EMG SIGNAL BEHAVIOR IN HUMAN VASTUS

EMG SIGNAL BEHAVIOR IN HUMAN

VASTUS LATERALlS, TIBIALlS

ANTERIOR ANO SOLEUS MUSCLES OURING

Cláudia Tarragô CandoUi"',

L- __

FATIGUE

de Souza Castro', Eduardo Mendonça Scheeren', Ana Maria Steffens Pressi', Jefferson Fagundes Loss', Marco Aurélio Vaz', Antônio Carlos Stringhini Guimarães' 1. Laboratório de Pesquisa do Exercício, Escola de Educação Física, Universidade Federal do Rio Grande do Sul - UFRGS

A

Flávio Antônio

2. Curso de Educação Física, Universidade

Foram comparados

do Vale do Rio dos Sinos - UNISINOS

sinais eletromiográflcos

buição de fibras, durante um protocolo

(EMG) de músculos. com supostas diferenças na distri-

de fadiga. utilizando-se

regressão linear entre o tempo de

contração e a mediana da freQüênCia (MF) e os valores root mean sQuare (RMS). Participaram deste estudo sete indivíduos

do sexo masculino

sinais EMG foram obtidos intermediária)

sem prévios comprometimentos

dos músculos vasto lateral (contração

e sóleo (contração

lenta) com eletrodos

neuro-musculares.

rápida). tibial anterior

de superfície

na configuração

Os

(contração bipolar. Os

torQues de extensores de joelho. de nexores dorsais e de nexores plantares foram obtidos a partir de um dinamômetro

isocinético.

O protocolo

de avaliação consistiu de três contrações voluntárias máxi-

mas isométricas (CVM) e de uma contração isométrica a 70% da maior CVM até a exaustão (protocolo de fadiga). a Qual foi interrompida

Quando o valor de torQ!Je atingia um nível de 50% da CVM. Os

valores de MF e de RMS foram calculados a partir de janelas consecutivas de I s de duração durante o protocolo

de fadiga. Regressões lineares foram aplicadas entre o tempo de contração e os valores

de MF e RMS em todos os músculos a fim de se verificar

o comportamento

domínios da freQüênCia e do tempo. Para testar a normalidade

do sinal EMG nos

dos valores de inclinação obtidos. foi

aplicado um teste de Shapiro-Wilk.

Análise de variância de um fator foi utilizada para avaliar possíveis

diferenças entre o comportamento

dos três músculos. O nível de signincância adotado foi 0.05 para

todas as análises estatísticas. Os músculos apresentaram uma diminuição o protocolo

de fadiga, conforme a literatura.

inclinação foi encontrada

(p

=

0.569).

nos valores de MF durante

mas nenhuma diferença estatística entre os valores de

Em relação aos valores de inclinação

RMS. também nenhuma diferença estatística foi encontrada (p

=

0.698).

obtidos dos valores

Embora os valores de MF

e de RMS pareçam ser sensíveis à fadiga muscular. regressões lineares não foram capazes de avaliar diferenças entre músculos de diferentes composições Kn"OR"

Fadiga muscular; Controle

neuromuscular;

de fibras.

Eletromiografla.

INTRODUCTION Skeletal muscle fatigue is a continuous process that starts at the beginning of the neuromuscular activity anel might be responsible for changes in the electrical tr,msmission, excitation-contraction coupling anel other steps of the contractile process (BASNIAJAN& DE LUCA 1985, CLAMANN 1990, BIG1..AND-RlTCHIEet aI. 1992). ln aelelition to the elecrease in the mechanical response, electrical aspects of the neuromuscular function anel fiber type elistribution are factors relateel to muscle fatigue (HÀKKINEN & KOMI 1986). There is a consensus in the literature that the factors responsible for

Year 5, nO 9, Novel1lber

2004

initiating fatigue start immeeliately after the beginning of exercise (l3IGLAND-RITCHIE 1992). The electromyographic (EMG) signal obtaineel eluring voluntary contractions is a collection of action potentials from many motor units firing at elifferent frequencies. Any interpretation of the raw EMG signal in relation to muscle force proeluction, muscle activation, or muscle fatigue state is elifficult prior to EMG signal processing. This signal processing may be performeel in the time ar in the frequency elomain (HERZOG et aI. 1994).

