Temperature Influences at the Myoelectric Level in the Upper Extremities of the Human Body

Efrén V. Herrera1, *, Edgar M. Vela2, *, Victor A. Arce1, Katherine G. Molina1, Nathaly S. Sánchez1, Paúl J. Daza1, Luis E. Herrera1, Douglas A. Plaza1
1 Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería en Electricidad y Computación, FIEC, Guayaquil, Ecuador
2 Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, SUPSI, Manno, Switzerland

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© 2020 Herrera et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Innovative Technologies Manno, Switzerland, University of Applied Sciences and Arts of Southern Switzerland, SUPSI, Manno, Switzerland; Tel: +593-042269823; E-mail:



Nowadays, surface electromyography (sEMG) signals are used for a variety of medical interaction applications along with hardware and software interfaces. These signals require advanced techniques with different approaches that enable processing the sEMG signals acquired in the upper limb muscles of a person.


The purpose of this article is to analyze the sEMG signals of the upper limb of a person exposed to temperature changes to envisage its behavior and its nature. The anticipated diagnostic is a key factor in the health field. Therefore, it is very important to develop more precise methods and techniques. For the present study, a heat chamber that allows controlling the temperature of the area where the patient rests his or her hand was designed and implemented. With the appropriate hardware interfaces, the sEMG signals of the hand were registered with MatLab/Simulink software for further analysis. The article explains the analysis and develops knowledge, through a probabilistic approach regarding the change in the sEMG signals.


The results show that there is an activity in the sEMG signal response due to changes in temperature and it is feasible to detect them using the proposed method.


This finding contributes to research that seeks to characterize temperature’s effect in the biomedical field.

Keywords: Surface electromyography signals (sEMG), Signal analysis, Upper limbs, Temperature changes, Probabilistic approach, Biomedical field.