Dry Sensor Interface


Dry - Mobile - Fast - EEG

Wearable Sensing’s wireless DSI-EEG+fNIRS system is the first truly hybrid system, enabling simultaneous, automatically synchronized recordings of dry EEG and fNIRS from the same location.  The system is built with Wearable Sensing’s leading dry electrodes in terms of signal quality and comfort, and Archinoetics ultra-bright LED’s integrated into the emitters. The DSI-EEG+fNIRS takes on average less than 3 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-EEG+fNIRS has 8 pods, each with 4 emitters and 4 detectors, and a dry electrode EEG sensor in the middle. There are 2 pods on the pre-frontal cortex, 2 pods on the temporal lobe, 2 pods on the motor cortex, and 2 pods on the occipital lobe. This sensor configuration allows scientists to do a variety of different experiments, including mental workload tasks, auditory tasks, motor tasks, and visual tasks. 

Used around the world by leaders in Research, & Brain-Computer Interfaces

Truly Hybrid EEG+fNRIS

The DSI EEG+fNIRS system is the first true hybrid system on the market, enabling colocalized recordings of the two modalities, designed for various neurovascular coupling research. There are a total of 8 sensor pods on the system, and each pod has 1 EEG sensor in the middle, 4 emitters, and 4 detectors surrounding. All of the data is digitized together, and thus, synchronized automatically

Integrated Mayer Wave Removal

Mayer wave is a systemic oscilliation in the blood throughout the whole body, that causing a slow frequency artifact in fNIRS. The configuration of the emitters and detectors on each pod allows us to record short distance and long distance paths. The short distance path allows us record only the Mayer wave, while long distance gives us Mayer wavbe and fNIRS. Using linear regression, we can automatically remove this artifact from the data

EEG+fNIRS based Cognitive Gauges

Using QStates, we were able to differentiate the selectivity of the pod locations based on specific tasks. We trained 4 models to classify whether the subject was doing a visual (red), auditory (blue), cognitive (green), or psychomotor task (purple). Then, we ran a single trial where the subject started by doing each type of task individually, and we were able to clearly classify the cognitive state based on the task at hand


Ultra Bright Emitters

Wearable Sensing has partnered with Archinoetics to integrate their extremely powerful LEDs into the emitters. In the figure shown above, you can see how our emitters (red line) are brighter, and turn on and off faster than traditional fNIRS emitters (black line). This will allow the detector to have more time to detect activity, and thus create a stronger and more robust fNIRS signal. We also have a custom silicon photodiode with gain, amplified directly at the source.

Research-Grade Signal Quality

With over 90% correlation to research-grade wet EEG systems, the dry sensor interface (DSI) offers unparalleled quality and performance

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Extreme Comfort

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

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Free Data Acquisition Software

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

Artifact Immunity

Faraday cage's, spring-loaded electrodes, and our patented common-mode follower technology, provides near immunity against electrical and motion artifacts

1 Minute Cleaning

Using 70% isopropyl alcohol and a cleaning brush, the DSI-EEG+fNIR only takes a minute to clean, 3 minutes to dry, and can be up and running on the next subject in minutes

Free API

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

Rapid Setup

The DSI-EEG+fNIRS was designed for ultra-rapid setup, taking on average less than 3 minutes to don. Software automatically tunes fNIRS for most optimal path

Ambulatory System

DSI headsets have active sensors, amplifiers, digitizers, batteries, onboard storage, and wireless transmission, making them complete, mobile, wearable EEG systems

Cognitive Gauges

DSI systems exclusively work with QStates, a machine learning algorithm for cognitive classification on states such as mental workload, engagement, and fatigue

Wireless Synchronization

Our Wireless Trigger Hub simplifies the synchronization of DSI headsets with other devices. It features: 

  • 8 trigger input and output channels (independent and parallel port)
  • 4 Analog inputs for TTL pulses or other analog triggers with BNC and Stereo connectors
  • 2 Switch inputs for push buttons or photodiodes
  • 1 Audio input on a mono connector
  • All channels have an adjustable trigger threshold
  • All inputs are thresholded and sent as digital triggers on independent outputs and a parallel output
  • Parallel-USB interface is available as an option g standard cables.

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.

Auxiliary Sensors

The DSI-24 has 3 auxiliary inputs on the headset, which allows for automatic synchronization of Wearable Sensing’s auxiliary sensors to the EEG. The sensors available include 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.


EEG Channels

Fp1, Fp2, C3, C4, T3, T4, O1, O2, A1, A2

Reference / Ground 

Common Mode Follower (Pz) / Fpz

Head Size Range

52cm – 62cm circumference

Sampling Rate

300 Hz (600Hz upgrade available) EEG
15 Hz fNIR


0.003 – 150 Hz EEG
40 nm fNIR


4 Emitters and 4 Detectors

fNIR Emitters

4 LED (Class I Laser) per sensor

Emitter Frequencies

760, 808, 850 nm

fNIR Detectors

SiPD with integrated Gain

Detector Sensitivity

0.13 pW



Wireless Range

10 m

Run Time

4 hours


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

Compatible Software

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


CAPTIV Neurolab


Presentation; E-Prime

Neurovascular Coupling







Monitoring Children

Studying Brain Stimulation

Enhancing BCI