**4. Effect of muscle force on mean and median frequencies**

In order to make a reliably automate the muscle fatigue determination, the knowledge of the effects of time-varying factors on MNF and MDF is very important. Two time-varying factors, muscle force and muscle geometry, are the major factors due to the activities that involve dynamic muscle contractions (muscle force and/or geometry are changing) (Cechetto et al., 2001). It should be noted that the number and firing rate of active motor units (MUs) do not significantly affect MNF and MDF in both experimental and theoretical studies (Englehart & Parker, 1994; Solomonow et al., 1990).

The individual effects of muscle force and muscle geometry on MNF and MDF have been investigated in many previous researches. The effect of muscle force is discussed in this section, while the effect of muscle geometry will be discussed in the next section.

At present, the conflicting results of MNF and MDF with the muscle force effect exist in the literature. The difference in the experimental conditions for most of the studies is presented in Table 2. Maybe it is the possible reasons for the conflicting results of MNF and MDF on muscle force effect. It can be observed from the table that three different cases exist for the effect of muscle force on MNF and MDF.


Each of the first two cases is found in eight publications, while the third case exists only in two publications. However, the third case is found in the most recent study (Kaplanis et al., 2009) which used the EMG data recorded from 94 subjects (the largest EMG data compared with other publications).


Computational Intelligence in Electromyography Analysis – 202 A Perspective on Current Applications and Future Challenges

The next interested factor in Table 1 is the recording time. Because in the analysis of muscle fatigue, the EMG signals recorded during the fatigue of muscle are needed. Most of the studies used a level of force as the threshold to finish the recording. In other words, the EMG data have been recorded until the subject cannot maintain the required force level. However, several studies define the specific recording times that range from 30s to 170s.

Other factors are varied, such as the inter-electrode distance (5-75 mm), the levels of force (10-100%MVC), and the specification of filtering (1-1350 Hz). However, most of the studies paid more an interest to the study of biceps brachii muscle. The evaluating performance

In order to make a reliably automate the muscle fatigue determination, the knowledge of the effects of time-varying factors on MNF and MDF is very important. Two time-varying factors, muscle force and muscle geometry, are the major factors due to the activities that involve dynamic muscle contractions (muscle force and/or geometry are changing) (Cechetto et al., 2001). It should be noted that the number and firing rate of active motor units (MUs) do not significantly affect MNF and MDF in both experimental and theoretical

The individual effects of muscle force and muscle geometry on MNF and MDF have been investigated in many previous researches. The effect of muscle force is discussed in this

At present, the conflicting results of MNF and MDF with the muscle force effect exist in the literature. The difference in the experimental conditions for most of the studies is presented in Table 2. Maybe it is the possible reasons for the conflicting results of MNF and MDF on muscle force effect. It can be observed from the table that three different cases exist for the

• In the first case (CF1), MNF and MDF are unaffected or only weakly affected by changes in muscle force or load levels (Bilodeau et al., 1991; Cechetto et al., 2001; Hagberg & Ericsson, 1982; Inbar et al., 1986; Merletti et al., 1984; Petrofsky & Lind,

• In the second case (CF2), MNF and MDF increase as muscle force levels increase (Doheny et al., 2008; Gander & Hudgins, 1985; Gerdle et al., 1990; Hagberg & Ericsson, 1982; Hagberg & Hagberg, 1989; Moritani & Muro, 1987; Muro et al., 1982; Van Boxtel &

• In the third case (CF3), MNF and MDF decrease as muscle force levels increase

Each of the first two cases is found in eight publications, while the third case exists only in two publications. However, the third case is found in the most recent study (Kaplanis et al., 2009) which used the EMG data recorded from 94 subjects (the largest EMG data compared

section, while the effect of muscle geometry will be discussed in the next section.

between each pair of the methods and the muscles should be done in future study.

**4. Effect of muscle force on mean and median frequencies** 

studies (Englehart & Parker, 1994; Solomonow et al., 1990).

effect of muscle force on MNF and MDF.

Schomaker, 1984).

with other publications).

1980a, 1980b; Viitasalo & Komi, 1978).

(Kaplanis et al., 2009; Rainoldi et al., 1999).

**Table 2.** A survey of the experimental conditions in related works about the effect of muscle force on MNF and MDF in chronological order. Note that CF is one of three conflicting cases for muscle force effect; MA is maximum amplitude; FCR is flexor carpi radialis; BL is brachialis; FL is frontalis; CS is corrugator supercilii; ED is extensor digitorum; TZ is trapezius; TB is triceps brachii; AN is anconeus. There are several possible reasons for the conflicting results presented above.

