During muscle contraction, electrical signals are generated by the muscle cells. The analysis of those signals is called electromyography (EMG). The EMG signal is mainly determined by physiological factors including so called central factors (central nervous system origin) and peripheral factors (muscle tissue origin). In addition, during the acquisition of EMG signals, technical factors are introduced (measurement equipment origin). The aim of this dissertation was to develop and evaluate methods to estimate physiological properties of the muscles using multichannel surface EMG (MCsEMG) signals. In order to obtain accurate physiological estimates, a method for automatic signal quality estimation was developed. The method’s performance was evaluated using visually classified signals, and the results demonstrated high classification accuracy. A method for estimation of the muscle fibre conduction velocity (MFCV) and the muscle fibre orientation (MFO) was developed. The method was evaluated with synthetic signals and demonstrated high estimation precision at low contraction levels. In order to discriminate between the estimates of MFCV and MFO belonging to single or populations of motor units (MUs), density regions of so called spatial distributions were examined. This method was applied in a study of the trapezius muscle and demonstrated spatial separation of MFCV (as well as MFO) even at high contraction levels. In addition, a method for quantification of MU synchronisation was developed. The performance on synthetic sEMG signals showed high sensitivity on MU synchronisation and robustness to changes in MFCV. The method was applied in a study of the biceps brachii muscle and the relation to force tremor during fatigue. The results showed that MU synchronisation accounted for about 40 % of the force tremor. In conclusion, new sEMG methods were developed to study muscle function and motor control in terms of muscle architecture, muscle fibre characteristics, and processes within the central nervous system.

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.

Strukturell avbildning med ultraljud kan användas för att upptäcka sjukdomar och störningar i kroppen. För att ställa tillförlitliga diagnoser räcker det inte alltid med en strukturell avbildning utan ibland krävs det även fysiologisk information. Vid användning av funktionell avbildning med ultraljud kan den informationen mätas i kroppens olika fysiologiska system.   Systemen består av funktionellt olika enheter och kallas för motoriska enheter i skelettmuskulatur. Vid sjukdomar som ateroskleros (åderförkalkning) kan dessa enheter vara så kallade kärlplack, som består av vävnad med varierande egenskaper och medicinsk relevans. Möjligheten att kunna analysera funktionella enheter i system som dessa kan bidra mycket till diagnostisering av sjukdomar och störningar.   Den här studien presenterar en metod för att hitta naturliga kluster av funktionella enheter i skelettmuskulatur, från 3D-data inhämtat med ultraljudssekvenser.   I studien genererades syntetiska data från en modell som simulerar sekvenser av aktionspotentialer i kontraherande muskelvävnad. Datat bearbetades med förbehandlingar och klusteranalys och resultaten utvärderades med siluettkoefficienter. Kombinationer av fyra förbehandlingssätt och två klustringsalgoritmer jämförs i studien. Även tester på riktigt ultraljudsdata av muskelkontraktioner utfördes.   Den bästa kombinationen av förbehandling och klustringsalgoritm gav goda resultat och använder datanormalisering samt temporal bandpassfiltrering som förbehandling tillsammans med hierarkisk Complete Linkage-klustring. Den var dessutom relativt okänslig för störningar i datat. Resultaten från riktigt ultraljudsdata gav en grov indelning av områden i muskeln som visuellt överensstämmer med anatomin i den strukturella bilden. / Structural imaging using ultra sound can be used to detect diseases and disorders in the body. It’s not always enough to structurally image these detections for accurate diagnosis, sometimes physiologically functional information is needed. By using functional imaging, this information can be measured in various physiological systems throughout the body.   The systems are built up by functionally different units. In skeletal muscle these units are called motor units and in cases of disease, like atherosclerosis, they can be arterial plack. The placks have a tissue composition of various properties and clinical relevance. If functional units could be analyzed in systems like these, much could be contributed to diagnosis of diseases and disorders.   In this study, a method of detecting natural clusters of functional units in skeletal muscle, using 3D data collected from ultrasound sequences, is presented.   Using a model that simulates a series of actions potentials in contracting muscle tissue, synthetic data was generated. During analysis the data was preprocessed and clustered, the results were analyzed using silhouette coefficients. In this study, combinations of four methods of preprocessing and two clustering algorithms are compared. Real ultrasound data of contracting muscle tissue was also examined.   A combination of preprocessing and clustering that clustered the data particularly well used data normalization and temporal passband filtering for preprocessing together with hierarchical Complete Linkage clustering. It also seemed to be relatively unaffected by noise. Clustering of the real ultrasound data resulted in a coarse sorting of the different areas of the muscle that corresponds to the anatomy seen in structural images.

