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Abstract

Objective:

The authors developed a function to quantify fatigue in multiple shoulder muscles by generating a single score using relative changes in EMG amplitude and frequency over time.

Background:

Evaluating both frequency and amplitude components of the electromyographic signal provides a more complete evaluation of muscle fatigue than either variable alone; however, little effort has been made to combine time and frequency domains for the evaluation of myoelectric fatigue.

Method:

Surface EMG was measured from 14 shoulder muscles while participants performed simulated, repetitive work tasks until exhaustion. Each 60-s work cycle consisted of four tasks (dynamic push, dynamic pull, static drill, static force target matching task) scaled to participants’ anthropometrics and strength. The function was generated to calculate a multimuscle fatigue score (MMFS) based on changes in EMG frequency, amplitude, and the number of muscles showing signs of myoelectric fatigue (increase in EMG amplitude; decrease in EMG frequency).

Results:

The function was evaluated through changes in MMFS over time: first (31.8 ± 14.6), middle (47.6 ± 25.3), last (58.6 ± 35.5) reference exertions (p < .05). The evaluation of the relationships between MMFS and changes in strength (r = −0.510) and MMFS and perceived fatigue (RPF) (r = 0.298) showed significant relationships over time (p < .05). MMFS scores increased over time (p < .05) with significant relationships between MMFS and strength changes and RPF (p < .05).

Conclusion and application:

The MMFS allows for comparisons between workplace tasks, which can aid in workplace design to mitigate the development of fatigue.

Keywords

quantification fatigue electromyography shoulder muscles

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References

Al-Mulla

M. R.

Sepulveda

Colley

. (2011). A review of non-invasive techniques to detect and predict localised muscle fatigue. Sensors, 11(4), 3545–3594.

Boettcher

C. E.

Ginn

K. A.

Cathers

(2008). Standard maximum isometric voluntary contraction tests for normalizing shoulder muscle EMG. Journal of Orthopaedic Research, 26(12), 1591–1597.

Bonato

Gogliato

Knaflitz

(1996). Analysis of myoelectric signals recorded during dynamic contraction: A time-frequency approach to assessing muscle fatigue. IEEE Engineering in Medicine and Biology, 15(6), 102–111.

De Luca

C. J

. (1979). Physiology of mathematics of myoelectric signals. IEEE Transactions on Biomedical Engineering BME 26(6), 313–325.

Dideriksen

J. L.

Farina

Enoka

R. M.

(2010). Influence of fatigue on the simulated relation between the amplitude of the surface electromyogram and muscle force. Philosophical Transactions of the Royal Society A, 368(1920), 2765–2781.

Ekstrom

R. A.

Soderberg

G. L.

Donatelli

R. A.

(2005). Normalization procedures using maximum voluntary isometric contractions for the serratus anterior and trapezius muscles during surface EMG analysis. Journal of Electromyography and Kinesiology, 15(4), 418-428.

Enoka

R. M.

Duchateau

(2008). Muscle fatigue: What, why and how it influences muscle function. Journal of Physiology, 586(1), 11–23.

Gerdle

Larsson

Karlsson

(2000). Criterion validation of surface EMG variables as fatigue indicators using peak torque. A study of repetitive maximum isokinetic knee extensions. Journal of Electromyography and Kinesiology, 10(4), 225–232.

Gonzalez-Izal

Malanda

Gorostiaga

Izquierdo

(2012). Electromyographic models to assess muscle fatigue. Journal of Electromyography and Kinesiology, 22(4), 501–512.

10.

Haddad

Mirka

G. A.

(2013). Trunk muscle fatigue and its implications in EMG-assisted biomechanical modeling. International Journal of Industrial Ergonomics, 43, 425–429.

11.

Hagberg

(1981). Muscular endurance and surface electromyogram in isometric and dynamic exercise. American Physiological Society, 51(1), 1–7.

12.

Hodder

J. N.

Keir

P. J.

(2013). Obtaining maximum muscle excitation for normalizing shoulder electromyography in dynamic contraction. Journal of Electromyography and Kinesiology, 23(5), 1166–1173.

13.

Luttmann

Jäger

Laurig

(2000). Electromyographical indication of muscular fatigue in occupational field studies. International Journal of Industrial Ergonomics, 25(6), 645–660.

14.

MacIssac

D. T.

Parker

P. A.

Englechart

K. B.

Rogers

D. R.

(2006). Fatigue estimation with a multivariable myoelectric mapping function. IEEE Transactions on Biomedical Engineering, 53(4), 694–700.

15.

McDonald

A. C.

Sonne

M. W. L.

Keir

P. J.

(2017). Optimized maximum voluntary exertion protocol for normalizing shoulder muscle activity. International Biomechanics, 4(1), 9–16.

16.

McDonald

A. C.

Tse

C. T. F.

Keir

P. J.

(2016). Adaptations to isolated shoulder fatigue during simulated repetitive work. Part II: Recovery. Journal of Electromyography and Kinesiology, 29, 42–49.

17.

Micklewright

Gibson

S. T. C.

Gladwell

Salman

A. A.

(2017). Development and validity of the rating-of-fatigue scale. Journal of Sports Medicine, 47(11), 2375–2393.

18.

Navaneethakrishna

Ramakrishnan

(2014). Multiscale feature based analysis of surface EMG signals under fatigue and non-fatigue conditions. IEEE Xplore, 4627–4630.

19.

Potvin

J. R.

Bent

L. R.

(1997). A validation of techniques using surface EMG signals from dynamic contractions to quantify muscle fatigue during repetitive tasks. Journal of Electromyography and Kinesiology, 7(2), 131–139.

20.

Roger

D. R.

MacIsaac

D. T.

(2010). Training a multivariable myoelectric mapping function to estimate fatigue. Journal of Electromyography and Kinesiology, 20(5), 953–960.

21.

Tse

C. T. F.

McDonald

A. C.

Keir

P. J.

(2016). Adaptations to isolated shoulder fatigue during simulated repetitive work. Part I: Fatigue. Journal of Electromyography and Kinesiology, 29, 34–41.

22.

Waite

D. L.

Brookham

R. L.

Dickerson

C. R.

(2010). On the suitability of using surface electrode placements to estimate muscle activity of the rotator cuff as recorded by intramuscular electrodes. Journal of Electromyography and Kinesiology, 20(5), 903–911.

Using EMG Amplitude and Frequency to Calculate a Multimuscle Fatigue Score and Evaluate Global Shoulder Fatigue

Abstract

Objective:

Background:

Method:

Results:

Conclusion and application:

Keywords

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References