Firstly, the different muscles studied have the different muscle fibre composition and distribution, and also the different tissue filter effects (Farina et al., 2002). The EMG power spectrum can be changed by both of which. Moreover, the difference of subject gender can produce the differences in fibre diameters and types (Sabbahi et al., 1981). Hence, the difference in the type and distribution of muscle fibres should be one of the major reasons, although the conflicting results exist in the same muscle i.e. the biceps brachii.

The Usefulness of Mean and Median Frequencies in Electromyography Analysis 205

not found for traditional MNF and MDF. This finding can be applied for the EMG signals recorded from the biceps brachii (Thongpanja et al., 2010, 2011) and also the flexor pollicis longus (Thongpanja et al., 2012). To easily observe and use in applications, five statistical variables consisting mean, median, variance, the RMS and kurtosis are used to apply with the selected efficient range of consecutive feature series. The results showed that the consistent results exist across the subjects (subject-independent) by applying mean and median variables (Thongpanja et al., 2011, 2013). The optimization of such techniques can be

(a) (b)

(c) (d)

**Figure 1.** (a, c, e) MNF and (b, d, f) MDF of EMG signals recorded at a constant joint angle (90º) as a function of muscle force (1-5 kg) for three subjects. (a-b) the first case in muscle force effect or CF1 (c-d) the second case in muscle force effect or CF2 (e-f) the third case in muscle force effect or CF3. The error

(e) (f)

Muscle geometry is another main factor that does significantly affect MNF and MDF. Generally, the effect of muscle geometry including electrode configuration, fibre diameter and subcutaneous tissue thickness has been evaluated by the resulting from changes in joint

**5. Effect of muscle geometry on mean and median frequencies** 

bars shown are given by the standard deviation of the mean value.

found more details in Thongpanja et al. (2013).

Secondly, the electrode locations over the muscle are different in the experiments. Komi and Viitasalo (1976) mentioned that MNF increase with muscle force levels unless the electrodes were located over the motor point area.

Thirdly, the inter-electrode distance (ID) of the bipolar surface electrodes may be the possible reason for the conflicting results. However, based on the observation throughout Table 2, the different inter-electrode distances are also found in the same case (all cases).

Fourthly, Bilodeau et al. (1992) found the different results between two genders for MDF but not for MNF. The difference in skinfold layer is the main contributor for the differences between two genders in that study. On the other hand, Kaplanis et al. (2009) found that no significant differences exist between values based on gender and age.

Other possible reasons are the limited and different number of subjects (i.e. 4–94 subjects), the level of force exhibited (i.e. %MVC or weight in kg), the range of joint angle exhibited (i.e. 0-150 degrees of extension), the difference in recording time (i.e. 1–30s), the existence of fatigue that resulting from the longer recording times (Lariviere et al., 2001), and the method of statistical analysis used.

To confirm the effect of muscle force on MNF and MDF, the relationship between MNF (and also MDF) and muscle force level was re-evaluated by the new EMG data (Phinyomark et al., 2012c). Figs. 1(a), 1(c) and 1(e) illustrate the relationship between muscle force level and MNF at the constant angle, while Figs. 1(b), 1(d) and 1(f) display the relationship between muscle load level and MDF at the same condition.

Three conflicting cases were found in our experiments for the effect of muscle force on MNF and MDF. The results are the subject-dependent. It is similar as the three conflicting cases which were found in the literature. To answer the question "why's the subject-dependent?", several related anthropometric variables obtained from the volunteers should be intended to find the possible reasons (Phinyomark et al., 2012c). The preliminary study showed that a number of anthropometric variables have a correlation with the conflicting results, such as standing height, hand breadth, body mass, and forward grip reach.

In order to modify MNF and MDF to have the consistent results (the same case), a modification of traditional MNF and MDF should be done. In one of our previous works (Thongpanja et al., 2010), we found that if a concept of using consecutive fast Fourier transform (FFT) is used instead of using a whole signal FFT, a certain relationship between MNF (and MDF) and muscle force level (the third case) can be found in the middle range of consecutive feature series for all trials and subjects, as an example is shown in Fig. 2. This is not found for traditional MNF and MDF. This finding can be applied for the EMG signals recorded from the biceps brachii (Thongpanja et al., 2010, 2011) and also the flexor pollicis longus (Thongpanja et al., 2012). To easily observe and use in applications, five statistical variables consisting mean, median, variance, the RMS and kurtosis are used to apply with the selected efficient range of consecutive feature series. The results showed that the consistent results exist across the subjects (subject-independent) by applying mean and median variables (Thongpanja et al., 2011, 2013). The optimization of such techniques can be found more details in Thongpanja et al. (2013).

