This protocol describes the electromyographic fatigue threshold which demarcates between nonfatiguing and fatiguing exercise workloads. This information could be used to develop a more individualized training program.
Theoretically, the electromyographic (EMG) fatigue threshold is the exercise intensity an individual can maintain indefinitely without the need to recruit more motor units which is associated with an increase in the EMG amplitude. Although different protocols have been used to estimate the EMG fatigue threshold they require multiple visits which are impractical for a clinical setting. Here, we present a protocol for estimating the EMG fatigue threshold for cycle ergometry which requires a single visit. This protocol is simple, convenient, and completed within 15-20 min, therefore, has the potential to be translated into a tool that clinicians can use in exercise prescription.
Surface electromyography (EMG) is a noninvasive approach of studying motor unit recruitment during isometric1-3, isokinetic4-6, or continuous7-10 muscle action. The amplitude of the EMG signal represents muscle activation which consists of the number of motor units activated, the firing rate of the motor units, or both11. The concept of the EMG fatigue threshold is used to indicate the highest workload in which an individual can exercise indefinitely without an increase in EMG amplitude8.
It is important to briefly discussion the origin of the EMG fatigue threshold. The original study by deVries et al.12 involved a protocol that consisted of multiple (usually 3 to 4) discontinuous work bouts, where the EMG amplitude was plotted versus time for each work bout. The power output was then plotted versus the slope coefficients from the EMG amplitude versus time relationship, and then extrapolated to zero slope (the y-intercept)12. The authors12 originally termed that protocol the physical working capacity at the fatigue threshold (PWCFT). In a another study, deVries et al.13 used discontinuous work bouts, but used linear regression to find the first power output that resulted in a significant slope for the EMG amplitude versus time relationship. The authors13 also termed that protocol the PWCFT, creating some confusion in the literature. In a subsequent article, deVries et al.14 modified their earlier protocol13 and developed a continuous incremental protocol. The EMG amplitude was plotted against time for each power output and the PWCFT was defined as the average of the highest power output that resulted in no change in EMG amplitude over time and the lowest power output that resulted in an increase in EMG amplitude over time14.
It should be noted that the term PWC was originally introduced in the late 1950s15,16 and is synonymous with a plethora of literature (past, present, and across different countries) examining aerobic capacity at a given workload17. Moreover, the term is used in the ergonomic and industrial literature which focus on day-to-day productivity of workers performing repetitive action during 8 hour work days such as individuals in an assembly plant18.
The term EMG fatigue threshold was initially used by Matsumoto and colleagues19 after they modified the deVries12 protocol where the power output versus slope coefficients of the EMG amplitude versus time relationship are plotted and extrapolated to the point of zero slope. More recently, Guffey et al.20 and Briscoe et al.8 used the method of deVries et al.14 and the terminology of Matsumoto et al.19 to operationally define the EMG fatigue threshold. Moving forward, we recommend that the term EMG fatigue threshold be used. Thus, the EMG amplitude versus time relationship is plotted for each power output and then analyzed using linear regression analyses (Figure 1). To estimate the EMG fatigue threshold, the highest power output with a non-significant (p >0.05) slope and the lowest power output with a significant (p <0.05) slope is identified and then the average is calculated14. This protocol is simple, convenient, and completed within 15-20 min. Moreover, the incremental rate can be modulated based on the individual’s level of habitual physical activity, and therefore has potential applications in clinical settings.
All procedures were approved by the University Institutional Review Board for Human Subjects.
1. Preparation of the Participant’s Leg
2. Measurement of Leg for Electrode Placement
3. Placement of the EMG Electrodes
4. Checking the EMG Signal
5. Setting-up the Cycle Ergometer
6. Performing the EMG Fatigue Threshold Protocol
7. Processing the EMG Signal
8. Determining the EMG Fatigue Threshold for Each Participant
As shown in Figure 1, for a single participant, each power output that is completed has six data points that represent the EMG amplitude for the vastus lateralis muscle. Therefore, in this example, the highest power output with a non-significant (p >0.05) slope is 200 watts, whereas the lowest power output with a significant (p <0.05) slope is 225 W. Therefore, for this participant the EMG fatigue threshold is 213 W. Once the EMG fatigue threshold is determined for each participant then inferential statistics can be performed.
