The purpose of this study was to determine whether ischemia would enhance muscle spindle responses to tendon tap and vibration during submaximal fatiguing contractions in the soleus muscle of able-bodied individuals. Nine healthy adults attended two experimental sessions approximately 48 hours apart. Both sessions were identical except that the fatigue task in one was performed with a pressure cuff placed above the knee and inflated to 180 mm Hg. Three 5s maximum voluntary contractions (MVCs) were performed prior to and after the fatigue task. Each participant held a target force of 20% MVC until endurance time (peak-to-peak tremor amplitude exceeded 5% MVC or target force dropped by 2% for 3s). Muscle spindle responses were evaluated using the peak-to-peak EMG amplitude of tendon taps (delivered by a custom-made tapper) and the Motor Unit Firing Rates (MUFR) during 15 s of vibration, recorded with fine-wire intramuscular electrodes. H reflex responses were measured before and after fatigue for each condition, to measure the net excitability of the spinal cord. There were no significant differences (p>0.05) in the P-P EMG of tendon taps or the MUFR across any conditions. The post-fatigue Maximal Voluntary Contraction forces were measured and were less than the pre-fatigue values under both conditions (and significantly different in the non-ischemic condition (p=0.01)). Absence of significant differences in the Hmax:Mmax ratios (p=0.94 in non-ischemic/fatigue and p=0.43 in ischemic condition) indicated that the spinal excitability was relatively unchanged across the conditions. Therefore, we could not conclude that ischemia enhanced the muscle spindle response. / text

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.

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 thesis is an investigation of the neurophysiologic mechanism, central sensitization, underlying pain and dysfunction in osteoarthritis. Central sensitization is an important mechanism in the pathophysiology of osteoarthritis but, to our knowledge, its influence on motoneurone excitability is unknown. Our primary hypothesis states that increasing central sensitization within a spinal segment will cause a greater increase in the excitability of motoneurones in subjects with osteoarthritis when compared to healthy controls. To test this hypothesis, we experimentally induced central sensitization in individuals and monitored the recruitment threshold force of the motor units in the first dorsal interosseous muscle using indwelling electromyography. Findings from this study suggest that central sensitization lowers the motor unit recruitment threshold in osteoarthritis compared to healthy individuals. Motoneurone excitability might be inhibited in healthy individuals with persistent sensitization as well. Thus, central sensitization is an important consideration in the biomechanical dysfunction seen in osteoarthritis. / Canadian Arthritis Network

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The detection of physiological signals from the Motor System (electromyographic signals), studied by electromyography, is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of electromyographic signals (EMG) that includes the identification and classification of Motor Unit Action Potential (MUAP) of EMG signals, is very import to help the therapist in the evaluation of motor disorders The EMG decomposition is a complex task due to the features of the EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date the majority of research on EMG decomposition utilizes EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively little research has been conducted using surface based EMG signals. As such this thesis aims to contribute to the clinical practice and Biofeedback therapies by presenting a system permitting the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of Differential Evolution and Spectral Clustering techniques. The developed system presented coherent results in: a) Identification of the number of Motor Units actives in the EMG signal; b) Presentation of the morphological patterns of MUAPs in the EMG signal; c) Identification of the firing sequence of the Motor Units. The Techniques utilized in this work have not yet been applied in the field of EMG decomposition and, in the end of this work, it was proved that they are excellent techniques for the surface EMG decomposition. The model proposed in this work is an advance in the research of decomposition of surface EMG signals. / A captação de sinais fisiológicos provenientes do Sistema Motor, que pode ser realizada pela eletromiografia, tem sido cada vez mais utilizada na prática clínica para auxiliar o terapeuta no diagnóstico de distúrbios motores. Desta forma, o processo de decomposição de sinais eletromiográficos (EMG), que inclui a identificação e classificação dos potenciais de ação de Unidade Motora (MUAP) de um sinal EMG de superfície é de extrema importância para a prática clínica, para auxiliar os profissionais na detecção de patologias do Sistema Motor. O processo de decomposição de um sinal EMG é uma tarefa complexa, pois as características de um sinal EMG dependem do tipo de eletrodo utilizado (intramuscular ou de superfície), do seu posicionamento em relação ao músculo, o nível de contração e o estado clínico do Sistema Neuromuscular do paciente. A maior parte dos sistemas de decomposição de sinais EMG são específicos para o sinal proveniente de eletrodos invasivos, devido às facilidades e vantagens em processar este tipo de sinal. Assim, poucos esforços foram concentrados no que tange à decomposição de sinais EMG de superfície. Neste contexto, este trabalho apresenta um sistema de decomposição de sinais EMG de superfície utilizando Modelos Ocultos de Markov, com o apoio das técnicas Evolução Diferencial e Agrupamento Espectral, no intuito de auxiliar a prática clínica e as terapias de Biofeedback. O sistema desenvolvido apresentou resultados coerentes no que tange a: a) Identificação da quantidade de Unidades Motoras ativas no sinal EMG; b) Apresentação dos padrões morfológicos de MUAPs presentes no sinal EMG; c) Identificação da seqüência de disparos das Unidades Motoras no sinal EMG analisado. As técnicas utilizadas neste trabalho ainda não tinham sido fruto de pesquisa na área de decomposição de sinais EMG, e se destacam como excelentes técnicas para processamento de sinal EMG de superfície. A arquitetura do modelo proposto constitui um avanço nas pesquisas de decomposição de eletromiografia de superfície. / Doutor em Ciências