Résumé en français :<p>L’objectif de nos investigations a été d’étudier, chez le sujet humain, les mécanismes responsables de l'altération des performances motrices au cours du vieillissement. La première étude était destinée d’une part, à comparer la diminution maximale de force observée dans les différents régimes de contraction et, d’autre part, à contribuer à la compréhension des mécanismes à l’origine de la meilleure préservation de force pour le régime excentrique. Etant donné que jusqu’à présent, seuls des facteurs musculaires avaient été proposés afin d’expliquer les différences existant en fonction du régime de contraction, nous nous sommes plus particulièrement intéressés à une éventuelle participation de facteurs nerveux. <p>Dans la seconde étude, nous avons testé de manière indirecte (via l’enregistrement d’activités réflexes) l’efficacité des afférences périphériques au cours du vieillissement. En effet, sous le contrôle de la commande centrale, celles-ci contribuent également à réguler le niveau d’excitabilité des motoneurones. Une moindre efficacité de celles-ci pourrait donc être un facteur supplémentaire responsable de l’altération de la fonction motrice. <p>Nous avons ensuite analysé (études III et IV) les propriétés contractiles et le comportement des unités motrices lors de contractions lentes et très rapides (contractions balistiques). Cela nous a permis de vérifier s’il existait chez les seniors une relation entre la diminution de force, de sa vitesse d’installation, et la stratégie d’activation des unités motrices.<p>Enfin, dans l’étude V, nous avons analysé la fatigabilité neuromusculaire chez les seniors, comparativement aux sujets jeunes. Plus spécifiquement, nous avons étudié les contractions concentriques et excentriques maximales fatigantes. La fatigue n’a en effet pas encore été étudiée lors de ces deux types de contraction chez les adultes jeunes et âgés. L’objectif de cette dernière étude était surtout d’analyser la part relative des mécanismes nerveux et musculaires à l’origine de la fatigue ainsi que leur décours dans le temps en fonction de l’âge des sujets.<p>L’approche méthodologique utilisée nous a permis d’analyser les modifications fonctionnelles du muscle et de ses unités motrices avec l’âge. Un intérêt tout particulier a été porté aux ajustements de la commande nerveuse et à la compréhension des mécanismes sous-jacents. L’ensemble de nos résultats expérimentaux documentent de manière originale l’interaction étroite entre les adaptations nerveuses et musculaires au cours du vieillissement. Plus largement, notre travail doctoral contribue à une meilleure connaissance de la remarquable plasticité du système neuromusculaire chez l’homme. <p>Résumé en anglais :\ / Doctorat en Sciences de la motricité / info:eu-repo/semantics/nonPublished

