A Low-Power Bluetooth LE Surface EMG Sensor

We present a low-power Bluetooth Low Energy (BLE) surface electromyography (sEMG) system designed for wearable muscle monitoring. The device integrates a fully custom signal acquisition pipeline — including analog filtering, signal conditioning, dataset-driven waveform reproduction, and BLE-based wireless transmission — centered around a ∆Σ 16-bit ADC and a Nordic nRF52840 SoC. To evaluate its performance, a representative sidekicking motion from a public sEMG dataset was physically reproduced and recorded by both the proposed system and a clinical-grade EMG device. Time and frequency domain analyses show that the system preserves the key features of myoelectric signals within the 30–400 Hz band. Results support its suitability for applications in sports science, rehabilitation, and human–machine interaction.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-16
DOI
https://doi.org/10.5281/zenodo.17363706
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
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article

A Low-Power Bluetooth LE Surface EMG Sensor

Zenodo (CERN European Organization for Nuclear Research)
Muscle activation and electromyography studies
article

A Low-Power Bluetooth LE Surface EMG Sensor

article en

Abstract

We present a low-power Bluetooth Low Energy (BLE) surface electromyography (sEMG) system designed for wearable muscle monitoring. The device integrates a fully custom signal acquisition pipeline — including analog filtering, signal conditioning, dataset-driven waveform reproduction, and BLE-based wireless transmission — centered around a ∆Σ 16-bit ADC and a Nordic nRF52840 SoC. To evaluate its performance, a representative sidekicking motion from a public sEMG dataset was physically reproduced and recorded by both the proposed system and a clinical-grade EMG device. Time and frequency domain analyses show that the system preserves the key features of myoelectric signals within the 30–400 Hz band. Results support its suitability for applications in sports science, rehabilitation, and human–machine interaction.

Zenodo (CERN European Organization for Nuclear Research)
Universidade Federal de Minas Gerais (BR)
Affordable and clean energy
Openalex Percentile: Top 50%
Muscle activation and electromyography studies
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