Brazi!ian Jouma! o/ Biol1lec!wnics

15

FATIGL'E

J;-'"JJl',\1A:'\

\'A:3TC:3

LATERAUS,

TJBL\U:3

A;-':TE~IO~

A:'\n

'::OLEt;.::

The analysis of the EMG signal in the frequency domain has been widely used in the study of muscle behavior during sustained contractions to assess local muscle fatigue. Factors which may affect the electromyographic power spectnlI11 are: changes in the action potential characteristics (amplitude and form), firing rates, muscle temperature, additional recruitment of motor units during fatigue and leveI of voluntary effort. The median frequency (MF) has been proposed as a sensitive index to evaluate fatigue (HÀGG 1992). There are evidences that continuous high intensity activity is followed by progressive decrease in the activation of the pool of motor neurons (BIGLAND-RITCHIE et a!. 1983), Many studies indicate that during fatigue due to a sustained contraction, there is a decrease in the MF of the EMG signal (KADEFORS et a!. 1968, LINSTROM et a!. 1977, VAZ et a!. 1996). The magnitude of the EMG signal (measured by the root mean square -I{MS- value) might be used as well in the study of muscle fatigue (HERZOG et a!. 1994). However, a gap appears to exist in the literature with respect to the behavior of the I{jVISof the EMG signal eluring sustaineel contractions in elifferent muscles. VAZ et a!. (1996) showeel evidences that the RMS values increaseel for the knee extensor muscles during a fatigue protocol when the leveI of voluntaty effort was maintaineel at 70% of the maximal voluntary contraction - (MVC), whereas it elecreased when this leveI of effort coulel no longer be

maintaineel.

These results were obtaineel from the

rectus femoris anel vastus lateralis muscles, which are composeel primarily of fast twitch fibers (70.5% anel 67.3%, respectively]OHNSON et a!. 1973). It is possible, however, that muscles with different fiber type (01' motor unit) elistribution show a elistinct behavior when the RMS of the EMG signal is analyzeel. In other worels, one might expect that a muscle with a higher percentage of fast twitch fibers shoulel show a steeper increase in the RMS values with fatigue when compareel to a muscle with a lower percentage of fast twitch fibers. The purpose of this stuely was to eletermine the behavior of EMG in the frequency (MF) anel time (RMS) domains, eluring muscle fatigue, in muscles with elifferent fiber type composition, accoreling to ]OHNSON et a!. (1973), namely vastus lateralis (67.3% af fast twitch fiber type), tibialis anterior (26.6% af fast twitch fiber type) anel soleus (13.6% of fast twitch fiber type). As the vastus lateralis anel tibialis anterior muscles shoulel be less resistant to fatigue than the soleus muscle, two preelictions have been formulateel: eluring an isometric fatigue protocal up to exhaustion, (1) vastus lateralis muscle shoulel show a more pronounceel nega tive slope in a linear regression for MF values than both tibialis anterior anel soleus muscles, (2) the vastus lateralis muscle shoulel show a more pronounceel positive slope in a linear regression for the RMS values than the tibialis anterior anel soleus muscles.

METHODS

Seven healthy male subjects (age = 18-24 years of age) gave their written informeel cansent to participate in the stuely after aI! proceelures were Glrefully explaineel to them. Knee extensor, elorsal and plantar flexor torques were obtained by using an isokinetic Cybex (Norm) elynamameter (Lumex & Co., Ronkonkoma, New York, USA), whereas EMG signals were obtaineel by using an 8-channel EMG system (Bortec Eletronics lnc., Calgary, Canaela). Bipolar surface electroeles (Agi AgCI; with a 2.2 cm eliameter; with elouble siele sticker) were placeel an the elistal thirel of the vastus lateralis, tibialis anterior and soleus muscles, anel a grounel electrode was placed on the tibia. The skin unelerneath the recoreling electroeles was prepared for EMG recoreling by using stanelarel proceelures (MERLETI'I 1999, SODERBERG & KNUTSON 2000). EMG signals passeei through a pre-amplifier 10cateellO cm away from the electrodes, anel then passeei through a main amplifier. 16