"This compendium-format dissertation (i.e., comprised mostly of published and in-process articles) primarily reports on system identification methods that relate the surface electromyogram (EMG)—the electrical activity of skeletal muscles—to mechanical kinetics. The methods focus on activities of the elbow and hand-wrist. The relationship between the surface EMG and joint impedance was initially studied. My work provided a complete second-order EMG-based impedance characterization of stiffness, viscosity and inertia over a complete range of nominal torques, from a single perturbation trial with slowly varied torque. A single perturbation trial provides a more convenient method for impedance evaluation. The RMS errors of the EMG-based method were 20.01% for stiffness and 7.05% for viscosity, compared with the traditional mechanical measurement. Three projects studied the relationship between EMG and force/torque, a topic that has been studied for a number of years. Optimal models use whitened EMG amplitude, combining multiple EMG channels and a polynomial equation to describe this relationship. First, we used three techniques to improve current models at the elbow joint. Three more features were extracted from the EMG (waveform length, slope sign change rate and zero crossing rate), in addition to EMG amplitude. Each EMG channel was used separately, compared to previous studies which combined multiple channels from biceps and, separately, from triceps muscles. Finally, an exponential power law model was used. Each of these improvement techniques showed better performance (P<0.05 and ~0.7 percent maximum voluntary contraction (%MVC) error reduction from a nominal error of 5.5%MVC) than the current “optimal” model. However, the combination of pairs of these techniques did not further improve results. Second, traditional prostheses only control 1 degree of freedom (DoF) at a time. My work provided evidence for the feasibility of controlling 2-DoF wrist movements simultaneously, with a minimum number of electrodes. Results suggested that as few as four conventional electrodes, optimally located about the forearm, could provide 2-DoF simultaneous, independent and proportional control with error ranging from 9.0–10.4 %MVC, which is similar to the 1-DoF approach (error from 8.8–9.8 %MVC) currently used for commercial prosthesis control. The third project was similar to the second, except that this project studied controlling a 1-DoF wrist with one hand DoF simultaneously. It also demonstrated good performance with the error ranging from 7.8-8.7 %MVC, compared with 1-DoF control. Additionally, I participated in two team projects—EMG decomposition and static wrist EMG to torque—which are described herein. "

A hallmark of human behaviour is that we can either couple or decouple our thoughts, decision and motor plans from actions. Previous studies have reported evidence of gating of information between intention and action that can happen at different levels in the central nervous system (CNS) involving the motor cortex, subcortical structures such as the basal ganglia and even in the spinal cord. In my research I examine the extent of this gating and its modulation by task context. I will present results obtained by data collected from (a) neck muscles and neural recording from frontal eye field (FEF) in macaque monkeys and (b) putative motor units (MUs) from high density electrode arrays using surface EMG signals in human to delineate the type of information that leaks into muscles in the periphery when subjects are involved in preparing eye and hand movements, respectively, and its modulation by task context Overall, my results reveal that we can assess some aspects of central planning in the activity of motor units Further, the recruitment of these motor units depend on task context.

