Publication

Smart Armband with Graphene Textile Electrodes for EMG-based Muscle Fatigue Monitoring

Ata Jedari Golparvar
2021
Conference Papers

Abstract

We report the successful acquisition of surface electromyography (sEMG) signals from an intelligent armband and its application in localized muscle fatigue monitoring with a costume-designed, small-scale front-end readout circuitry. The correlation coefficient of the graphene-based textile electrodes in benchmarking against Ag/AgCl electrodes is recorded to be similar to 97%. SNR values for Ag/AgCl and graphene textile electrodes were 15.9 dB and 14.3 dB, respectively. The muscle fatigue experiment was an isometric contraction conducted on the right biceps brachii of subjects. The recorded signal showed indications of localized muscle fatigue with an apparent increase in the total band energy and decreased instantaneous median frequency (IMF) with linear regression slopes of 0.0082 mV(2)/s and -0.19 Hz/s, respectively. Recorded promising results show that graphene textiles can be applied as practical sensing elements for wearable sEMG acquisition and enable novel applications such as muscle fatigue monitoring.

Official source

https://infoscience.epfl.ch/entities/publication/f8a4a770-8a2e-4b9a-8217-d74ce23a7258

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ata Jedari Golparvar
2021
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/f8a4a770-8a2e-4b9a-8217-d74ce23a7258

About this result

Related concepts (25)

Electromyography

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an electromyograph to produce a record called an electromyogram. An electromyograph detects the electric potential generated by muscle cells when these cells are electrically or neurologically activated. The signals can be analyzed to detect abnormalities, activation level, or recruitment order, or to analyze the biomechanics of human or animal movement.

Linear regression

In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.

Simple linear regression

In statistics, simple linear regression is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variable. The adjective simple refers to the fact that the outcome variable is related to a single predictor.

Related publications (28)

Novel theory and potential applications of central diastolic pressure decay time constant

Nikolaos Stergiopoulos, Patrick Segers, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Central aortic diastolic pressure decay time constant ( ) is according to the two-element Windkessel model equal to the product of total peripheral resistance (R) times total arterial compliance (C ). As such, it is related to arterial stiffness, which has ...

2024

Partial discharge localization in power transformer tanks using machine learning methods

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Nature Publishing Group2024

Weak correlations between visual abilities in healthy older adults, despite long-term performance stability

Michael Herzog, Simona Adele Garobbio

Using batteries of visual tests, most studies have found that there are only weak correlations between the performance levels of the tests. Factor analysis has confirmed these results. This means that a participant excelling in one test may rank low in ano ...

2024