**2. Electromyography**

The hypothesis that muscles generate electricity was by Francesco Redi in 1666 due to the suspicion that the discharges of electric fish were of muscular origin.

Along with other scientific developments during the Renaissance, interest in the muscles also began to increase. Leonardo da Vinci (1452 - 1519), for example, devoted careful attention to muscles and their anatomical function by conducting dissections of cadavers [12]

The main objectives of the first scientific experiments on muscles were to understand their structure and function [12]. A number of scientists since studied muscle dynamics. Luigi Galvani presented the first study on the electrical properties of muscles and nerves in 1791. He termed this neuromuscular potential "Animal Electricity". This discovery was recognized as the starting point for neurophysiology. Thereafter, a growing number of studies have been developed in this field [11]. sEMG is a technique for recording and monitoring the electrical signals from muscle contractions. A major methodological problem for EMG is the frequent presence of artifacts or noise. Artifacts or noise are defined as information whose origin is distinct from the neuroelectrical muscle activity signal. Some examples of this include interference, heart rate, poor contact between the electrode and the skin, etc.[12].

Computational Intelligence in Electromyography Analysis – 392 A Perspective on Current Applications and Future Challenges

should be adjusted to 500-1000x [2,3,5].

low- and high-cut filter frequencies [28].

human movement [27].

**2. Electromyography** 

analysis.

The measurement that indicates the success of this separation is the common mode rejection ratio (CMRR), which is usually expressed in decibels (dB). The CMRR value of the

The sEMG equipment should be calibrated before recording signals. Calibration is important for fidelity, accuracy and reliability when reading the signal. The amplification factor is critical during the calibration process, since it is the ratio between the input voltage and that which comes out of the amplifier. The gain is selected according to the requirements of the type of experiment, the studied muscles, the type of electrodes involved and the planned use of the amplified signal. Whereas an sEMG signal has a maximum voluntary contraction amplitude not exceeding 5 millivolts (mV) peak-to-peak, the gain

During the mathematical processing of the sEMG signal, filters can be used to remove components that don't belong to the signal or components that are irrelevant for a given

The useful information in the sEMG signal is located in a particular frequency band (20-500 Hz), and is reduced by a filtering effect from the tissue located between the muscle fibers and the active sensing surface. The filter band corresponds to the frequency between the

Time-based signal processing can be carried out using a set of processing procedures intended to characterize the signal's curve and measure signal strength during the contraction. Signal processing applications in the time domain are widely used in areas such as neuromuscular coordination, motor control, the relationship between EMG and strength

This chapter will report, therefore, on the importance of sEMG with respect the dynamics of

The hypothesis that muscles generate electricity was by Francesco Redi in 1666 due to the

Along with other scientific developments during the Renaissance, interest in the muscles also began to increase. Leonardo da Vinci (1452 - 1519), for example, devoted careful attention to

The main objectives of the first scientific experiments on muscles were to understand their structure and function [12]. A number of scientists since studied muscle dynamics. Luigi Galvani presented the first study on the electrical properties of muscles and nerves in 1791. He termed this neuromuscular potential "Animal Electricity". This discovery was recognized as the starting point for neurophysiology. Thereafter, a growing number of studies have been developed in this field [11]. sEMG is a technique for recording and

and muscular coordination in the dynamics of human movement.

suspicion that the discharges of electric fish were of muscular origin.

muscles and their anatomical function by conducting dissections of cadavers [12]

differential amplifiers used in sEMG is on the order of 80 to 100 dB [3, 22, 24].

The presence of artifacts is difficult to avoid with this type of signal acquisition, since in order to amplify the signal, which is received in microvolts (μV), unwanted signals are also amplified and can compromise interpretation of the EMG signal. Thus, the signal-to-noise ratio has been a problem, and numerous studies have been undertaken to resolve EMG signal interpretation problems. After several attempts, a solution was found in the development of the differential amplifier [3] (ACIERNO, BARATTA & SOLOMONOW, 1995).

The signal amplifier is an electronic device that filters, amplifies and records bands of signals.

The initial problem with the amplifiers was that signal acquisition was dependent on the electrical resistance of the skin. Thus, in many studies skin resistance and temperature were initially monitored when the test was performed, conditions that made it difficult or impossible to reproduce and some EMG experiments [1].

Over time, corrections have been made to this system so that the amplifiers currently have high input impedance and attenuate noise levels, which allows the reproduction of experiments without interference with the results.