Computational Intelligence in Electromyography Analysis – 204 A Perspective on Current Applications and Future Challenges

were located over the motor point area.

of statistical analysis used.

muscle load level and MDF at the same condition.

There are several possible reasons for the conflicting results presented above.

although the conflicting results exist in the same muscle i.e. the biceps brachii.

significant differences exist between values based on gender and age.

standing height, hand breadth, body mass, and forward grip reach.

Firstly, the different muscles studied have the different muscle fibre composition and distribution, and also the different tissue filter effects (Farina et al., 2002). The EMG power spectrum can be changed by both of which. Moreover, the difference of subject gender can produce the differences in fibre diameters and types (Sabbahi et al., 1981). Hence, the difference in the type and distribution of muscle fibres should be one of the major reasons,

Secondly, the electrode locations over the muscle are different in the experiments. Komi and Viitasalo (1976) mentioned that MNF increase with muscle force levels unless the electrodes

Thirdly, the inter-electrode distance (ID) of the bipolar surface electrodes may be the possible reason for the conflicting results. However, based on the observation throughout Table 2, the different inter-electrode distances are also found in the same case (all cases).

Fourthly, Bilodeau et al. (1992) found the different results between two genders for MDF but not for MNF. The difference in skinfold layer is the main contributor for the differences between two genders in that study. On the other hand, Kaplanis et al. (2009) found that no

Other possible reasons are the limited and different number of subjects (i.e. 4–94 subjects), the level of force exhibited (i.e. %MVC or weight in kg), the range of joint angle exhibited (i.e. 0-150 degrees of extension), the difference in recording time (i.e. 1–30s), the existence of fatigue that resulting from the longer recording times (Lariviere et al., 2001), and the method

To confirm the effect of muscle force on MNF and MDF, the relationship between MNF (and also MDF) and muscle force level was re-evaluated by the new EMG data (Phinyomark et al., 2012c). Figs. 1(a), 1(c) and 1(e) illustrate the relationship between muscle force level and MNF at the constant angle, while Figs. 1(b), 1(d) and 1(f) display the relationship between

Three conflicting cases were found in our experiments for the effect of muscle force on MNF and MDF. The results are the subject-dependent. It is similar as the three conflicting cases which were found in the literature. To answer the question "why's the subject-dependent?", several related anthropometric variables obtained from the volunteers should be intended to find the possible reasons (Phinyomark et al., 2012c). The preliminary study showed that a number of anthropometric variables have a correlation with the conflicting results, such as

In order to modify MNF and MDF to have the consistent results (the same case), a modification of traditional MNF and MDF should be done. In one of our previous works (Thongpanja et al., 2010), we found that if a concept of using consecutive fast Fourier transform (FFT) is used instead of using a whole signal FFT, a certain relationship between MNF (and MDF) and muscle force level (the third case) can be found in the middle range of consecutive feature series for all trials and subjects, as an example is shown in Fig. 2. This is

**Figure 1.** (a, c, e) MNF and (b, d, f) MDF of EMG signals recorded at a constant joint angle (90º) as a function of muscle force (1-5 kg) for three subjects. (a-b) the first case in muscle force effect or CF1 (c-d) the second case in muscle force effect or CF2 (e-f) the third case in muscle force effect or CF3. The error bars shown are given by the standard deviation of the mean value.

#### **5. Effect of muscle geometry on mean and median frequencies**

Muscle geometry is another main factor that does significantly affect MNF and MDF. Generally, the effect of muscle geometry including electrode configuration, fibre diameter and subcutaneous tissue thickness has been evaluated by the resulting from changes in joint

The Usefulness of Mean and Median Frequencies in Electromyography Analysis 207


50º, 70º, 90º, 110º, 130º

45º, 60º, 75º, 90º, 105º, 120º 0.1-3000 2

20-450 2

Thirdly, it can be observed that the frequency band of EMG signals does not affect MNF and

Reference *N* Age Muscle ID Force levels Joint angles Filter CG

60%MVC

**Table 3.** A survey of the experimental conditions in related works about the effect of muscle geometry (joint angle) on MNF and MDF in chronological order. Note that CF is one of the two conflicting cases