Revista Brasileira de Biomccânica

Knee extensor, elorsal anel plantar flexor tarques anel EMG signal were eligitizeel at a frequency of 2000 Hz using an analog-to-eligital boa rei (CODAS, Dataq Instruments, Inc., Akron, USA) anel storeel on a Pentium (200 MHz) personal computeI' for further analysis. Previous to the test, aI! subjects warmeel up by using a bicycle ergometer for a periael of 5 minutes. The right knee extensa r torques were abtained at an angle af 45 degrees af knee flexion, anel 90 elegrees of hip tlexion. The elorsiflexion torque at an ankle angle of 20 elegrees of plantar tlexion, anel the plantar flexor torque af the right limb were obtaineel at an ankle angle of 10 elegrees of elorsiflexion (O elegree = anatomical 01' neutral pasition). Three maximal isometric voluntary cantractions (MVC) were performeel for a perioel of two seconels each. Two minutes were given between trials ta avoiel fatigue. The largest tarque value abtaineel from these trials was useel to calcula te 70% af MVC. The

Ano 5, nO 9, Novembro 2004

C.

T CA~J)OTTI,

F. A. S. CASTRO, E. M. SCIIEERE~,

subjects performed the fatigue test, which consisted in maintaining an isometric contraction at 70% of MVC until the torque values dropped to the leveI of 50% of MVC, when the test was interrupted. Visual feedback was provided to the subjects during the fatigue test through an oscilloscope to help the subjects in keeping with the desired torque leveI. The processing of the EMG signal and torque data was done by using the Data Analysis System - SAD [(version 2.61.07mp, 2002) software (www.ufrgs.br/lmm)]. The torque data were processed by using a 10 Hz cut-off frequency low-pass filter and the EMG signals were band-passed filtered 00 Hz - 1000 Hz). The MF of the power spectrum was obtained by using a Fast Fourier Transform (FFT) algorithm (2048 points), and calculatecl for consecu-

A. M. S. PRESSI, J. F. Loss, M. A. VAZ & A. C. S. Gl:IMARAES

tive winclows of one seconcl each throughout the fatigue test, at a levei of 70% of MVC. RMS values were also obtainecl from consecutive windows of one second from the raw EMG signals. Linear regression was appliecl to the resultant MF and RMS values obtainecl from the fatigue test, and their respective slopes were obtainecl. The slopes thus calculated were used to evaluate the behavior of the EMG signal in the frequency ancl time domains. A Shapiro-Wilk test was applied to the slope values to test for a normal distribution of the clata. One-way analysis of variance was used to evaluate possible differences in the behavior of the three muscles. A 0.05 leveI of significance was adopted for ali statistical analyses.

RESUlTS

The contraction times for the 70% MVC fatigue protocol for the knee extensor, plantar flexor and dorsal flexor musc\es were 30.30 ± 8.06 s, 40.2 ± 16.4 s and of 38.5 ± 9.8 s, respectively. The mean and standarcl deviation of the slopes of the linear regression of the MF -MFand of the RIvlSvalues, for ali muscles, can be observed in TableRMS 1. Although no significant differences were found among the slope of the linear regressions of the MF values (p = 0.569), these results show more pronounced negative slopes for the tibialis anterior compared to the vastus lateralis

and to the soleus musc\es, for the MF values found. 1n relation to the RIvISvalues, no significant differences were found among the slope of the linear regressions (p = 0.698), although these results show

-

90

70 50 'N ;S 10 60 O 50 ~

~ 0.4

:;;

40 20 30

f4-·tt·.•.~.

•

00 0.6

(a)

70

-0.6235

±

0.4441

Table I. Mean and standard deviation of the slopes of the linear regressions of the median frequency (MF) and of the RMS values of the vastus lateralis, tibialis anterior and of lhe soleus muscles.

