also assessed with a cognitive task validated under hypoxia. Normobaric hypoxia and O2 saturation (Spo 2) were produced and monitored using the Reduced Oxygen Breathing Device (ROBD2).
RESULTS: Significant Spo 2 decreases were recorded at acute 25K and insidious 20K simulated altitudes. Significant power decreases were recorded in all frequencies (alpha, beta, gamma, and theta) and all channels with acute 25K exposures. Gamma, beta, and theta frequency power were significantly decreased with insidious 20K exposures at most of the channels. The frequency power decreases corresponded to significant decreases in cognitive performance and flight performance. Most importantly, frequency power suppressions occurred despite 42% of the volunteers not perceiving they were hypoxic in the acute phase, nor 20% in the insidious phase.
DISCUSSION: Results suggest EEG suppression during acute/insidious hypoxia can index performance decrements. These findings have promising implications in the development of biosensors that mitigate potential in-flight hypoxic physiological episodes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Vergeer, Mark; Mesik, Juraj; Baek, Yihwa; Wilmerding, Kelton; Engel, Stephen A
Orientation-selective contrast adaptation measured with SSVEP Journal Article
In: Journal of Vision, vol. 18, no. 5, pp. 2–2, 2018.
@article{vergeer2018orientation,
title = {Orientation-selective contrast adaptation measured with SSVEP},
author = {Mark Vergeer and Juraj Mesik and Yihwa Baek and Kelton Wilmerding and Stephen A Engel},
doi = {https://doi.org/10.1167/18.5.2},
year = {2018},
date = {2018-05-01},
journal = {Journal of Vision},
volume = {18},
number = {5},
pages = {2--2},
publisher = {The Association for Research in Vision and Ophthalmology},
abstract = {Exposure to oriented luminance contrast patterns causes a reduction in visual sensitivity specifically for the adapter orientation. This orientation selectivity is probably the most studied aspect of contrast adaptation, but it has rarely been measured with steady-state visually evoked potentials (SSVEPs), despite their becoming one of the more popular methods of human neuroscience. Here, we measured orientation selective adaptation by presenting a plaid stimulus of which the horizontal and vertical grating reversed contrast at different temporal frequencies, while recording EEG signals from occipital visual areas. In three experiments, we compared SSVEP responses to the plaid before and after adaptation. All experiments showed a significant decrease in SSVEP response at the frequency of the adapter orientation, whereas such an effect was absent for the frequency of the orthogonal orientation. Adaptation also led to robust phase delays, selectively for the SSVEP frequency corresponding to the adapter orientation. These results demonstrate the efficiency of SSVEPs for measuring orientation selective adaptation; the method can measure changes in both amplitude and phase, simultaneously for two orientations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kohli, Siddharth; Casson, Alexander J
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE Milan, Italy, 2015, ISSN: 1558-4615.
@conference{kohli2015towards,
title = {Towards out-of-the-lab EEG in uncontrolled environments: feasibility study of dry EEG recordings during exercise bike riding},
author = {Siddharth Kohli and Alexander J Casson},
doi = {10.1109/EMBC.2015.7318539},
issn = {1558-4615},
year = {2015},
date = {2015-11-05},
booktitle = {2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
pages = {1025--1028},
address = {Milan, Italy},
organization = {IEEE},
abstract = {Conventional EEG (electroencephalography) has relied on wet electrodes which require conductive gel to help the electrodes make contact with the scalp. In recent years many dry electrode EEG systems have become available that do not require this gel. As a result they are quicker and easier to set up, with the potential to record the the EEG in situations and environments where it has not previously been possible. This paper investigates the practicality of using dry EEG in new non-conventional recording situations. In particular it uses a dry EEG recording system to monitor the EEG while a subject is riding an exercise bike. The results show that good-quality EEG, free from high-amplitude motion artefacts, can be collected in this challenging motion rich environment. In the frequency domain a peak of activity is seen over the motor cortex (C4) at 23 Hz starting five minutes after the start of the exercise task, giving initial insights into the on-going operation of the brain during exercise},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
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