Figure 1: Representative results for a single participant. Linear regression was performed for the EMG amplitude versus time relationship for each power output. The power output indicated by the red arrow (200 W) is the highest power output with a non-significant (p >0.05) slope, whereas the power output indicated by the green arrow (225 W) is the lowest power output with a significant (p <0.05) slope. The average of these two power outputs equal 213 W, which is the EMGFT.
Figure 2: Depiction of the electrode arrangement for the vastus lateralis muscle. In addition, we have provided a visual of where the EMG electrodes are placed for the rectus femoris and vastus medialis muscles. Specific directions for EMG electrode placed can be found on the following website: http://www.seniam.org.
We here present a method for determining neuromuscular fatigue in the quadriceps femoris muscles for dynamic exercise. This method provides a straightforward and non-invasive approach to using surface EMG. Moreover, the versatility of this method is that researchers can adapt it to other modes of exercise such as the treadmill20.
Theoretically, for intensities at or below the EMG fatigue threshold the participant should be able to sustain the exercise workbout indefinitely12,13. Briscoe et al.8 validated the EMG fatigue threshold for cycle ergometry. On separate occasions each participant exercised at 70%, 100%, and 130% of their EMG fatigue threshold. The authors found that for 70% and 100% of the EMG fatigue threshold participants did not have increased EMG amplitude during the exercise workload8. For the workload at 130% of EMG fatigue threshold, however, participants exhibited a significant increase in EMG amplitude8. Briscoe et al.8 concluded that the EMG fatigue threshold for cycle ergometry was a valid protocol to determine neuromuscular fatigue during continuous exercise.
With regard to critical steps in the protocol and troubleshooting consider the following. If there is too much noise in the EMG signal when performing step 4.1.2 then first check the connection between the EMG electrodes and the device recording the signal. Oftentimes, the EMG leads may not be connected properly to the EMG electrode. Second, the areas where the electrodes are placed need to be free of any hair and feel smooth to the touch rather than rough (i.e., shaving stubbles). Therefore, ensure that all hair is thoroughly removed in locations where the EMG electrode will be placed. Also, it is important to clean the area once the abrading is completed. Again, the goal is to have a clean and smooth surface. Third, the center area of the EMG electrode should not be dry and if so use conductance gel (such as those used for ultrasound) as a supplement. Make sure to use the gel sparingly, because excess gel may interfere with the adhesiveness of the EMG electrode. Taken together, these items are common culprits which increase the noise in the EMG signal and thus contaminating the data.
Although the EMGFT protocol is versatile there are potential limitations to its application in a clinical setting. For example, certain clinical populations may not tolerate the testing protocol. That is, while the increase in workload can be modified (i.e., 5 W instead of 25 W per stage) patients with severe respiratory and/or cardiac illnesses may prematurely fatigue during the initial stages of the test. Another potential limitation is that the quadriceps femoris muscles are all activated during cycle ergometry; however, the EMG signal is being recorded from only one of these muscles. To date, no studies have determined the EMGFT across the three superficial quadriceps femoris muscles for cycle ergometry to identify whether there are differences between muscles.
In summary, the method of estimating the EMG fatigue threshold from a single incremental exercise test is a useful tool for assessing neuromuscular fatigue during dynamic exercise. Moreover, this test provides an objective method of determine of the efficacy of various interventions that attenuate muscle fatigue.
The authors have nothing to disclose.
This project was funded by, in part, by start-up funds from Wayne State University to M.H. Malek.
839 E Monark cycle ergometer | Monark Exercise AB | 839 E | |
Heart rate monitor | Polar | Polar H1 | |
Laptop | Dell Inspiron | varies | any laptop computer with USB slots should work. |
EMG amplifiers | BioPac Systems, Inc. | 100B | 100C are the latest version |
Disposable EMG electrodes | BioPac Systems, Inc. | EL-500 | |
Sandpaper | Home Depot | 9 in. x 11 in. 60 Grit course no-slip grip Advanced Sandpaper (3-Pack) |