Due to the incompleteness of captured information in the literature, in future study, a request to complete all interested information to the first author or the corresponding author

As the possible reasons mentioned above that are inconclusive, the main reason for the conflicting results should be the changes of muscle force with the muscle length. The same weight was used at all angles in most of the studies, therefore the changes in MNF and MDF were not due to changes in the muscle length, or joint angle, only but also to changes in the muscle force. In future work, EMG signals should be measured from the muscle under a

To confirm the effect of muscle geometry on MNF and MDF, the relationship between MNF (and also MDF) and elbow joint angle was re-evaluated by the similar EMG data as used in Section 4. Figs. 3(a), 3(c) and 3(e) illustrate the relationship between joint angle and MNF at the constant load, while Figs. 3(b), 3(d) and 3(f) display the relationship between joint angle

Three conflicting cases were found in our experiments for the effect of elbow joint angle on MNF and MDF. The results are the subject-dependent. It is similar as the three conflicting cases which were found in the effect of muscle force on MNF and MDF. In the third case or CG3, MNF (and MDF) increases as muscle length or joint angle (degrees of flexion) increases, as can be observed in Figs. 3(e) and 3(f). In future work, several related anthropometric variables obtained from the volunteers should be intended to find the possible reasons, as

10 10, 20, 30, 40, 50, 60, 70%MVC

12 - BB - - 30º-150º - 2

10 - TA - - 0º, 15º, 30º, 45º - 2

15 24±3 BB 30 7kg 0º-140º 15-450 2

MDF.

Gerdle et al. (1988)

Moritani et al.

Merletti et al.

Cechetto et al.

Doheny et al.

should be done.

(1988)

(1993)

Potvin (1997)

(2001)

(2008)

23 20-30 TZ,DT,

12 24.8±2.8 BB,BR,

TB

for the muscle geometry effect; DT is Deltoid; IF is infraspinatus.

constant force (varying loads) while joint angles varied.

and MDF at the same condition.

mentioned in Section 4.

IF,BB

12 31.1±10 BB 40 20, 30, 40, 50,

**Figure 2.** The consecutive MDF feature series computed from the EMG signals recorded from the biceps brachii during dynamic muscle contractions (0-150 degrees of extension). Four load levels are applied: 2, 4, 6 and 8 kg. The FFT is computed using the window size of 512 samples and window overlapping of 64 samples. Note that the second case exists in the beginning and the end ranges (the dashed line boxes) and the third case exists in the middle range (the solid line box).

angle or muscle length (Merletti et al., 1999). Changing in such factors can vary producing a time-varying EMG spectrum. In the literature, two different cases exist for the effect of muscle geometry on MNF and MDF.

In the first case (CG1), MNF and MDF are unaffected by changes in joint angle or muscle length (Sato, 1976). A number of the studies showed no significant change in the power spectrum of EMG signals acquired from the biceps brachii under constant load while joint angle varied. It is also found for the EMG signals recorded from the trapezius, deltoid and the infraspinatus (Gerdle et al., 1988).

In the second case (CG2), MNF (and MDF) increases as muscle length or joint angle (degrees of extension) decreases (Inbar et al., 1987; Shankar et al., 1989). This case exists in most of the studies for EMG signals acquired from the biceps brachii (Cechetto et al., 2001; Doheny et al., 2008; Moritani et al., 1988; Okada, 1987; Potvin, 1997), and is also found for EMG signals acquired from other muscles, such as the tibialis anterior (Merletti et al., 1993), the brachioradialis (Doheny et al., 2008), and the triceps brachii (Doheny et al., 2008; Okada, 1987). The second case, however, is found frequently in the recent studies compared to the first case.

The experimental conditions for several studies are summarized in Table 3. The difference in the experimental conditions may be the reasons for the conflicting results presented in the literature.

Firstly, muscle types and electrode locations over the muscle are different in the experiments. Doheny et al. (2008) mentioned that this factor is one of the reasons for the second case effect. However, the conflicting results are also found in the same muscle i.e. the biceps brachii.

Secondly, Cechetto et al. (2001) proposed that the inter-electrode distance (ID) may be the possible reason for the conflicting results. However, based on the observation through Table 3, three different inter-electrode distances (10, 30 and 40 mm) are found in the same case (the second case).


Thirdly, it can be observed that the frequency band of EMG signals does not affect MNF and MDF.