0.7

0.3 0.1 0.2

t •.•..• ~ • • ~•.•.~•• t ~ •••

60

Soleu5 -0.7045 0.0052 0.0026 0.4407 0.0038 0.0044 -0.8588 ±anterior ±±0.0032 0.0031 0.3517 Vastu5±± lareralisTibialis

• -• 50 70

60

.*." Time

(5)

P5j

(b)

80

80

90

Time (5) Figure

I.

150

Linear regressian af ane representative subjecl: (a) MF and (b) RMS values af the vastus lateralis muscle during the entire fatigue protocol.

..

125~'" ~1·111 .•.• 'N

I

100

-

75

~

50

•••

• ~

.

0.3

•

•

•• '*' t•• ~~ ~ I•••••• .~ •.•• ~

:[

.......~-~~~

0.2

(a)

~

••....••.......•..•...

....

V)

.

0.1 .) ••••••

25 O~, 115

125

135 Time (5)

Figure

, 145

o 155

I

I

115

125

I 135

145

155

Time (5)

2. Linear regression of one representative subject: (a) MF and (b) RMS values of the tibialis anterior muscle during the entire fatigue protocol.

Year 5, nO 9, November 2004

Brazi/ian jouTna/ 0/ Biomechanics

17

FATIGI 'E 1:-;111',\IA:-; \'ASTI 's L\rE~\LlS,

TIBIALlS A:\rERI0R

A:-;IJ S,'LEI'S

200 0,3

•••

150

N' ~

N'

~

100

u...

0.2

• • r,

•

f

•..•.

t .•...•. • .......• • .•..

• .••.

•.•......•.••••••••••...•

~ ••

,.+

+

u...

~

~

50 o I 120

I

I

130

140

I 150

I 160

Time (5) Figure].

0,1 0,0 120

130

140

150

160

Time (5)

Linear regressian af ane representative subject: (a) MF and (b) RMS values af lhe saleus muscle during the entire fatigue prataco!.

more pronounced posltlve slopes for the vastus lateralis compared to the tibialis anterior and soleus muscles, for the RMS values found. The results 01' one representative subject can be visualized in Fig-

ures 1, 2 and 3, respectively, vastus lateralis, tibialis anterior and soleus muscles, \Vhich show the linear regression 01' the MF anel 01' the RMS values.

DISCUSSION

Electromyogrdphic signals have been widely used to direct and study skeletal muscle fatigue. Among the several EMG parameters used to evaluate fatigue, the MF values 01' the power spectrum in the frequency elomain and the RMS values in the time domain seems to be the most frequently used (BASMAjIAN & DE LUCA 1985). It is well known that, during fatiguing contractíons, there is a shift 01' the frequency component 01' the EMG signal towards lower frequencies, as observed by monitoring the MF (NAGAT'A et aI. 1990, VAZ et a!. 1996). Theoretical and experimental evielence indicates a strong correlation and/or proportional relation between the mean or median frequencies 01' the power spectrum and muscle fiber coneluction velocity (LINDSTROM et aI. 1970 anel 1977, STULEN & DE LUCA 1981). Skeletal muscles are composeel 01' different fiber 01' a spccific fiber type in types. The predominance a muscle gives the muscle its mechanical characteristics in terms 01' force proeluction. Therefore, the force-time histoty 01' muscles with different fiber type elistribution shoulel be different. In other worels, the mechanical anel electrical behavior 01' muscles sllOulel be relateel to their structural as well as mechanical characteristics eluring fatiguing contractions, The purpose 01' this study was to eletermine the EMG signal behavior 01' muscles with assumed different fiber type composition during a fatigue protocol, analyzed by the slopes 01' linear regressions between the time anel MF and/or RMS values. It was assumeel that the vastus lateralis, a muscle \Vith larger percentage 01' fast twitch fibers (when compared to tibialis anterior and soleus muscles) shoulel show a more pronounced negative slope (preeliction 1). The resulL,>did not SUPPOlt this prediction, as the slopes 01' 18

Revista Brasileira de Biomecânica

the linear regression for the MF in ali the three muscles during the entire fatigue protocol were similar (Table 1, Figures 1, 2 and 3). ll1e expecteel elecr~L