Estimating Surface EMG Activity of Human Upper Arm Muscles Using InterCriteria Analysis

Electromyography (EMG) is a widely used method for estimating muscle activity and could help in understanding how muscles interact with each other and affect human movement control. To detect muscle interactions during elbow flexion and extension, a recently developed InterCriteria Analysis (ICrA) based on the mathematical formalisms of index matrices and intuitionistic fuzzy sets is applied. ICrA has had numerous implementations in different fields, including biomedicine and quality of life; however, this is the first time the approach has been used for establishing muscle interactions. Six human upper arm large surface muscles or parts of muscles responsible for flexion and extension in shoulder and elbow joints were selected. Surface EMG signals were recorded from four one-joint (pars clavicularis and pars spinata of m. deltoideus [DELcla and DELspi, respectively], m. brachialis [BRA], and m. anconeus [ANC]) and two two-joint (m. biceps brachii [BIC] and m. triceps brachii-caput longum [TRI]) muscles. The outcomes from ten healthy subjects performing flexion and extension movements in the sagittal plane at four speeds with and without additional load are implemented in this study. When ICrA was applied to examine the two different movements, the BIC–BRA muscle interaction was distinguished during flexion. On the other hand, when the ten subjects were observed, four interacting muscle pairs, namely DELcla-DELspi, BIC-TRI, BIC-BRA, and TRI-BRA, were detected. The results obtained after the ICrA application confirmed the expectations that the investigated muscles contribute differently to the human upper arm movements when the flexion and extension velocities are changed, or a load is added

Changes in EMG Activities of Upper Arm Muscles and in Shoulder Joint Angles in Post-stroke Patients

The aim of the paper is to compare the electromyographic signals (EMGs) and the joint angles of the affected upper limb muscles of stroke survivors to those of their non-affected limb as well as to those of the dominant and the non-dominant limbs of healthy volunteers. Twenty five volunteers, ten post-stroke survivors and fifteen healthy subjects as control group, participated in the experiments. EMGs of muscles of the upper limbs and two angles in the shoulder joint were registered and processed during three static and two dynamic tasks. The results showed a big variability of all investigated parameters (mean and median frequencies, ranges of motions, maximal normalized EMGs) both for the patients and for the healthy subjects, for right and for left hand. This makes difficult a deduction of definitive conclusions about the changes in motor control of the upper limbs due to stroke. Moreover, natural differences in motor control exist for dominant and non-dominant limb. On the whole, the power-frequency analysis and the relevant statistical analysis indicated that the muscles of the affected limb had lower median frequencies than those of the healthy limb. Examination of full elbow flexions in the sagittal plane showed that the range of the motion in the shoulder joint of both limbs of the patients increased when compared to the healthy subjects and that this increase was larger for the affected limb. The post-stroke survivors used more of their muscle power although no increased co-contraction was observed

Estimation of contractile parameters of successive twitches in unfused tetanic contractions of single motor units – A proof-of-concept study using ultrafast ultrasound imaging in vivo

During a voluntary contraction, motor units (MUs) fire a train of action potentials, causing summation of the twitch forces, resulting in fused or unfused tetanus. Twitches have been important in studying whole-muscle contractile properties and differentiation between MU types. However, there are still knowledge gaps concerning the voluntary force generation mechanisms. Current methods rely on the spike-triggered averaging technique, which cannot track changes in successive twitches’ properties in response to individual neural firings. This study proposes a method that estimates successive twitches contractile parameters of single MUs during low force voluntary isometric contractions in human biceps brachii. We used a previously developed ultrafast ultrasound imaging method to estimate unfused tetanic activity signals of single MUs. A twitch decomposition model was used to decompose unfused tetanic activity signals into individual twitches. This study found that the contractile parameters varied within and across MUs. There was an association between the inter-spike interval and the contraction time (r = 0.49, p < 0.001) and the half-relaxation time (r = 0.58, p < 0.001), respectively. The method shows the proof-of-concept to study MU contractile properties of individual twitches in vivo, which can provide further insights into the force generation mechanisms of voluntary contractions and response to individual neural discharges

