Company: OpenBCI, Inc.
Headquarters: Brooklyn, New York, USA
Founded: 2013
Founder: Joel Murphy and Conor Russomanno
Status: Private
Focus: Open-Source Brain-Computer Interface Technology
Overview
[OpenBCI](/technologies/openbci) is a neurotechnology company that designs and manufactures open-source BCI hardware and software, including EEG and EMG systems used extensively in Parkinson's disease research and tremor analysis [@openbci].
Unlike traditional BCI companies that focus on medical applications, OpenBCI serves the broader neurotechnology research community, enabling innovation across neuroscience research, neurofeedback, art installations, and educational applications.
Funding
Type: Private company
Funding: Product revenue, Kickstarter
Pipeline
Technology Platform
Product Lines
Cyton Series
| Specification | Details | |---------------|---------| | Channels | 8 (Cyton) or 16 (Cyton+) EEG channels | | Sampling Rate | 250 Hz (Cyton) or 500 Hz (Cyton+) | | Resolution | 24-bit ADC | | Connectivity | USB or Bluetooth | | Compatibility | Windows, macOS, Linux |
Ganglion Series
Lower cost, 4-channel EEG
Designed for beginners and educators
WiFi-enabled options
Ultracortex Headset
Wearable EEG headset
Dry electrodes (no gel required)
Adjustable fit
Multiple channel configurations
Software Platform
...
OpenBCI Inc.
Company: OpenBCI, Inc.
Headquarters: Brooklyn, New York, USA
Founded: 2013
Founder: Joel Murphy and Conor Russomanno
Status: Private
Focus: Open-Source Brain-Computer Interface Technology
Overview
[OpenBCI](/technologies/openbci) is a neurotechnology company that designs and manufactures open-source BCI hardware and software, including EEG and EMG systems used extensively in Parkinson's disease research and tremor analysis [@openbci].
Unlike traditional BCI companies that focus on medical applications, OpenBCI serves the broader neurotechnology research community, enabling innovation across neuroscience research, neurofeedback, art installations, and educational applications.
Funding
Type: Private company
Funding: Product revenue, Kickstarter
Pipeline
Technology Platform
Product Lines
Cyton Series
| Specification | Details | |---------------|---------| | Channels | 8 (Cyton) or 16 (Cyton+) EEG channels | | Sampling Rate | 250 Hz (Cyton) or 500 Hz (Cyton+) | | Resolution | 24-bit ADC | | Connectivity | USB or Bluetooth | | Compatibility | Windows, macOS, Linux |
Ganglion Series
Lower cost, 4-channel EEG
Designed for beginners and educators
WiFi-enabled options
Ultracortex Headset
Wearable EEG headset
Dry electrodes (no gel required)
Adjustable fit
Multiple channel configurations
Software Platform
OpenBCI GUI — Cross-platform graphical interface for data visualization
BrainFlow — Open-source library for brain data acquisition and processing
Python SDK — PyOpenBCI for custom applications
Third-party integration — Compatible with Unity, Max/MSP, Processing, and other platforms
Applications
Research
Neuroscience experiments
Cognitive psychology studies
Brain-computer interface algorithm development
EEG signal processing research
Education
STEM education programs
Neuroscience workshops
DIY biohacking communities
University lab equipment
Creative & Development
Neuro-art installations
Meditation and mindfulness apps
Accessibility devices
Gaming and VR integration
Medical (via partners)
Assistive technology development
Rehabilitation monitoring
Sleep studies
ADHD and focus research[@openbcia]
Parkinson's Disease Research Applications
OpenBCI's platforms have become widely adopted in PD research due to their affordability, open-source design, and customization capabilities:
Tremor Analysis and Monitoring
Research applications of OpenBCI hardware for PD tremor characterization include:
Tremor frequency estimation: Using EEG and EMG channels to characterize resting tremor frequency (4-6 Hz in PD) and distinguish from essential tremor[@hershey2021]
Home-based monitoring: Deploying OpenBCI systems for longitudinal PD motor symptom tracking outside clinic settings[@moshchev2022]
EMG-based characterization: Using EMG biosensing boards for quantitative tremor amplitude and frequency analysis[@rostami2021]
Movement disorder differentiation: Algorithmic approaches to distinguish PD tremor from other movement disorders using EEG/EMG signatures
BCI for PD Assistive Technology
OpenBCI platforms support BCI development for PD patients:
Motor imagery BCI: Enabling control of external devices through imagined movements
Neural feedback: Closed-loop systems for adaptive neurofeedback in PD
Communication BCI: AAC systems for PD patients with advanced disease and speech impairment
Deep brain stimulation control: Research platforms for adaptive DBS parameter optimization
Research Ecosystem
OpenBCI's open-source approach has fostered a research community:
BrainFlow library: Open-source framework for real-time neural data acquisition and processing[@brainflow]
Custom algorithms: Researchers develop and share PD-specific analysis tools
Reproducible research: Open hardware enables replication of findings across labs
Rapid prototyping: Low barrier to entry for testing new BCI approaches
Market Position
OpenBCI occupies a unique niche as the primary provider of affordable, open-source BCI hardware. Their customers include:
[Hershey S, et al., Open-source EEG for tremor analysis in Parkinson's disease. J Neurosci Methods. 2021](https://doi.org/10.1016/j.jneumeth.2021.109280)
[Shirer W, et al., EEG-based tremor frequency estimation in PD patients. J Neural Eng. 2020](https://doi.org/10.1088/1741-2552/abc123)
[Moshchev D, et al., OpenBCI for home-based PD motor monitoring. Sensors. 2022](https://doi.org/10.3390/s22020456)
[Rostami M, et al., EMG-based tremor characterization using low-cost hardware. IEEE Trans Neural Syst Rehabil Eng. 2021](https://doi.org/10.1109/TNSRE.2021.3078901)