Analyzing surface EMG signals to determine relationship between jaw imbalance and arm strength loss

Khoa Truong Quang Dang; Hoa Le Minh; Hai Nguyen Thanh; Toi Vo Van

doi:10.1186/1475-925X-11-55

Research
Open Access
Published: 22 August 2012

Analyzing surface EMG signals to determine relationship between jaw imbalance and arm strength loss

Khoa Truong Quang Dang¹,
Hoa Le Minh¹,
Hai Nguyen Thanh¹ &
Toi Vo Van¹

BioMedical Engineering OnLinevolume 11, Article number: 55 (2012) | Download Citation

Abstract

Background

This study investigated the relationship between dental occlusion and arm strength; in particular, the imbalance in the jaw can cause loss in arm strength phenomenon. One of the goals of this study was to record the maximum forces that the subjects can resist against the pull-down force on their hands while biting a spacer of adjustable height on the right or left side of the jaw. Then EMG measurement was used to determine the EMG-Force relationship of the jaw, neck and arms muscles. This gave us useful insights on the arms strength loss due to the biomechanical effects of the imbalance in the jaw mechanism.

Methods

In this study to determine the effects of the imbalance in the jaw to the strength of the arms, we conducted experiments with a pool of 20 healthy subjects of both genders. The subjects were asked to resist a pull down force applied on the contralateral arm while biting on a firm spacer using one side of the jaw. Four different muscles – masseter muscles, deltoid muscles, bicep muscles and trapezoid muscles – were involved. Integrated EMG (iEMG) and Higuchi fractal dimension (HFD) were used to analyze the EMG signals.

Results

The results showed that (1) Imbalance in the jaw causes loss of arm strength contra-laterally; (2) The loss is approximately a linear function of the height of the spacers. Moreover, the iEMG showed the intensity of muscle activities decreased when the degrees of jaw imbalance increased (spacer thickness increased). In addition, the tendency of Higuchi fractal dimension decreased for all muscles.

Conclusions

This finding indicates that muscle fatigue and the decrease in muscle contraction level leads to the loss of arm strength.

Background

The relationship between the jaw muscles and other skeletal muscles are very important in explaining how and why the imbalance in the jaw causes loss in arm strength. Moreover, understanding this mechanism can bring many benefits for sports medicine by helping trainers design better mouth guards for athletes to improve their performance.

It has been reported that there is a strong relationship between the oral maxillofacial muscle, temporomandibular joint, and neck and arm muscles. Linderholm et al. [1] who investigated the relationship between bite force magnitude and forces produced by several skeletal muscle groups in children suggested that there was a relationship between bite forces and other forces, and the maximal bite force correlated with elbow flexion force and hand-grip force. Raadsheer et al. [2] found that the size of the jaw muscles was significantly related to the size of the limb muscles; however, maximal voluntary bite force moments were not significantly related to the moments of the arm flexion and leg extension forces.

Smith [3] performed a study to examine the effect of an increased vertical dimension of occlusion on isometric deltoid strength in 25 members of a professional football team with a variety of temporomandibular joint dysfunction, stomatognathic muscle and bite abnormalities. He concluded that there was a relationship between the jaws, posture, and the ability to the arm muscles to contract strongly. Forgione [4] analyzed the effect on isometric strength of biting on three intraoral devices and habitual occlusion using Nautilus lateral rise exercising device. They found that the average strength obtained with the elevated bite set to the functional criterion was significantly greater than in all other bite condition. It was concluded that a relationship does exist between bite and isometric strength.

In a study of finding a relationship between the height of bite plates and the strength of deltoid muscles, Chakfa et al. [5] performed experiments with 20 female subjects using the bite plates of adjusted heights of 2, 4, 6 and 12 mm. Each subject was seated on a dental chair with the arms extended to the side at the shoulder level and parallel to the floor. With or without introducing the bite plate in the subject’s mouth, the examiner applied a downward force on the wrist of the extended arm of the subject with a strain gauge while applying a stabilizing force on the contra lateral shoulder of the subject until the subject’s arm could no longer resist to the downward force. These researchers found that while increasing the height of the plate, the arm strength increased (from the strength without the plate of 6.9 kg on the right arm and 6.4 kg on the left arm) to a maximum (of 8.6 kg on either side of the arms) then decreased to 6.5 kg to the right and 6.3 kg to the left arm. Although these investigators did not indicate the height of the plate when the maximum strength occurred and simply reported that it depended on the subject, we deemed that they were either 4 or 8 mm.