The human jaw, like all other articulated body parts, exhibits small oscillatory movements during isometric holding tasks. These movements, known as physiological tremor, arise as a consequence of the interaction of various factors. One of these factors is reflex feedback from peripheral receptors. In the human jaw, receptors that innervate the periodontium are able to transduce minute changes in force. This thesis examines the contribution of these periodontal mechanoreceptors (PMRs) to the genesis of physiological tremor of the human jaw. By using frequency domain analysis of time series recorded during isometric biting tasks, the character of physiological jaw tremor can be revealed. Physiological jaw tremor was observed in force recorded from between the teeth as well as from electromyograms recorded from the principal muscles of mastication. These recordings have shown us that jaw physiological tremor consists of a frequency invariant component between 6 and 10Hz. This frequency remains unaltered under various load conditions where the mechanical resonance of the jaw would be expected to vary greatly (Chapter 2). Such findings indicate a ‘neurogenic’ origin for this tremor. A possible candidate for this neurogenic component of physiological tremor in the jaw is the reflex feedback arising from the PMRs. Using local anaesthetisation, it has been shown in this thesis, that by blocking outflow from the PMRs, the amplitude of neurogenic physiological jaw tremor can be reduced dramatically. This procedure caused a dramatic reduction in not only the mechanical recordings of tremor but also in the coupling between masseteric muscles bilaterally (Chapter 3) and between single motor units recorded from within a homonymous muscle (Chapter 4). The obvious mechanism by which periodontal mechanoreceptor anaesthetisation could reduce the amplitude of physiological tremor in the jaw would be by reducing the amplitude of the oscillatory input to the motoneurones driving the tremor. This interpretation remains controversial however as physiological tremor in the jaw can be observed at force levels above which the PMRs are supposedly saturated in their response. In light of this knowledge, the saturating characteristics of these receptors in terms of reflex output were examined. To do this, a novel stimulation paradigm was devised whereby the incisal teeth were mechanically stimulated with identical stimulus waveforms superimposed upon increasing tooth preloads. This necessitated the use of a frequency response method to quantify the reflexes. An optimal frequency for stimulation was identified and used to confirm that the hyperbolic saturating response of PMRs observed previously, translated to a similar phenomenon in masticatory reflexes (Chapter 5). These data reinforced the idea that physiological tremor in the jaw was not just a consequence of rhythmic reflex input from PMRs, as the dynamic reflex response uncoupled from the input as the receptor-mediated reflex response saturated. An alternative hypothesis was then developed that suggested the effect of PMR suppression in physiological tremor was via tonic rather than rhythmic effects on the masseteric motoneurone pool. By utilising a novel contraction strategy to manipulate the mean firing rate of the motor neuron pool at a given level of force production, data contained in Chapter 6 shows that population motor unit firing statistics influence the expression of physiological tremor, and such manipulations mimic, to an extent, the changes in firing statistics and tremor amplitude seen during anaesthetisation of the PMRs. This thesis therefore posits a mechanism whereby periodontal input influences the firing rate of motoneurones in such a way as to promote tremulous activity (Chapter 5). However, as this proposed mechanism did not explain the full extent of tremor suppression seen during PMR anaesthetisation it can therefore only be considered a contributing factor in a multifactor process. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1297555 / Thesis (Ph.D.) -- University of Adelaide, School of Molecular and Biomedical Science, 2007

