L'estimation de la force générée par un muscle est importante dans les études biomécaniques et pour les applications cliniques. Puisque cette force ne peut pas être mesurée directement, le signal électromyographique de surface (SEMG), reflétant le niveau d'activation musculaire, est utilisé pour quantifier la force développée. Cependant, tous les facteurs, contrôlant une contraction isométrique, n'influencent pas la force et le SEMG simultanément. Le but de ce travail de thèse est donc de développer un modèle de simulation conjointe du SEMG et de la force, afin d'étudier la relation EMG-force. Dans ce but, nous avons d'abord développé une nouvelle méthode de simulation de la force musculaire à partir d'un modèle d'EMG existant. Le modèle complet a été testé pour le choix de la stratégie de recrutement et l'influence de la durée de la consigne. Puis, nous avons utilisé une méthode de Monte Carlo pour étudier la sensibilité du modèle aux différents paramètres physiologiques d'entrée. Deux critères existants (relations EMG-force et force-variabilité de force) ainsi qu'un nouveau critère (erreur entre la consigne de force et la force générée), ont été utilisés pour optimiser les paramètres avec une consigne de force constante. Ce nouveau critère a ensuite été utilisé avec une consigne de force variable (sinusoïdale ou triangulaire), afin d'obtenir les plages optimales des paramètres. Enfin, pour évaluer notre modèle, nous avons réalisés des expérimentations et une simulation pour le biceps. Les résultats montrent que notre modèle EMG-force est capable de simuler qualitativement les comportements réels du biceps pour les contractions isotoniques et anisotoniques.

Involuntary electromyographic (EMG) activity has been recorded in the thenar (thumb) muscles of spinal cord injured (SCI) subjects for only short time periods (minutes), but it is unknown if this motor unit activity is ongoing. Longer duration EMG recordings can investigate the physiological significance of this neuromuscular activity. Analysis of these data is complex and time consuming. Since no software is currently capable of classifying 24 hours of data at a single motor unit level, the goal of this research was to devise an algorithm to automatically classify motor unit potentials over 24-hours. Twenty-four-hour, 2-channel thenar muscle EMG recordings were obtained from four different SCI subjects with cervical level injuries using a data logging device with custom software. The automatic motor unit classification algorithm used to classify the 24-hour recordings was a procedure consisting of four stages that included segmentation, clustering, and motor unit template uniting. All individual potentials were then classified and any superimposed potentials were resolved into their constituent classes. Finally, the algorithm found the firing patterns for each of the stable motor unit classes. The classification algorithm performance was compared to the analysis of a human operator and assessed in 2 ways: Tracking global classes over the 24 hours and correctly classifying individual motor unit potentials as to belonging to particular global classes. The algorithm was able to track an average of 13 global classes in four 24-hour recordings with a mean accuracy of 92 %. It was also able to classify individual potentials with a mean accuracy of 86% over four recordings, greater than the inter-rater reliability of two human operators (79%). The activities of the motor units tracked by the algorithm ranged from tonic firing to sporadic activity. The algorithm could analyze 24 hours of data in 2-3 weeks, while a human operator was estimated to take more than 2 years. In conclusion, the motor unit classification algorithm accomplished its goal of automatically tracking motor unit classes over a 24-hour recording with high accuracy. The 24-hour classification method developed here could be applied towards classifying long term recordings of other biological signals.

<p><strong>Syfte </strong></p><p>Syftet med föreliggande studie var att studera korrelationen mellan EMG-respons och effektutveckling i samband med genomförande av knäböj.</p><p><strong>Metod</strong></p><p>Fyra manliga testpersoner deltog genom att utföra både knäböj 90° och djupa knäböj i en Smith-maskin som är ansluten till en Linear Encoder som möjliggör beräkning av effektutveckling. Samtidigt registrerades elektromyografisk aktivitet i musklerna Vastus lateralis, Hamstrings och Gluteus maximus. De utförde knäböj på olika relativa belastningsnivåer; 20, 40, 60, 80, 100% av 1RM.</p><p><strong>Resultat</strong></p><p>Resultaten visade inte en stark korrelation mellan medel-EMG och power, inte heller mellan medel-EMG och hastighet, dock indikerade resultaten mellan de sistnämnda en tendens till att en lägre EMG aktivitet uppstod vid de högre hastigheterna. En starkare korrelation kunde antydas mellan medel-EMG och belastning/kraft. Ingen tydlig skillnad mellan musklerna påträffades i förhållande till resultaten ovan. Dock var Hamstrings den muskeln som uppvisade den svagaste korrelationen.</p><p><strong>Slutsats</strong></p><p>EMG-aktiviteten var i stor grad densamma för respektive muskel trots olika belastningar, olika powervärden samt olika utföranden. Nervsystemet tycks därmed arbeta på ett särskilt sätt, oberoende av de andra parametrarna. Däremot kunde man se en svagare tendens för lägre EMG-aktivitet vid de högre hastigheterna. Hamstringsmuskulaturen var den som hade mest avvikande mönster, detta kan bero på det faktum att den har ett mer komplicerat förlopp än de andra två musklerna som testats.</p>