Computational Intelligence in Electromyography Analysis – 206 A Perspective on Current Applications and Future Challenges

muscle geometry on MNF and MDF.

the infraspinatus (Gerdle et al., 1988).

literature.

second case).

**Figure 2.** The consecutive MDF feature series computed from the EMG signals recorded from the biceps brachii during dynamic muscle contractions (0-150 degrees of extension). Four load levels are applied: 2, 4, 6 and 8 kg. The FFT is computed using the window size of 512 samples and window overlapping of 64 samples. Note that the second case exists in the beginning and the end ranges (the

angle or muscle length (Merletti et al., 1999). Changing in such factors can vary producing a time-varying EMG spectrum. In the literature, two different cases exist for the effect of

In the first case (CG1), MNF and MDF are unaffected by changes in joint angle or muscle length (Sato, 1976). A number of the studies showed no significant change in the power spectrum of EMG signals acquired from the biceps brachii under constant load while joint angle varied. It is also found for the EMG signals recorded from the trapezius, deltoid and

In the second case (CG2), MNF (and MDF) increases as muscle length or joint angle (degrees of extension) decreases (Inbar et al., 1987; Shankar et al., 1989). This case exists in most of the studies for EMG signals acquired from the biceps brachii (Cechetto et al., 2001; Doheny et al., 2008; Moritani et al., 1988; Okada, 1987; Potvin, 1997), and is also found for EMG signals acquired from other muscles, such as the tibialis anterior (Merletti et al., 1993), the brachioradialis (Doheny et al., 2008), and the triceps brachii (Doheny et al., 2008; Okada, 1987). The second case, however, is found frequently in the recent studies compared to the first case. The experimental conditions for several studies are summarized in Table 3. The difference in the experimental conditions may be the reasons for the conflicting results presented in the

Firstly, muscle types and electrode locations over the muscle are different in the experiments. Doheny et al. (2008) mentioned that this factor is one of the reasons for the second case effect. However, the conflicting results are also found in the same muscle i.e. the biceps brachii.

Secondly, Cechetto et al. (2001) proposed that the inter-electrode distance (ID) may be the possible reason for the conflicting results. However, based on the observation through Table 3, three different inter-electrode distances (10, 30 and 40 mm) are found in the same case (the

dashed line boxes) and the third case exists in the middle range (the solid line box).

**Table 3.** A survey of the experimental conditions in related works about the effect of muscle geometry (joint angle) on MNF and MDF in chronological order. Note that CF is one of the two conflicting cases for the muscle geometry effect; DT is Deltoid; IF is infraspinatus.

Due to the incompleteness of captured information in the literature, in future study, a request to complete all interested information to the first author or the corresponding author should be done.

As the possible reasons mentioned above that are inconclusive, the main reason for the conflicting results should be the changes of muscle force with the muscle length. The same weight was used at all angles in most of the studies, therefore the changes in MNF and MDF were not due to changes in the muscle length, or joint angle, only but also to changes in the muscle force. In future work, EMG signals should be measured from the muscle under a constant force (varying loads) while joint angles varied.

To confirm the effect of muscle geometry on MNF and MDF, the relationship between MNF (and also MDF) and elbow joint angle was re-evaluated by the similar EMG data as used in Section 4. Figs. 3(a), 3(c) and 3(e) illustrate the relationship between joint angle and MNF at the constant load, while Figs. 3(b), 3(d) and 3(f) display the relationship between joint angle and MDF at the same condition.

Three conflicting cases were found in our experiments for the effect of elbow joint angle on MNF and MDF. The results are the subject-dependent. It is similar as the three conflicting cases which were found in the effect of muscle force on MNF and MDF. In the third case or CG3, MNF (and MDF) increases as muscle length or joint angle (degrees of flexion) increases, as can be observed in Figs. 3(e) and 3(f). In future work, several related anthropometric variables obtained from the volunteers should be intended to find the possible reasons, as mentioned in Section 4.

The Usefulness of Mean and Median Frequencies in Electromyography Analysis 209

the narrow joint angles should decrease, while the values of MNF and MDF that are computed from the normalized EMG signals measured at wide joint angles should be same as the old one. It can be observed throughout Figs. 5(c) and 5(d). As a result, the consistent results should exist across the subjects (subject-independent). The consistent case is the second case. In future

(a) (b)

(c) (d)

(a) (b)

work, the evaluation of this finding should be done with the large EMG data set.

