Wearable Sensing’s wireless DSI-Flex is the leading dry electrode EEG system in terms of signal quality and comfort. The DSI-Flex takes on average less than 5 minutes 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.
The DSI-Flex has dry sensors on flexible cables, enabling scientists to place the electrodes in varying configurations on the head. These flexible sensors are designed to be screwed into custom caps, so that scientists can order 1 DSI-Flex, and multiple caps, allowing for rapid application of multiple electrode configurations. Every sensor on the DSI-Flex can be customized as either ExG, GSR, TEMP, and REP. 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, & Brain-Computer Interfaces
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-Flex can be customized so that an EEG sensor is replaced with a DSI auxiliary sensor. There are up to 7 locations on the DSI-Flex, enabling any configuration of the following sensors: EEG, ECG, EMG, EOG, GSR, RESP, & TEMP. 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.
Up to 7 Custom Sensor Locations
Reference / Ground
Common Mode Follower / Custom
Head Size Range
300 Hz (600Hz upgrade available)
0.003 – 150 Hz
0.317 μV referred to input
Input Impedance (1Hz)
> 120 dB
Amplifier / Digitizer
16 bits / 7 channels
> 12 hours
~ 68 Hours (available option)
Real time, evoked potentials
Signal Quality Monitoring
Continuous impedance, Baseline offset, Noise (1-50 Hz)
Raw and Filtered Data available
.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
Applied Neuroscience NeuroGuide; Brainmaster Brain Avatar; EEGer
Comparison of a Novel Dry Electrode Headset to Standard Routine EEG in Veterans Journal Article
In: Journal of Clinical Neurophysiology, vol. 33, no. 6, pp. 530–537, 2016.
Exploring neuroplasticity in acute mild traumatic brain injury Journal Article
In: The FASEB Journal, vol. 30, pp. 992–4, 2016.
Investigation of engagement of viewers in movie trailers using electroencephalography Journal Article
In: Brain-Computer Interfaces, vol. 2, no. 4, pp. 193–201, 2015.
Brain activation profiles in mTBI: Evidence from combined resting-state EEG and MEG activity Conference
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE IEEE, Milan, Italy, 2015, ISSN: 1558-4615.
Usability of four commercially-oriented EEG systems Journal Article
In: Journal of Neural Engineering, vol. 11, no. 4, pp. 046018, 2014.
EEG and eye-tracking based measures for enhanced training Conference
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE 2012, ISSN: 1557-170X.
Evaluation of a Dry Electrode System for Electroencephalography: Applications for Psychophysiological Cognitive Workload Assessment Journal Article
In: vol. 54, no. 3, pp. 210–214, 2010.
Using Electroencephalography to Measure Cognitive Load Journal Article
In: Educational Psychology Review, vol. 22, no. 4, pp. 425–438, 2010.
Electroencephalogram (EEG) Study of Learning Effects across Addition Problems Technical Report
PEBL Technical Report Series 2010.