Hyperkalemic periodic paralysis, HyperKPP, is an inherited progressive disorder of the muscles caused by mutations in the voltage gated sodium channel (NaV1.4). The objectives of this thesis were to develop a technique for measurement symptoms in vivo using electromyography (EMG) and to determine the mechanism by which Ca2+ alleviates HyperKPP symptoms, since this is unknown. Increasing extracellular [Ca2+] ([Ca2+]e) from 1.3 to 4 mM did not result in any increases in45Ca2+ influx suggesting no increase in intracellular [Ca2+] ([Ca2+]i) acting on an intracellular signaling pathway or on an ion channel such as the Ca2+sensitive K+ channels. HyperKPP muscles have larger TTX-sensitive22Na+ influx than wild type muscles because of the defective NaV1.4 channels. When [Ca2+] was increased from 1.3 to 4 mM, the abnormal 22Na+ influx was completely abolished. Thus, one mechanism by which Ca2+alleviates HyperKPP symptoms is by reducing the abnormal Na+ influx caused by the mutation in the NaV1.4 channel.

Cross-education of strength is a neural adaptation defined as the increase in strength of the untrained contralateral limb after unilateral training of the opposite homologous limb. The neural mechanisms of the effect have remained elusive, although it appears to be a motor learning adaptation. Despite cross-education of strength being an inter-limb effect, no previous study has determined the influence of handedness and the direction of transfer (dominant to non-dominant or the reverse). Arguably, this is partly responsible for massive variation in the literature regarding the magnitude of the effect. The primary purpose of this document is to attempt to determine the central and peripheral neuro-physiological mechanisms controlling cross-education of muscular strength. Prior to determining the mechanisms of the effect, the influence of handedness and the preferred direction of transfer for cross-education of strength must be addressed. The secondary purpose is to determine the preferential direction of transfer of cross-education of strength in order to isolate the circumstances in which the effect is more pronounced. Two experiments were necessary to meet these objectives. <p>Experiment 1: The purpose was to determine the effect of the direction of transfer on cross-education in right-handed individuals. Subjects were randomized into a left-hand training (LEFT), right-hand training (RIGHT), or non-training control (CON) group. Strength training was 6 weeks of maximal isometric ulnar deviation, 4 times per week. The change in strength in the untrained limb was greatest in the RIGHT group (39.2%; p<.01), whereas no significant changes in strength were observed for the untrained limb of the LEFT group (9.3%) or for either of the CON group limbs (10.4% and 12.2%). There were no changes in muscle thickness of untrained limbs compared to CON. Changes in untrained limb EMG were not different compared to CON. Cross-education with hand strength training occurs only in the right-to-left direction of transfer in right-handed individuals. Cross-education of arm muscular strength is most pronounced to the non-dominant arm. <p>Experiment 2: The purpose of this study was to determine the central and peripheral mechanisms of cross-education of strength after actual and imagery training. Subjects were randomized into an actual training, imagery training, or non-training control group. A sub-sample of 8 subjects (4 actual, 4 imagery training) had brain activity during exercise assessed with functional magnetic resonance imaging (fMRI). Strength training was 6 weeks of maximal isometric handgrip ulnar deviation (Biodex) of the right arm, 4 times per week. Actual training was highly effective for increasing strength in trained (45.3%; p<.01) and untrained (47.1%; p<.01) limbs. Imagery training and control groups had no increases in strength for either arm. Muscle thickness increased only in the trained arm of the actual group (8.4%; p<.001). After actual training, there was an increase in activation of contralateral sensorimotor cortex and left temporal lobe during actual contractions with the untrained left arm (p<.001). Actual training was associated with a significantly greater change in agonist muscle activation pooled over both limbs, compared to the imagery and control groups (p<.05). Cross-education of strength is only significant after actual training, indicating that peripheral feedback is necessary for the effect. Cross-education of strength is accompanied by changes in cortical activation indicative of motor learning and the retrieval of memory of movement acquired by the trained limb. <p>General Conclusion: The neuro-physiological mechanism of cross-education of strength is that changes in cortical activation indicative of motor learning occur in both brain hemispheres after unilateral training. Cross-education of strength is influenced by strength asymmetries related to handedness, and the preferential direction of transfer is from dominant to non-dominant limb. Cross-education is a motor learning adaptation also reliant on peripheral feedback during training.

The main goal of this thesis was to discover the relationships between MU characteristics and MUP features. To reach this goal, several features explaining the anatomical structure of the muscle were introduced. Additionally, features representing specific properties of the EMG signal detected from that muscle, were defined. Since information regarding the underlying anatomy was not available from real data, a physiologically based muscle model was used to extract the required features. This muscle model stands out from others, by providing similar acquisition schemes as the ones utilized by physicians in real clinical settings and by modelling the interactions among different volume conductor factors and the collection of MUs in the muscle in a realistic way. Having the features ready, several relationship discovery techniques were used, to reveal relationships between MU features and MUP features. To interpret the results obtained from the correlation analysis and pattern discovery techniques properly, several algorithms and new statistics were defined. The results obtained from correlation analysis and pattern discovery technique were similar to each other, and suggested that to maximize the inter-relationships between MUP features and MU features, MUPs could be filtered based on their slope values, specifically MUPs with slopes lower than 0. 6 v/s could be excluded. Additionally PDT results showed that high slope MUPs were not as informative about the underlying MU and could be excluded to maximize the relationships between MUP features and MU characteristics. Certain MUP features were determined to be highly related to certain MU characteristics. MUP <em>area</em> and <em>duration</em> were shown to be the best representative feature for the MU size and <em>average fiber density</em>, respectively. For the distribution of fiber diameter in the MU, <em>duration</em> and <em>number of turns</em> were determined to reflect <em>mean fiber diameter</em> and <em>stdv of fiber diameter</em> the best, correspondingly.

