About
OpenEarable is the world's first fully open-source AI platform for ear-based sensing applications. Combining true wireless audio with an extraordinary suite of sensors, it enables developers, researchers, and companies to build advanced wearable applications that were previously impossible with off-the-shelf earphones. The platform integrates a 9-axis Inertial Measurement Unit (accelerometer, gyroscope, magnetometer), dual in-ear and out-of-ear microphones capable of capturing infrasound to ultrasound frequencies, a photoplethysmography (PPG) sensor for heart rate and SpO2 monitoring, a 3-axis bone conduction accelerometer, and a factory-calibrated optical skin temperature sensor. Data can be streamed in real-time via Bluetooth Low Energy or recorded at high rates to an internal microSD card. OpenEarable is modular and reconfigurable, making it ideal for both prototyping and production research. Its integration with edge-ml.org enables no-code machine learning pipelines directly on the device. The platform is trusted by companies and research labs worldwide, with published papers covering applications from respiration rate estimation to chewing detection and CPR support. Whether you are building health monitoring applications, studying silent speech recognition via bone conduction, detecting sleep apnea, or tracking athletic performance, OpenEarable provides the open, extensible foundation to bring your ideas to life.
Key Features
- Multi-Sensor Array: Integrates 30+ detectable phenomena via dual microphones (infrasound to ultrasound), 9-axis IMU, PPG, bone conduction accelerometer, and optical skin temperature sensor.
- True Wireless Audio: Supports full LEAudio wireless audio streaming alongside sensor data, enabling simultaneous audio and biosensing in a compact earphone form factor.
- Real-Time BLE Streaming & SD Recording: Stream sensor data in real-time over Bluetooth Low Energy or record at high sampling rates (up to 800 Hz) to an internal microSD card for offline analysis.
- No-Code Edge Machine Learning: Integrates with edge-ml.org to enable on-device machine learning pipelines without coding, making AI model deployment accessible to researchers and developers alike.
- Fully Open-Source & Modular: All hardware schematics, firmware, libraries, and apps are open-source. The modular, reconfigurable design supports custom extensions for research and commercial applications.
Use Cases
- Continuous health monitoring including heart rate, SpO2, and skin temperature for clinical or consumer wellness applications.
- Research into ear-based biometrics such as ear canal authentication, silent speech recognition via bone conduction, and respiration rate estimation.
- Sports and fitness tracking using IMU data to monitor head motion, workout intensity, CPR quality, and energy expenditure.
- Detection of physiological behaviors such as chewing side detection, bruxism (teeth grinding), and sleep apnea using multimodal sensor fusion.
- Prototyping and academic research for HCI, wearable computing, and ubiquitous sensing publications backed by real hardware.
Pros
- Unmatched Sensor Density: No other earphone platform offers this breadth of integrated high-precision sensors, enabling detection of over 30 physiological and environmental phenomena.
- Fully Open-Source: Complete transparency across hardware, firmware, and software layers allows deep customization and eliminates vendor lock-in for research and commercial projects.
- Research-Validated: Trusted by universities and companies worldwide, with peer-reviewed publications demonstrating real-world applications across health, HCI, and sports science.
- No-Code ML Integration: The built-in edge-ml.org integration lowers the barrier for deploying on-device AI models, making the platform accessible to non-programmers and domain experts.
Cons
- Requires Physical Hardware: As a hardware-software platform, users must purchase the OpenEarable device, which may involve shipping times and upfront cost compared to purely software solutions.
- Steep Technical Learning Curve: Configuring sensors, integrating custom firmware, and building custom applications requires embedded systems or software development knowledge.
- Niche Application Domain: The platform is purpose-built for ear-based sensing; developers outside wearables, health tech, or HCI research may find limited direct applicability.
Frequently Asked Questions
What is OpenEarable?
OpenEarable is the world's first fully open-source AI platform for ear-based sensing. It combines true wireless audio with a rich suite of biosensors (IMU, PPG, microphones, temperature) in a compact earphone form factor, designed for research and development applications.
Is OpenEarable free to use?
The software, firmware, libraries, and tools are all free and open-source. You will need to purchase the OpenEarable hardware device, which is available through the official website, including a live demo option with no commitment.
What sensors does OpenEarable include?
OpenEarable includes dual infrasound-to-ultrasound microphones (in-ear and out-of-ear), a 9-axis IMU (accelerometer, gyroscope, magnetometer), a PPG pulse oximeter for heart rate and SpO2, a 3-axis bone conduction accelerometer, and an optical skin temperature sensor.
What kinds of applications can I build with OpenEarable?
You can build applications for health monitoring (heart rate, SpO2, respiration rate, sleep apnea), motion and workout tracking, silent speech recognition via bone conduction, eating and chewing detection, ear canal authentication, stress monitoring, and many more — over 30 detectable phenomena in total.
Does OpenEarable support machine learning on the device?
Yes. OpenEarable integrates with edge-ml.org, which provides a no-code interface for training and deploying machine learning models directly on the device, enabling real-time on-device inference without cloud dependency.
