Literature DB >> 22613823

The effect of perspiration on the sEMG amplitude and power spectrum.

Mohammad Abdoli-Eramaki1, Caroline Damecour, John Christenson, Joan Stevenson.   

Abstract

Sweat accumulation underneath surface EMG (sEMG) electrodes is a common problem in workplace studies which compromises electrode adherence to the skin as well as signal fidelity. In this study, the effect of sweat accumulation on signal amplitude and mean frequency (MF) was examined to determine if the sEMG signal becomes altered through the sweat layer and whether this effect can be avoided by interrupting the pool of sweat using a thin strip of medical adhesive between the electrode snaps. Nine males performed a maximum, isometric contraction of their right quadriceps as sEMG was collected. Skin conditions under the electrode were dry and wet in incremental layers of 0.02 mm of artificial sweat. The results demonstrated that sweat accumulation under sEMG electrodes dampens the amplitude of the EMG signal in a predictable way (r = .88 and .97 for double and single snap electrodes, respectively) with almost 2% and 3% deterioration for every 0.02 mm of sweat depending on the type of electrode used. The medical adhesive proved to be highly effective at preventing amplitude deterioration indicating that signal shunting can be prevented. MF was not influenced by sweat accumulation even under the extreme wet condition.
Copyright © 2012 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2012        PMID: 22613823     DOI: 10.1016/j.jelekin.2012.04.009

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  11 in total

1.  Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity.

Authors:  Minjae Kim; Taewan Kim; Dong Sung Kim; Wan Kyun Chung
Journal:  Sensors (Basel)       Date:  2015-07-06       Impact factor: 3.576

2.  Arrhythmia Evaluation in Wearable ECG Devices.

Authors:  Muammar Sadrawi; Chien-Hung Lin; Yin-Tsong Lin; Yita Hsieh; Chia-Chun Kuo; Jen Chien Chien; Koichi Haraikawa; Maysam F Abbod; Jiann-Shing Shieh
Journal:  Sensors (Basel)       Date:  2017-10-25       Impact factor: 3.576

3.  Whole Body Awareness for Controlling a Robotic Transfemoral Prosthesis.

Authors:  Andrea Parri; Elena Martini; Joost Geeroms; Louis Flynn; Guido Pasquini; Simona Crea; Raffaele Molino Lova; Dirk Lefeber; Roman Kamnik; Marko Munih; Nicola Vitiello
Journal:  Front Neurorobot       Date:  2017-05-30       Impact factor: 2.650

4.  Dry Electrodes for Surface Electromyography Based on Architectured Titanium Thin Films.

Authors:  Marco S Rodrigues; Patrique Fiedler; Nora Küchler; Rui P Domingues; Cláudia Lopes; Joel Borges; Jens Haueisen; Filipe Vaz
Journal:  Materials (Basel)       Date:  2020-05-05       Impact factor: 3.623

5.  Segmenting Mechanomyography Measures of Muscle Activity Phases Using Inertial Data.

Authors:  Richard B Woodward; Maria J Stokes; Sandra J Shefelbine; Ravi Vaidyanathan
Journal:  Sci Rep       Date:  2019-04-03       Impact factor: 4.379

6.  Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue.

Authors:  Joe Sanford; Rita Patterson; Dan O Popa
Journal:  J Rehabil Assist Technol Eng       Date:  2017-08-01

7.  Systematic reduction of leg muscle activity throughout a standard assessment of running footwear.

Authors:  Maurice Mohr; Vinzenz von Tscharner; Sandro Nigg; Benno M Nigg
Journal:  J Sport Health Sci       Date:  2021-01-13       Impact factor: 13.077

8.  Comparison of six electromyography acquisition setups on hand movement classification tasks.

Authors:  Stefano Pizzolato; Luca Tagliapietra; Matteo Cognolato; Monica Reggiani; Henning Müller; Manfredo Atzori
Journal:  PLoS One       Date:  2017-10-12       Impact factor: 3.240

9.  Ultra-conformal drawn-on-skin electronics for multifunctional motion artifact-free sensing and point-of-care treatment.

Authors:  Faheem Ershad; Anish Thukral; Jiping Yue; Phillip Comeaux; Yuntao Lu; Hyunseok Shim; Kyoseung Sim; Nam-In Kim; Zhoulyu Rao; Ross Guevara; Luis Contreras; Fengjiao Pan; Yongcao Zhang; Ying-Shi Guan; Pinyi Yang; Xu Wang; Peng Wang; Xiaoyang Wu; Cunjiang Yu
Journal:  Nat Commun       Date:  2020-07-30       Impact factor: 14.919

10.  Acute high-intensity and moderate-intensity interval exercise do not change corticospinal excitability in low fit, young adults.

Authors:  Jenin El-Sayes; Claudia V Turco; Lauren E Skelly; Mitchell B Locke; Martin J Gibala; Aimee J Nelson
Journal:  PLoS One       Date:  2020-01-24       Impact factor: 3.240

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