The human jaw, like all other articulated body parts, exhibits small oscillatory movements during isometric holding tasks. These movements, known as physiological tremor, arise as a consequence of the interaction of various factors. One of these factors is reflex feedback from peripheral receptors. In the human jaw, receptors that innervate the periodontium are able to transduce minute changes in force. This thesis examines the contribution of these periodontal mechanoreceptors (PMRs) to the genesis of physiological tremor of the human jaw. By using frequency domain analysis of time series recorded during isometric biting tasks, the character of physiological jaw tremor can be revealed. Physiological jaw tremor was observed in force recorded from between the teeth as well as from electromyograms recorded from the principal muscles of mastication. These recordings have shown us that jaw physiological tremor consists of a frequency invariant component between 6 and 10Hz. This frequency remains unaltered under various load conditions where the mechanical resonance of the jaw would be expected to vary greatly (Chapter 2). Such findings indicate a ‘neurogenic’ origin for this tremor. A possible candidate for this neurogenic component of physiological tremor in the jaw is the reflex feedback arising from the PMRs. Using local anaesthetisation, it has been shown in this thesis, that by blocking outflow from the PMRs, the amplitude of neurogenic physiological jaw tremor can be reduced dramatically. This procedure caused a dramatic reduction in not only the mechanical recordings of tremor but also in the coupling between masseteric muscles bilaterally (Chapter 3) and between single motor units recorded from within a homonymous muscle (Chapter 4). The obvious mechanism by which periodontal mechanoreceptor anaesthetisation could reduce the amplitude of physiological tremor in the jaw would be by reducing the amplitude of the oscillatory input to the motoneurones driving the tremor. This interpretation remains controversial however as physiological tremor in the jaw can be observed at force levels above which the PMRs are supposedly saturated in their response. In light of this knowledge, the saturating characteristics of these receptors in terms of reflex output were examined. To do this, a novel stimulation paradigm was devised whereby the incisal teeth were mechanically stimulated with identical stimulus waveforms superimposed upon increasing tooth preloads. This necessitated the use of a frequency response method to quantify the reflexes. An optimal frequency for stimulation was identified and used to confirm that the hyperbolic saturating response of PMRs observed previously, translated to a similar phenomenon in masticatory reflexes (Chapter 5). These data reinforced the idea that physiological tremor in the jaw was not just a consequence of rhythmic reflex input from PMRs, as the dynamic reflex response uncoupled from the input as the receptor-mediated reflex response saturated. An alternative hypothesis was then developed that suggested the effect of PMR suppression in physiological tremor was via tonic rather than rhythmic effects on the masseteric motoneurone pool. By utilising a novel contraction strategy to manipulate the mean firing rate of the motor neuron pool at a given level of force production, data contained in Chapter 6 shows that population motor unit firing statistics influence the expression of physiological tremor, and such manipulations mimic, to an extent, the changes in firing statistics and tremor amplitude seen during anaesthetisation of the PMRs. This thesis therefore posits a mechanism whereby periodontal input influences the firing rate of motoneurones in such a way as to promote tremulous activity (Chapter 5). However, as this proposed mechanism did not explain the full extent of tremor suppression seen during PMR anaesthetisation it can therefore only be considered a contributing factor in a multifactor process. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1297555 / Thesis (Ph.D.) -- University of Adelaide, School of Molecular and Biomedical Science, 2007

In daily activities, hand use is dominated by individuated thumb and finger movements, and by grasping. This thesis focused on the level of ???independence??? of the digits and its relationship to hand grasps, from the level of the motor units to the level of synergistic grasping forces. Four major studies were conducted in healthy adult volunteers. First, spike-triggered averages of forces produced by single motor units in flexor pollicis longus (FPL) in a grasp posture showed small but significant loading of the index, but not other fingers. This reflected a neural rather than anatomical coupling, as intramuscular stimulation produced minimal effect in any finger. Also, FPL had a surprisingly large number of low-force motor units and this may account for the thumb???s exceptional dexterity and force stability compared with the fingers. Second, independent control of extensor digitorum (ED) was more limited than flexor digitorum profundus (FDP), as more ED motor units of a ???test??? finger were recruited inadvertently by extension than by flexion of adjacent digits. Third, ???force enslavement??? in maximal voluntary tasks was greater in digit extension than flexion. The distribution of force enslavement (and deficits) matched the pattern of daily use of the digits (alone and in combination), and reveals a neural control system which preferentially lifts fingers together from an object by extension but allows an individual digit to flex to contact an object so the finger pads can engage in exploration and grasping. Finally, during grasping, irrespective of whether a digit had been lifted from the object, coherence among forces generated by the digits was similar. In addition, the coherence between finger forces was independent of any contraction of the thumb, was stable over 2 months, and required no learning. The pattern of coherence between digital grasping forces may be closely related to the level of digit independence and daily use. Overall, the grasp synergy was remarkably invariant over the various tasks and over time. In summary, this thesis demonstrates novel aspects of the properties of FPL, the lack of complete independence of the digits, and robustness in the production of flexion forces in hand grasps.