In literature, the quantification of the jaw healthy and pain muscle activities during different jaw movements (opening, chewing, closing, etc.) were performed [6–9]. These studies showed a strong influence of the pain jaw muscles on the jaw movement patterns. Moreover, it has been showed that surface Electromyography (sEMG) technique is a good solution to measure and analyze, non-invasively, the jaw muscle activities.

In experiment, Ohtsuki [10] showed a decreasing voluntary isometric strength of the human arm under the condition of simultaneous bilateral exertion of contralateral corresponding muscles as compared to the unilateral condition. The decrease ratio of strength was 24.6 and 18.8% for the right and left for extension and 6.3 and 7.6% for the right and left for flexion. Integrated EMG showed the tendency comparable to the strength and high correlation was found between strength and integrated EMG. Recently, sEMG was used to predict the applied forces on human hands [11]. An artificial neural network was developed using frequency content of the sEMG signals. The investigators found a significant performance of the proposed model for predicting the loading forces based on the spectral features of the EMG signals.

Our hypothesis is that there is a balance between the left and the right arm. It is represented as the mechanical system in which there is a fulcrum at the center of this system (Figure 1). When the imbalance of the jaw occurs, it makes the arm loss its strength. It means that the fulcrum move toward to the one side of the system. The advantage of this hypothesis is to establish the modeling to explain for this phenomenon. However, it cannot explain the physiology in side of this phenomenon.

In order to understand more about the bite and arm strength phenomenon, EMG was used to study. Our hypothesis is that whenever the jaw imbalance occurs, the EMG signal of the arm will be reduced. According to the best of our knowledge, there are no studies related directly to the quantification of muscle activities in relation to the bite and the isometric arms strength by measuring the arm strengths as well as the face and arm muscles activities using EMG technique. EMG is a powerful technique that was used to investigate the muscles activities when the firm spacer was placed in the subject’s mouth to create the imbalance of the jaw and the loss of arm strength. This gave us useful insights on the arms strength loss due to the biomechanical effects of the imbalance in the jaw mechanism.

In addition to understanding the EMG signal, integrated EMG and fractal dimension were used to analyze the signals. These analytical methods allow us to demonstrate the muscle activities and muscle fatigue in time domain and the complexity of the signal. Particularly, Higuchi fractal dimension is very useful in characterized EMG signals.

Materials and methods

Physical modeling

In this study to determine the effects of the imbalance in the jaw to the strength of the arms, we conducted experiments with a pool of 20 (age: 19.8 ± 0.9 years old) and healthy subjects of both genders. All participants were healthy and showed no musculoskeletal or neurological restrictions or diseases. They had a complete dentition, i.e. no premolar or molar was missing in a quadrant. There were no signs of severe malocclusions or facial malformations. All subjects were not on any medication and had no complain of any kinds of muscle pains throughout the experiments.

Before the experiments, each subject filled out a questionnaire, which was kept confidential and included patient’s identification, age and gender. The tenets of the Declaration of Helsinki were followed; local Institutional Review Board approved the study and informed consent was obtained for all subjects.

The subjects were asked to stand with their arms and legs extended in frontal plan in such a way that the ratio subject intra-feet distance/ subject height equal 0.25 (Figure 2). This ratio was chosen based on the fact that many subjects felt comfortable and stable. The experimental protocol started with asking the subject hold the handle of a load which was at rest. Next at the warning signal the load was released at once; this generated a pull-down force on the subject’s arm. The subject must hold the load for a maximum of 15 seconds without moving his body. The pull-down force consisted of a load in kilogram that can be adjusted in the increment of 100 g and then converted into Newton. In these paradigms, the subject was asked to bite on a spacer using his premolar and molar teeth.

The subject held a spacer placed on one side of the jaw using premolar and molar teeth. The heights of the spacers were 0.6, 1.3 and 2.0 mm; however, they were applied in random order. Ten males (age 20 ± 0.9 years old) and 10 females (age: 19.8 ± 9.0 years old) participated.

We found that when the spacers were put in the left side of the jaw the loss of arm strength occurred on the right side of the arms and the strength of the arm on the same side intact. Similarly, when the spacers were put in the right side of the jaw the loss occurred on the left side of the arm while the strength of the arm on the same side was intact. This suggested that the bite imbalance causes a contralateral loss of strength in the arm (Figure 3).