**Figure 4.** Samples of raw EMG signals recorded from the biceps brachii at (a) 30º and (b) 150º of extension in time-domain, and their power spectrum at (c) 30º and (d) 150º of extension. Note that a

**Figure 5.** Samples of normalized EMG signals recorded from the biceps brachii at (a) 30º and (b) 150º of extension in time-domain, and their power spectrum at (c) 30º and (d) 150º of extension. Note that a

(c) (d)

constant force (3kg) is performed for each angle.

constant force (3kg) is performed for each angle.

**Figure 3.** (a, c, e) MNF and (b, d, f) MDF of EMG signals recorded at a constant muscle force (3 kg) as a function of elbow joint angles (30-150 degrees of extension) for three subjects. (a-b) the first case in muscle geometry effect or CG1 (c-d) the second case in muscle geometry effect or CG2 (e-f) the third case in muscle geometry effect or CG3. The error bars shown are given by the standard deviation of the mean value.

In order to modify MNF and MDF to have the consistent results (the same case), a modification of traditional MNF and MDF should be done. Figs. 4(a) and 4(b) show the sample in time-domain of EMG signals measured at the same constant force level with the elbow joint angles at 30º and 150º of extension, respectively. It was found that at narrow elbow joint angles, i.e. 30º of extension, the distribution of positive and negative amplitudes is asymmetry, but at wide elbow joint angles, i.e. 150º of extension, the distribution of positive and negative amplitude is symmetry. The power spectrum of each of the samples is respectively shown in Figs. 4(c) and 4(d). Based on the observation of the distribution, if the EMG signal is normalized by setting the highest value to 1 and the lowest value to -1 for an asymmetric signal, the EMG baseline should be shifted away from the true zero line, as can be observed in Fig. 5(a). On the other hand, the EMG baseline should not be shifted away from the true zero line in the case of normalized symmetric signal, as can be observed in Fig. 5(b). Hence, the values of MNF and MDF that are calculated from the normalized EMG signals measured at the narrow joint angles should decrease, while the values of MNF and MDF that are computed from the normalized EMG signals measured at wide joint angles should be same as the old one. It can be observed throughout Figs. 5(c) and 5(d). As a result, the consistent results should exist across the subjects (subject-independent). The consistent case is the second case. In future work, the evaluation of this finding should be done with the large EMG data set.

Computational Intelligence in Electromyography Analysis – 208 A Perspective on Current Applications and Future Challenges

**Figure 3.** (a, c, e) MNF and (b, d, f) MDF of EMG signals recorded at a constant muscle force (3 kg) as a function of elbow joint angles (30-150 degrees of extension) for three subjects. (a-b) the first case in muscle geometry effect or CG1 (c-d) the second case in muscle geometry effect or CG2 (e-f) the third case in muscle geometry effect or CG3. The error bars shown are given by the standard deviation of the mean value.

(e) (f)

(a) (b)

(c) (d)

In order to modify MNF and MDF to have the consistent results (the same case), a modification of traditional MNF and MDF should be done. Figs. 4(a) and 4(b) show the sample in time-domain of EMG signals measured at the same constant force level with the elbow joint angles at 30º and 150º of extension, respectively. It was found that at narrow elbow joint angles, i.e. 30º of extension, the distribution of positive and negative amplitudes is asymmetry, but at wide elbow joint angles, i.e. 150º of extension, the distribution of positive and negative amplitude is symmetry. The power spectrum of each of the samples is respectively shown in Figs. 4(c) and 4(d). Based on the observation of the distribution, if the EMG signal is normalized by setting the highest value to 1 and the lowest value to -1 for an asymmetric signal, the EMG baseline should be shifted away from the true zero line, as can be observed in Fig. 5(a). On the other hand, the EMG baseline should not be shifted away from the true zero line in the case of normalized symmetric signal, as can be observed in Fig. 5(b). Hence, the values of MNF and MDF that are calculated from the normalized EMG signals measured at

**Figure 4.** Samples of raw EMG signals recorded from the biceps brachii at (a) 30º and (b) 150º of extension in time-domain, and their power spectrum at (c) 30º and (d) 150º of extension. Note that a constant force (3kg) is performed for each angle.

**Figure 5.** Samples of normalized EMG signals recorded from the biceps brachii at (a) 30º and (b) 150º of extension in time-domain, and their power spectrum at (c) 30º and (d) 150º of extension. Note that a constant force (3kg) is performed for each angle.
