Tutorial. Surface EMG detection,conditioning and pre-processing: Best practices |
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| Affiliation: | 1. Neuromuscular Research Centre & Technology, Department of Bioengineering, Imperial College London, SW7 2AZ London, UK;2. Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, Italy;1. Brock University, St. Catharines, ON, Canada;2. Worcester Polytechnic Institute, Worcester, MA, USA;3. Wilfrid Laurier University, Waterloo, ON, Canada;1. Graduate program in Rehabilitation Science, University of British Columbia, Vancouver, Canada;2. Laboratorio di Ingegneria del Sistema Neuromuscolare (LISiN), Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Italy;3. Escola de Educação Física e Desportos, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil;4. Department of Physical Therapy, University of British Columbia, Vancouver, Canada |
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| Abstract: | This tutorial is aimed primarily to non-engineers, using or planning to use surface electromyography (sEMG) as an assessment tool for muscle evaluation in the prevention, monitoring, assessment and rehabilitation fields. The main purpose is to explain basic concepts related to: (a) signal detection (electrodes, electrode–skin interface, noise, ECG and power line interference), (b) basic signal properties, such as amplitude and bandwidth, (c) parameters of the front-end amplifier (input impedance, noise, CMRR, bandwidth, etc.), (d) techniques for interference and artifact reduction, (e) signal filtering, (f) sampling and (g) A/D conversion, These concepts are addressed and discussed, with examples.The second purpose is to outline best practices and provide general guidelines for proper signal detection, conditioning and A/D conversion, aimed to clinical operators and biomedical engineers. Issues related to the sEMG origin and to electrode size, interelectrode distance and location, have been discussed in a previous tutorial. Issues related to signal processing for information extraction will be discussed in a subsequent tutorial. |
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| Keywords: | Tutorial Teaching Electromyography sEMG detection Physiotherapy Kinesiology Electrodes Signal conditioning sEMG amplifier Electrode–skin impedance Interference reduction Noise reduction Artifact reduction sEMG acquisition |
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