MUSCLES’ CO-ACTIVATION IN A STATIONARY LIMB

ALTERES ACCORDING TO THE MOVEMENT OF OTHER

LIMB

Hossein Mousavi Hondori

, Ling Shih-Fu

and Reza Khosrowabaldi

School of Mechanical and Aerospace Engineering, Nanyang Technological University,50 Nanyang Avenue, Singapore

School of Computer Science and Engineering, Nanyang Technological University,50 Nanyang Avenue, Singapore

Keywords: Electromyography, Posture, Motor control, Muscle co-contraction.

Abstract: This paper reports an interesting phenomenon of observable muscle co-contraction in stationary limbs

according to the movement pattern in an oscillating limb. In the experiments the subject's electromyography

signals of biceps and triceps of both left and right arm are recorded. Two experiments were conducted

which are different in the posture of left and right arm. The first experiment is conducted when both

forearms are in upright posture. In the second experiment though, the right forearm is moving. It was

observed that the EMG of both biceps and triceps (i.e. co-activation) of the stationary limb follow that of the

opposite moving limb. The reason can be addressed by the necessity of stabilizing the stationary limb when

one executes motion in the counter limb. Moreover it can possibly be due to post-intention, pre-motion

brain activities that may fire the muscles of both limbs similarly.

1 INTRODUCTION

Hogan (Hogan, 1984) emphasized how antagonist

muscle’s co-activation in forearm’s upright posture

might help with the posture control. He showed that

the co-activation sets the mechanical impedance of

the elbow joint and postulated that this is what the

co-activation is meant to do. Later Burdet (Burdet et

al, 2001) proved that human learns to stabilize

unstable dynamics by optimizing mechanical

impedance. Conclusively, unstable tasks require

impedance optimization and the impedance is set by

co-activation of a pair of muscles (i.e. agonist and

antagonist). Is this co-activation only considerable in

unstable dynamics? A recent study (Darainy et al,

2008) on EMG patterns of dynamic learning of

stable tasks also reveals a considerable portion of

co-activation. Therefore, the CNS co-contracts the

antagonists not only in unstable dynamics, but also it

does in all tasks (Mousavi et al, 2009).

So far it was proven that this co-activation or

mechanical impedance adjustment is required from

the perspective of controlling one limb (Hogan,

1984) and (Burdet et al, 2001). However in this

paper we report a seemingly meaningful co-

activation in a stationary limb when the counter limb

is moving.

2 EXPERIMENTAL

OBSERVATION

The co-activation of antagonist muscle is linking and

relating to optimal impedance. Co-activation occurs

in both stable and unstable tasks regardless of the

fact that in stable tasks impedance is not as

necessary.

In an experimental study we recorded the EMG of

biceps and triceps of both arms during two tasks

including:

• Both forearms were in upright posture

(stationary)

• Left forearm is in upright posture

(stationary)Right forearm was moving

(flexor-extensor)

163

Mousavi Hondori H., Shih-Fu L. and Khosrowabadi R. (2010).

MUSCLES’ CO-ACTIVATION IN A STATIONARY LIMB ALTERES ACCORDING TO THE MOVEMENT OF OTHER LIMB.

In Proceedings of the Third International Conference on Biomedical Electronics and Devices, pages 163-165

DOI: 10.5220/0002698901630165

 SciTePress

Figure 1: a) upright stationary posture b) elbow flexion-

extension.

The EMG signal when both forearms are in upright

posture (Figure 1.a) is shown in Figure 2. In Figure

3, however, we find the same muscles’ EMG when

left arm remains upright stationary but the right

forearm moves according to Figure 1.b.

5 10 15 20 25

0.04

0.05

0.06

0.07

0.08

0.09

Time

(

sec

)

EMG (volt)

Bicepce-Left

Tricepce-Left

Bicepce-Right

Tricepce-Right

Figure 2: EMG of right and left arm when both arms are

upright stationary.

0 5 10 15 20 25 30 35 40 45

0.05

0.1

0.15

0.2

Time (sec)

EMG (volt)

Becepce-Left

Tricepce-Left

Bicepce-Right

Tricepce-Right

Figure 3: EMG when left arm remains upright stationary

and right arm moves.

Comparing the two situations we can observe that

the EMG in the stationary limb (left arm) is

considerably affected by that of the moving limb

moreover biceps and triceps of the stationary arm

are co-activated with almost the same amount.

3 HYPOTHESIZING

It can be postulated that the source of the co-

activation of the muscles in the stationary limb is to

feel secure about the performance of the moving

limb. If the stationary limb remains more stable

against possible perturbations, in case of

perturbation less correction and hence computation

would be needed. Then the task which is intended to

be done by the opposite limb is performed with more

comfort and concentration. In a word, we spend

more energy to fire the muscles of a stationary limb

so as to avoid excessive computing.

4 APPLICATION

Stroke patients mostly suffer from hemiplegia; they

lose some of the motor neurons with their associated

information that leave them with one side affected

and one side intact. Recovery rate has been reported

significant when a stroke patient move the healthy

limb and a robot imitating the motion apply the same

pattern to the affected limb (Burgar et al, 2000),

(Luft et al, 2004), and (Hesse et al, 2003). The

reason why this accelerates the recovery is not clear

yet. However, our finding might help address this

question.

We observed that when one moves a limb, the CNS

also sends some signals to the other limb even if it is

in a static posture. The signal might not be as

powerful to move it or more probably the signal

might not meant to move it; instead it could be to

make sure that the resting limb is going to stay in the

static posture.

Now let’s imagine that every time the stroke

subject’s arm is driven by the robot there have been

some signals to fire the muscles already. That can be

the reason why a stroke patient’s recovery process is

faster when they move undergo mirror image

movement enabler system.

ACKNOWLEDGEMENTS

Hereby we would like to acknowledge the School of

Mechanical and Aerospace Engineering at Nanyang

Technological University and the M&C Lab in

especial.

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