L’objectif de ce travail a été d’analyser les effets d’une préparation motrice sur l’activité des motoneurones (MN). Pour cela, des protocoles expérimentaux combinant l’enregistrement unitaire de l’activité des unités motrices des muscles extenseurs du poignet avec des paradigmes de préparation motrice de nature temporelle ont été utilisés chez l’Homme. L’analyse des caractéristiques de la décharge tonique des MN montre un allongement des intervalles inter-potentiels associé à une diminution de leur variabilité durant la période préparatoire, bien avant que la réponse motrice ne soit déclenchée. Ces changements démontrent clairement l’implication de mécanismes inhibiteurs spinaux au cours de la préparation motrice pouvant s’exercer au travers d’interneurones prémotoneuronaux. Il est montré que les modulations d’activité motoneuronales induites par la préparation motrice ne sont ni spécifiques au muscle effecteur de la réponse motrice ni prédictifs de la performance. Il est proposé que l’inhibition exercée sur les MN pendant la préparation motrice constitue un mécanisme généralisé de frein pour retenir le déclenchement prématuré de la réponse motrice, tandis que la diminution de variabilité dans la décharge serait un phénomène de compensation, permettant de produire des forces stables malgré la désactivation motoneuronale. L’implication du niveau motoneuronal dans la préparation motrice montre qu’une information au préalable influence l’état du système moteur jusqu’à son élément le plus périphérique, supportant ainsi le caractère hautement distribué des processus préparatoires. Ce travail a également conduit à proposer l’utilisation de l’entropie approximative pour l’analyse de l’activité motoneuronale, permettant d’éviter les écueils liés aux méthodes classiques d’analyse tout en respectant l’hypothèse d’un codage neuronal temporel. / The aim of this work was to analyze the effects of motor preparation on motoneuron (MN) activity. For this purpose, recordings of wrist extensor muscles motor unit activity were combined with time motor preparation paradigms in Human. Changes in the MN tonic discharge were found to occur during preparatory period, i.e. well before it is time to act. These changes were a lengthening of the mean inter-spike interval associated with a decrease of its variability. These data clearly demonstrate that spinal inhibitory mechanisms are activated during motor preparation and suggest the involvement of premotoneuronal interneurons. The modulations of motoneuronal activity induced by the motor preparation are neither specific to the agonist muscle involved in the motor response nor predictive of the performance. It is assumed that the inhibition acting on the MN during the motor preparation constitutes a general braking mechanism serving to prevent premature motor response, whereas the decrease of discharge variability would be a compensatory phenomenon, allowing to produce an efficient steady force in spite of lower motoneuronal activation. The involvement of the motoneuronal level in motor preparation demonstrates that advance information may influence the state of the motor system, including even the most peripheral motor neurons in the spinal cord, which supports the idea that motor preparation involves highly distributed functional processes. In addition, this work led us to argue in favor of the approximate entropy analysis as a suitable method for analyzing spike trains, allowing to detect changes in the regularity of the time-ordered inter-spikes intervals.

No description available.

Title: Spectral Analysis of Electromyography Data of Power Lifters Objectives: The aim of this thesis is a description of muscle activity and its measu- rement using electromyography (EMG), description of parameters of EMG signal and their relationship to neuromuscular physiology. The aim of the practical part is an implementation of spectral analysis of EMG data of power lifters when performing 4 series of 5 split-squats carrying loading in one hand. Methods: The spectral analysis of EMG data of 35 athletes is presented. The athletes performed 4 series of 5 split-squats with one sided loading. The loading was 25% and 50% of their body mass and the carrying position was homolateral and contralateral to stance leg. Muscles chosen for measurement were vastus medialis obliquus, vastus lateralis obliquus, gluteus medius and biceps femoris of both sides. The implementation of digital signal proces- sing algorithm was done using Matlab and its Signal Processing Toolbox. The spectral analysis was implemented using discrete Fourier transform with sliding 256-sample window size and 32-sample window increment. The resulting spectrogram was divided into parts based on smoothed EMG. Median frequency for each split-squat was calculated. For the statistical processing we used median frequency differencies...

<p>Signal processing within the neurophysiological field is challenging and requires short processing time and reliable results. In this thesis, three main problems are considered.</p><p>First, a modified line source model for simulation of muscle action potentials (APs) is presented. It is formulated in continuous-time as a convolution of a muscle-fiber dependent transmembrane current and an electrode dependent weighting (impedance) function. In the discretization of the model, the Nyquist criterion is addressed. By applying anti-aliasing filtering, it is possible to decrease the discretization frequency while retaining the accuracy. Finite length muscle fibers are incorporated in the model through a simple transformation of the weighting function. The presented model is suitable for modeling large motor units.</p><p>Second, the possibility of discerning the individual AP components of the concentric needle electromyogram (EMG) is explored. Simulated motor unit APs (MUAPs) are prefiltered using Wiener filtering. The mean fiber concentration (MFC) and jitter are estimated from the prefiltered MUAPs. The results indicate that the assessment of the MFC may well benefit from the presented approach and that the jitter may be estimated from the concentric needle EMG with an accuracy comparable with traditional single fiber EMG.</p><p>Third, automatic, rather than manual, detection and discrimination of recorded C-fiber APs is addressed. The algorithm, detects the Aps reliably using a matched filter. Then, the detected APs are discriminated using multiple hypothesis tracking combined with Kalman filtering which identifies the APs originating from the same C-fiber. To improve the performance, an amplitude estimate is incorporated into the tracking algorithm. Several years of use show that the performance of the algorithm is excellent with minimal need for audit.</p>