Prolonged activity evokes potentiation and the "sag" phenomenon in slow motor units of rat soleus

Slow motor units (MUs) have no sag in their unfused tetani. This study in anesthetized rats shows that the sag can be observed in slow soleus MUs after prolonged activity. Twitches and unfused tetanic contractions were recorded from male (n=35) and female (n=39) MUs before and after the four minutes of the fatigue test (trains of 13 pulses at 40 Hz repeated every second). After this activity twitch contractions potentiated and a shift in the steep part of the force-frequency curve towards lower frequencies was observed in both sexes. Initially no sag was visible in unfused tetani, but after the fatigue test the phenomenon was observed in 77% of male and in 13% of female MUs, with the sex difference possibly related to a higher content of IIa myosin and faster MU contraction in male soleus. Decomposition of tetani with sag into trains of separate twitches elicited by successive stimuli revealed higher forces for the initial than subsequent twitches. The newly revealed enhancement of the sag in force development following long-lasting activation is more pronounced in males than in females

Estimation of contractile parameters of successive twitches in unfused tetanic contractions of single motor units : A proof-of-concept study using ultrafast ultrasound imaging in vivo

During a voluntary contraction, motor units (MUs) fire a train of action potentials, causing summation of the twitch forces, resulting in fused or unfused tetanus. Twitches have been important in studying whole-muscle contractile properties and differentiation between MU types. However, there are still knowledge gaps concerning the voluntary force generation mechanisms. Current methods rely on the spike-triggered averaging technique, which cannot track changes in successive twitches' properties in response to individual neural firings. This study proposes a method that estimates successive twitches contractile parameters of single MUs during low force voluntary isometric contractions in human biceps brachii. We used a previously developed ultrafast ultrasound imaging method to estimate unfused tetanic activity signals of single MUs. A twitch decomposition model was used to decompose unfused tetanic activity signals into individual twitches. This study found that the contractile parameters varied within and across MUs. There was an association between the inter-spike interval and the contraction time (r = 0.49, p < 0.001) and the half-relaxation time (r = 0.58, p < 0.001), respectively. The method shows the proof-of-concept to study MU contractile properties of individual twitches in vivo, which can provide further insights into the force generation mechanisms of voluntary contractions and response to individual neural discharges

An Approach for Simulation of the Muscle Force Modeling It by Summation of Motor Unit Contraction Forces

Muscle force is due to the cumulative effect of repetitively contracting motor units (MUs). To simulate the contribution of each MU to whole muscle force, an approach implemented in a novel computer program is proposed. The individual contraction of an MU (the twitch) is modeled by a 6-parameter analytical function previously proposed; the force of one MU is a sum of its contractions due to an applied stimulation pattern, and the muscle force is the sum of the active MUs. The number of MUs, the number of slow, fast-fatigue-resistant, and fast-fatigable MUs, and their six parameters as well as a file with stimulation patterns for each MU are inputs for the developed software. Different muscles and different firing patterns can be simulated changing the input data. The functionality of the program is illustrated with a model consisting of 30 MUs of rat medial gastrocnemius muscle. The twitches of these MUs were experimentally measured and modeled. The forces of the MUs and of the whole muscle were simulated using different stimulation patterns that included different regular, irregular, synchronous, and asynchronous firing patterns of MUs. The size principle of MUs for recruitment and derecruitment was also demonstrated using different stimulation paradigms

A General Mathematical Algorithm for Predicting the Course of Unfused Tetanic Contractions of Motor Units in Rat Muscle

