A Modular, Wireless and Wearable Biosignal Acquisition Platform
Antonios Doukakis, Aikaterini Smyrli, Makis Livadas, Henrique De Melo Ribeiro, Shadiya Alingal Meethal, Mohamad Reza Shahabian Alashti, Gabriella Lakatos, Patrick Holthaus, Farshid Amirabdollahian
AI summary
Problem
Existing wearable EMG systems force a trade-off between signal fidelity, channel count, power consumption, and form factor, while medical-grade systems remain tethered and bulky. There is a critical need for a truly wearable, scalable platform that delivers high-density biosignal acquisition with real-time streaming for intent-aware robotics.
Approach
The authors designed a distributed Leader-Follower board architecture that aggregates up to 64 EMG channels and a 9-axis IMU, using low-power microcontrollers and a custom low-latency 2.4 GHz wireless link for synchronized, real-time data streaming.
Key results
- Achieves 0.8 µVRMS input-referred noise with 16-bit effective resolution via hardware oversampling
- Scales flexibly from 16 to 64 EMG channels across modular, body-conforming boards
- Maintains balanced performance: 6.1 mW/channel power, 1.37 cm²/channel footprint, and 1.4 kHz wireless sampling
- Validates synchronized HD-EMG and IMU acquisition across eight daily-life activities with clear task-dependent signatures
Why it matters
Provides a compact, scalable foundation for intent-aware wearable robotics, rehabilitation, and human-robot interaction by enabling reliable high-density biosignal monitoring outside clinical settings.
Abstract
We present a modular, wireless biosignal acqui- sition platform designed to enable scalable electromyography (EMG) and inertial measurement unit (IMU) sensing for wear- able robotics applications. The system supports up to 64 EMG channels and integrates a 9-axis IMU, leveraging a distributed Leader-Follower board architecture. In this work, we demon- strate synchronised acquisition of 32 EMG channels together with IMU motion data in a fully wireless setup. The embedded firmware ensures low-latency, high-fidelity streaming at 1.4 kHz over a 2.4-GHz industrial, scientific and medical (ISM) band link. Benchmarking shows that the platform maintains uniformly strong performance across noise, power, footprint, bandwidth, and scalability, in contrast to existing designs that optimize only a single metric. Experimental demonstrations confirm reliable acquisition of high-density EMG and IMU signals across functional activities, highlighting the device’s robustness and wearability. The proposed system provides a compact and flexible solution for intent-aware wearable tech- nologies, with applications in assistive exosuits, rehabilitation, and human–robot interaction.