IoT Technologies for HealthCare. 7th EAI International Conference, HealthyIoT 2020, Viana do Castelo, Portugal, December 3, 2020, Proceedings

Research Article

Novel Wearable System for Surface EMG Using Compact Electronic Board and Printed Matrix of Electrodes

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  • @INPROCEEDINGS{10.1007/978-3-030-69963-5_4,
        author={Tiziano Fapanni and Nicola Francesco Lopomo and Emilio Sardini and Mauro Serpelloni},
        title={Novel Wearable System for Surface EMG Using Compact Electronic Board and Printed Matrix of Electrodes},
        proceedings={IoT Technologies for HealthCare. 7th EAI International Conference, HealthyIoT 2020, Viana do Castelo, Portugal, December 3, 2020, Proceedings},
        proceedings_a={HEALTHYIOT},
        year={2021},
        month={7},
        keywords={Multielectrode EMG Wearable device Printed electrodes},
        doi={10.1007/978-3-030-69963-5_4}
    }
    
  • Tiziano Fapanni
    Nicola Francesco Lopomo
    Emilio Sardini
    Mauro Serpelloni
    Year: 2021
    Novel Wearable System for Surface EMG Using Compact Electronic Board and Printed Matrix of Electrodes
    HEALTHYIOT
    Springer
    DOI: 10.1007/978-3-030-69963-5_4
Tiziano Fapanni1, Nicola Francesco Lopomo1, Emilio Sardini1, Mauro Serpelloni1
  • 1: University of Brescia

Abstract

In recent years, the application of IoT for health purposes, including the intense use of wearable devices, has been considerably growing. Among the wearable devices, the systems for measuring EMG (electromyography) signals are highly investigated. The possibility of recording different signals in a multichannel approach can lead to reliable data that can be used to improve diagnostic techniques, analyze performance in sports professionals and perform remote rehabilitation. In this work, we describe the design of a novel wearable system for surface EMG using a compact electronic board and a printed matrix of electrodes. The whole system has an estimated maximum current absorption of 55 mA at 3.3 V. We focused on the subsystem integration and on the real-time data transmission through Bluetooth Low Energy (BLE) with a throughput of 28 kB/s with a success rate of 99%. Some preliminary data are collected on a healthy man’s arm to validate the design. The acquired data are then analyzed and processed to improve information quality and extract contraction patterns.