<div><p>An unfused tetanus of a motor unit (MU) evoked by a train of pulses at variable interpulse intervals is the sum of non-equal twitch-like responses to these stimuli. A tool for a precise prediction of these successive contractions for MUs of different physiological types with different contractile properties is crucial for modeling the whole muscle behavior during various types of activity. The aim of this paper is to develop such a general mathematical algorithm for the MUs of the medial gastrocnemius muscle of rats. For this purpose, tetanic curves recorded for 30 MUs (10 slow, 10 fast fatigue-resistant and 10 fast fatigable) were mathematically decomposed into twitch-like contractions. Each contraction was modeled by the previously proposed 6-parameter analytical function, and the analysis of these six parameters allowed us to develop a prediction algorithm based on the following input data: parameters of the initial twitch, the maximum force of a MU and the series of pulses. Linear relationship was found between the normalized amplitudes of the successive contractions and the remainder between the actual force levels at which the contraction started and the maximum tetanic force. The normalization was made according to the amplitude of the first decomposed twitch. However, the respective approximation lines had different specific angles with respect to the ordinate. These angles had different and non-overlapping ranges for slow and fast MUs. A sensitivity analysis concerning this slope was performed and the dependence between the angles and the maximal fused tetanic force normalized to the amplitude of the first contraction was approximated by a power function. The normalized MU contraction and half-relaxation times were approximated by linear functions depending on the normalized actual force levels at which each contraction starts. The normalization was made according to the contraction time of the first contraction. The actual force levels were calculated initially from the recorded tetanic curves and subsequently from the modeled curves obtained from the summation of all models of the preceding contractions (the so called “full prediction”). The preciseness of the prediction was verified by two coefficients estimating the error between the modeled and the experimentally recorded curves. The proposed approach was tested for 30 MUs from the database and for three additional MUs, not included in the initial set. It was concluded that this general algorithm can be successfully used for modeling of a unfused tetanus course of a single MU of fast and slow type.</p></div

Description of the parameters used for the <i>j</i>-th MU recordings.

<p>A. The model of the <i>i</i>-th decomposed contraction within the unfused tetanus is shown by a dashed line, the black solid line is a piece of the force obtained by subtraction of all previous (<i>i</i>-1) contraction models from the experimental tetanic force. The parameters of the <i>i</i>-th twitch-like contraction are: <i>F</i>_<i>max</i>^<i>(j)</i><i>(i)</i>–the maximum twitch force; <i>T</i>_<i>lead</i>^<i>(j)</i> <i>(i)</i>–the lead time, the time between the <i>i</i>-th stimulus (its time position is indicated by vertical arrow) and the start of the current <i>i</i>-th contraction; <i>T</i>_<i>hc</i>^<i>(j)</i>–the half-contraction time, the time from the start of the contraction to the moment when the twitch force reaches a half of its maximal value; <i>T</i>_<i>c</i>^<i>(j)</i>–the contraction time, the time from the start of the contraction to the moment when the twitch amplitude reaches it maximal value <i>F</i>_<i>max</i>^<i>(j)</i><i>(i); T</i>_<i>hr</i>^<i>(j)</i><i>(i)</i>–the half-relaxation time, the time between the start of the contraction to the moment when during the relaxation, the twitch force decreases to <i>F</i>_<i>max</i>^<i>(j)</i><i>(i)/</i>2; <i>T</i>_<i>tw</i>^<i>(j)</i><i>(i)</i>—the duration of the current contraction, from the time between the moment when the contraction starts and the moment when the force decreases to 0.01% of <i>F</i>_<i>max</i>^<i>(j)</i><i>(i)</i>. The equation describing this bell-shape 6-parameters curve are given in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0162385#pone.0162385.ref009" target="_blank">9</a>]; B. Parameters measured for tetanic contractions presented on a part of the unfused tetanic curve (left) and the maximum fused tetanus (right). <i>F</i>_<i>mftf</i>^<i>(j)</i>—the maximal force that a MU develops during stimulation at 150 Hz stimulation frequency (in the fused tetanus). <i>F</i>_{<i>tetmin</i>}^<i>(j)</i><i>(i)</i>—the force level at which the <i>i</i>-th contraction starts; <i>F</i>_<i>res</i>^<i>(j)</i><i>(i) = F</i>_<i>mftf</i>^<i>(j)</i><i>-F</i>_{<i>tetmin</i>}^<i>(j)</i><i>(i)</i>—the residual force.</p