This study examined the relationship among implicit and explicit measures of prejudice (against African-Americans, homosexuals, and Muslims), Right-Wing Authoritarianism (RWA), Religious Fundamentalism (RF), and Christian Orthodoxy (CO). The implicit measure of prejudice was Facial EMG, which is the measurement of the activity of key facial muscles when participants were exposed to pictures of members of the minority groups, as well as to pictures of the corresponding group. The explicit measure of prejudice was the Social Distance Scale, which measures how willing people are to have someone in a variety of close relationships. The primary hypothesis was that one’s score on the implicit (and some of the explicit) measures of prejudice can be predicted using RF, CO, and RWA. The analyses revealed that RWA was predictive of prejudice against homosexuals and Muslims, but not against African-Americans.

This study is aimed to determine the electromyographic signals of the forearm, using Ag/AgCl electrodes. The four major muscles of forearm, which are providing the bioelectrical currents, have been displayed and analysed to determine the different activities. In order to record the signals, an EMG device has been developed and installed and a schematic has also been presented in this paper.

The main goal of this thesis was to discover the relationships between MU characteristics and MUP features. To reach this goal, several features explaining the anatomical structure of the muscle were introduced. Additionally, features representing specific properties of the EMG signal detected from that muscle, were defined. Since information regarding the underlying anatomy was not available from real data, a physiologically based muscle model was used to extract the required features. This muscle model stands out from others, by providing similar acquisition schemes as the ones utilized by physicians in real clinical settings and by modelling the interactions among different volume conductor factors and the collection of MUs in the muscle in a realistic way. Having the features ready, several relationship discovery techniques were used, to reveal relationships between MU features and MUP features. To interpret the results obtained from the correlation analysis and pattern discovery techniques properly, several algorithms and new statistics were defined. The results obtained from correlation analysis and pattern discovery technique were similar to each other, and suggested that to maximize the inter-relationships between MUP features and MU features, MUPs could be filtered based on their slope values, specifically MUPs with slopes lower than 0. 6 v/s could be excluded. Additionally PDT results showed that high slope MUPs were not as informative about the underlying MU and could be excluded to maximize the relationships between MUP features and MU characteristics. Certain MUP features were determined to be highly related to certain MU characteristics. MUP <em>area</em> and <em>duration</em> were shown to be the best representative feature for the MU size and <em>average fiber density</em>, respectively. For the distribution of fiber diameter in the MU, <em>duration</em> and <em>number of turns</em> were determined to reflect <em>mean fiber diameter</em> and <em>stdv of fiber diameter</em> the best, correspondingly.

Gloved work has been shown to increase the effort required to perform manual tasks. In power grip tasks, these differences have been observed as reductions in strength and increases in muscular effort. Decreases in force output have been attributed to a number of factors, including loss of tactile sensitivity, glove flexibility or suppleness, thickness, changes in hand geometry, and friction at the glove-object interface. Glove research has rarely quantified glove attributes, and often compared gloves of varying material and physical properties. This research had the unique opportunity to control for a number of these properties by using three sets of identical gloves (powerline maintainers? insulating rubber gloves), differing only in thickness. <br /><br /> Administering the Von Frey Hair Test indicated that the gloves did indeed decrease tactile sensitivity. This research showed that increasing glove thickness led to large decreases in maximum power grip force. Small changes in hand geometry, such as increased interdigital space or grip span, affected force output. In the same hand posture, participants increased their grip force with increasing glove thickness for the object lifting task but were able to maintain a fixed submaximal force with visual feedback. The decrease in tactile sensitivity is a likely cause of this difference. <br /><br /> Muscular activity was affected by wearing the gloves while performing manual tasks. Inconsistent responses of muscular activation were seen in gloved maximum grip effort, while overall increases in electromyographic activity were recorded for tasks at submaximal levels when wearing gloves. <br /><br /> Interdigital spacing had different effects on maximal and submaximal tasks. For maximum effort power grip, interdigital spacing decreased force output by as much as 10%, with no significant changes in muscle activation. For submaximal tasks, no significant differences were seen in muscular activity or in force output. The overall force capability of the gloved user is hindered by changes in interdigital spacing at near maximal effort, but does not appear to be for tasks requiring lower grip force, such as the lifting task which required roughly 20%MVC. Overall, the effect of wearing these gloves on the users, the powerline maintainers, is a substantially increased effort to work. This research contributes to a greater understanding of why and how gloves inhibit performance.