A main feature of this new generation of amplifiers is that they can amplify a particular type of biological signal independent of skin resistance [28]. The evolution of cables and connectors must also be considered in the development process of EMG acquisition equipment, since the type of conductive material and insulation system help minimize noise.

The main purpose of these developments is to help investigate and analyze human movement. The field of biomechanics is a practical example of the use of technological resources to interpret human movement [28].

Biomechanics can be defined generally as the study of the mechanics of living beings, or more specifically, the science that examines forces acting upon and within a structure and the biological effects produced by these forces [17]. Given the complex approach involved in biomechanics and human movement analysis [17], it is important to discuss the concepts, criteria and methods involved, focusing on the use of EMG for reliable interpretations.

EMG can be defined as the study of muscle function by analyzing the electrical signal generated during muscle contraction. Studying muscle function by means of EMG can be carried out under both normal and pathological conditions [12]. EMG has been used in important studies on muscle activity that have both qualitatively and quantitatively addressed the function of human movement. New information about muscle activity has been discovered as developments in processing and instrumentation have been applied to EMG [3,12, 15, 28] .

Application of Surface Electromyography in the Dynamics of Human Movement 395

Causative factors have an effect on the basic or elementary signal and are divided into extrinsic and intrinsic factors. Among the extrinsic factors are electrode configuration, the distance between the electrodes, the location of the electrodes over the motor point and the myotendonous junction, the location of the electrodes in relationship to the lateral border of the muscle and the orientation of the electrode in relation to muscle fibers. Intrinsic factors are the physiological, anatomical and biochemical characteristics of the muscle, such as the number of active motor units at the time a particular contraction occurs, the muscle fiber type, blood flow in the muscle, the fiber diameter, depth and location of the active fibers of the muscles in relation to the detection electrodes, the amount of tissue between the electrode and the muscle surface, as well as other factors such as the length of the

The intermediate factors are the physical and physiological phenomena that are influenced by one or more causative factors and, in turn, influence the determinants. Among this type are the detection electrode volume, the overlap of the action potential in the EMG signal, "cross-talk" with neighboring muscles, the conduction velocity of the action potential and the effect of spatial filtering. Since the determinant factors have a direct effect on the EMG signal and include the number of active motor units, the mechanical interaction between muscle fibers, the firing rate and the number of motor units detected, the amplitude, duration and shape of action potentials of motor units, as well as the recruitment and the stability of these units.

Soderberg and Cook described the limitations, collection methods and interpretation of electrical activity. Regarding the type of electrode, they believe that the sEMG can be used to

The normalization procedure is usually considered necessary for recording, quantifying and comparing the EMG data obtained from different individuals or the same individual on

Concern about the establishment of common standards for the collection, recording, analysis and interpretation of EMG signals has been expressed by a number of authors [12,27,28,], and more recently a practical guide for standardizing procedures to be used in EMG studies has been presented [1]. Thus, there is a tendency toward consensus among researchers on the use

Several studies [3, 5, 16, 27] have described the need to normalize the EMG signal amplitude when trying to make comparisons between different muscles, subjects, materials and days. This is due to the great variability observed in EMG tracings obtained from both different

The EMG signal can be rectified by mathematical processing or by the root mean square (RMS) of squared instantaneous values . This signal can be passed through a low-pass filter for a presentation wrap the curve. Signal processing can then be carried out in accordance with the specific aim of the work [2]. In general, it is necessary to normalize the EMG signal in order to minimize the differences between individuals [16], when not comparing pre-and

of appropriate instrumentation for collecting, recording and processing EMG signals.

analyze superficial muscles without causing discomfort to the volunteer [25].

depolarization zone and the ion flux across the membrane.

different days [27].

post-treatment.

individuals and different muscles.

However, the purpose of this study is to present and discuss the use of sEMG as a quantification tool for studying motor and functional rehabilitation and neurophysiological abnormalities in the nervous system in comparison with peripheral stimuli.

Many authors have used different procedures to analyze EMG signals, which impedes both the comparison and reproducibility of results obtained in laboratory experiments, although their experiments have been described in internationally recognized scientific journals.

Thus, although there is diversity in the procedures for both applying EMG and analyzing the signals, this technique for investigating myoelectrical activity can be used in many different areas of study for different research purposes.

It is important, therefore, to demonstrate some of the applications of EMG as a research tool as well as different methods of analyzing EMG signals to facilitate the design of future and to foster appropriate analysis methods for signal data.