Signal processing within the neurophysiological field is challenging and requires short processing time and reliable results. In this thesis, three main problems are considered. First, a modified line source model for simulation of muscle action potentials (APs) is presented. It is formulated in continuous-time as a convolution of a muscle-fiber dependent transmembrane current and an electrode dependent weighting (impedance) function. In the discretization of the model, the Nyquist criterion is addressed. By applying anti-aliasing filtering, it is possible to decrease the discretization frequency while retaining the accuracy. Finite length muscle fibers are incorporated in the model through a simple transformation of the weighting function. The presented model is suitable for modeling large motor units. Second, the possibility of discerning the individual AP components of the concentric needle electromyogram (EMG) is explored. Simulated motor unit APs (MUAPs) are prefiltered using Wiener filtering. The mean fiber concentration (MFC) and jitter are estimated from the prefiltered MUAPs. The results indicate that the assessment of the MFC may well benefit from the presented approach and that the jitter may be estimated from the concentric needle EMG with an accuracy comparable with traditional single fiber EMG. Third, automatic, rather than manual, detection and discrimination of recorded C-fiber APs is addressed. The algorithm, detects the Aps reliably using a matched filter. Then, the detected APs are discriminated using multiple hypothesis tracking combined with Kalman filtering which identifies the APs originating from the same C-fiber. To improve the performance, an amplitude estimate is incorporated into the tracking algorithm. Several years of use show that the performance of the algorithm is excellent with minimal need for audit.

In this thesis we develop several kinds of latent variable models in order to address three types of bio-statistical problem. The three problems are the treatment effect of carcinogens on tumour development, spatial interactions between plant species and motor unit number estimation (MUNE). The three types of data looked at are: highly heterogeneous longitudinal count data, quadrat counts of species on a rectangular lattice and lastly, electrophysiological data consisting of measurements of compound muscle action potential (CMAP) area and amplitude. Chapter 1 sets out the structure and the development of ideas presented in this thesis from the point of view of: model structure, model selection, and efficiency of estimation. Chapter 2 is an introduction to the relevant literature that has in influenced the development of this thesis. In Chapter 3 we use the EM algorithm for an application of an autoregressive hidden Markov model to describe longitudinal counts. The data is collected from experiments to test the effect of carcinogens on tumour growth in mice. Here we develop forward and backward recursions for calculating the likelihood and for estimation. Chapter 4 is the analysis of a similar kind of data using a more sophisticated model, incorporating random effects, but estimation this time is conducted from the Bayesian perspective. Bayesian model selection is also explored. In Chapter 5 we move to the two dimensional lattice and construct a model for describing the spatial interaction of tree types. We also compare the merits of directed and undirected graphical models for describing the hidden lattice. Chapter 6 is the application of a Bayesian hierarchical model (MUNE), where the latent variable this time is multivariate Gaussian and dependent on a covariate, the stimulus. Model selection is carried out using the Bayes Information Criterion (BIC). In Chapter 7 we approach the same problem by using the reversible jump methodology (Green, 1995) where this time we use a dual Gaussian-Binary representation of the latent data. We conclude in Chapter 8 with suggestions for the direction of new work. In this thesis, all of the estimation carried out on real data has only been performed once we have been satisfied that estimation is able to retrieve the parameters from simulated data. Keywords: Amyotrophic lateral sclerosis (ALS), carcinogens, hidden Markov models (HMM), latent variable models, longitudinal data analysis, motor unit disease (MND), partially ordered Markov models (POMMs), the pseudo auto- logistic model, reversible jump, spatial interactions.