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Updated: Jul 9, 2026

Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
Published on: July 27, 2015
Toward the development of predictive equations of back muscle capacity based on frequency- and temporal-domain
Christian Larivière1, Denis Gravel, Denis Gagnon
1Safety Ergonomics Program, Occupational Health and Safety Research Institute Robert-Sauvé, Quebec, Canada. larchr@irsst.qc.ca
Background Context:
Back muscles capacity is impaired in chronic low back pain patients but no motivation-free test exists to measure it. A functional endurance test (FET) was used to assess capacity of back muscles using surface electromyographic (EMG) indices as outcome measures.
Purpose:
The main objective of the present study was to explore the possibility of combining different types of EMG indices to predict absolute endurance and strength.
Study Design/Setting:
A cross-sectional study using a repeated measures design in laboratory setting.
Methods:
Healthy subjects (44 men and 29 women) performed maximal voluntary contractions (Strength criterion: extension moment at L5/S1) and a fatigue test involving intermittent static extension contractions to exhaustion (Tend endurance criterion: time to reach exhaustion). Surface EMG signals were collected from four pairs of back muscles. From the first 5 minutes (women) or 10 minutes (men) of EMG data, frequency- and temporal-domain analyses were applied to compute various EMG indices.
Results:
Strength values ranged from 153 to 508Nm, whereas Tend values ranged from 3 to 57 minutes across the subjects. Gender-specific multiple regression equations were developed, using the retained EMG indices from the four electrode sites, to predict Tend (men: R(2)=0.76, error=9%; women: R(2)=0.70, error=17%) and Strength (men: R(2)=0.72, error=9%; women: R(2)=0.25, error=13%).
Conclusions:
It appears to be possible to predict the capacity of back muscles using an intermittent and time-limited (submaximal) fatigue task. Frequency- and temporal-domain EMG indices were shown to provide complementary information in this respect. This FET has potential to better infer back muscle capacity for realistic occupational tasks because more specific muscle fatigue mechanisms are involved.
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