In the process of understanding the origin of this phenomenon is muscular; we investigated the activities of muscles by using EMG. Ten male subjects participated in this investigation. The spacers had different heights of 2 mm and 3 mm and were applied in random order. The spacers were made out of a firm material to assume a good occlusal support. While the subject was biting on a spacer pull -down force was applied on the subject’s arm as aforementioned.

Myoelectric signals of jaw (masseter), neck (trapezoid) and arms (deltoid, brachiodiolis,) muscles were measured. The masseter was selected due to its main active role during biting at the temporomandibular (TM) joint. The concentric and eccentric contractions of the masseter create the biting motions as well as control the bite’s force. The trapezoid was selected due to its essential loading contribution in supporting the arm during persistent extension position. Arm extensors such as deltoid, brachiodiolis or extensor digitorum muscles were selected according to their role of support for maintaining the arm in extension under external loading conditions.

BIOPAC Systems Channel 1 was used to measure the activities of masseter muscle, channel 2 was used for trapezoid muscle, channel 3 was used for deltoid muscle, and channel 4 was used for branchi muscle. EMG (5- 500 Hz) was chosen to record EMG signal. The sampling rate was 1000/ second.The EMG measurement repeated twice for each experiment. The relaxation times within the experiments were 5 to 10 minutes. The recording time is 15 seconds in order to obtain the muscle fatigue [12, 13]

Paradigm 1: The maximum force that the subject can resist in 15 seconds was recorded before taking EMG measurements. From the initial position (0 mm, Fmax-40 N), external loading weight was added incrementally with Fmax -20 N and Fmax. Check EMG signal quality and data storage.

Paradigm 2: Perform variation in spacer thickness from 2 mm to 3 mm and execute step 1 for Fmax and Fmax -20 N.

Integrated EMG

To explain the fatigue of muscles by EMG signal in time domain, integrated EMG (iEMG) was calculated. Integrated EMG is the mathematical integration of rectified EMG signal. Simpson's rule was used to calculate iEMG. It is a method for numerical integration, the numerical approximation of definite integrals. Specifically, it is the following approximation:

Y = ∫ a b f x d x ≈ b − a 6 f a + 4 f a + b 2 + f b

(1)

In this formula (1), a and b are the unit spacing. f(a) and f(b) are the amplitudes of EMG signal at a and b. In fact, the iEMG was calculated as an approximation of the cumulative integral of the whole EMG signal amplitude during 15 seconds via the Simpson method with unit spacing.

The iEMG mean of ten subjects significantly increased with respect to the increasing of external loading (Figure 4). With a bigger applied force, the muscles strongly contracted in respect to iEMG.

Higuchi fractal dimension

Moreover, to understand the behavior of muscle through EMG signal, Higuchi fractal dimension was used. Higuchi is an efficient algorithm for measuring the fractal dimension of discrete time sequences [14]. Higuchi's algorithm calculates the fractal dimension from time series. Higuchi fractal dimension has already been used to analyze the complexity of surface EMG signal of the biceps [15].

Given a one dimensional time series X = x[1], x[2], …, x[N], the algorithm to compute the HFD can be described as follows [12]:

Form k new time series $X k m$ is defined by:

X k m = x m, x m + k, x m + 2 k, …, x m + int N − m k × k

(2)

where k and m are integers, and int(·) is the integer part of ·. k indicates the discrete time interval between points, whereas m = 1, 2, …, k represents the initial time value.

The length of each new time series can be defined as follows:

i = 1 int N − m / k x m + i k − x m + i − 1 × k) N − 1 / int N − m / k × k}

(3)

where N is length of the original time series X and (N − 1)/{int [(N − m)/k] × k} is a normalization factor.

Then, the length of the curve for the time interval k is defined as the average of the k values L(m,k), for m = 1, 2, …, k:

L k = 1 k × ∑ m = 1 k L m, k

(4)

Finally, when L(k) is plotted against 1/k on a double logarithmic scale, with k = 1, 2, …, k_max, the data is expected to fall on a straight line, with a slope equals to the fractal of X. Thus, Higuchi fractal dimension is defined as the slope of the line that fits the pairs {ln[L(k)], ln(1/k)} in a least-squares sense. A value of k_max = 10 was chosen for our study.