Title: H-reflex, depending on the position of the joint Aim: The aim of this study is to determine whether the position of the ankle joint influences the parameters of the soleus muscle H-reflex. We are interested in a change of amplitude, latency and threshold of the H-reflex. Method: To measure H-reflex, we have used surface elektromygraphy. We examined two different positions of the foot in probands lying on the bed on their stomach. The first position was with the feet out of bed, around 90 degrees at the ankle joint (rest position). At the second position, the foot moved the bed and was in position in plantar flexion. Stimulation were performed over the tibial nerve in the popliteal fossa. The response, we recorded the surface electrode over the soleus muscle. Results: By changing the position of the ankle from rest to plantar flexion there was no statistically significant changes in amplitude, latency or threshold of the H-reflex. In plantar flection, we found a reduction of Hmax/Mmax ratio, which is probably due to reduced excitability alpha motoneurons through reciprocal ihibition from stretched muscle of the leg. Keywords: H-reflex, soleus muscle, joint position, surface EMG

An accurate determination of muscle force is desired in many applications in different fields such as ergonomics, sports medicine, prosthetics, human-robot interaction and medical rehabilitation. Since individual muscle forces cannot be directly measured, force estimation using recorded electromyographic (EMG) signals has been extensively studied. This usually involves interpretation and analysis of the recorded EMG to estimate the underlying neuromuscular activity which is related to the force produced by the muscle. Although invasive needle electrode EMG recordings have provided substantial information about neuromuscular activity at the motor unit (MU) level, there is a risk of discomfort, injury and infection. Thus, non-invasive methods are preferred and surface EMG (SEMG) recording is widely used. However, physiological and non-physiological factors, including phase cancelation, tissue filtering, cross-talk from other muscles and non-optimal electrode placement, affect the accuracy of SEMG-based force estimation. In addition, the relative movement of the muscle bulk and the innervation zone (IZ) with respect to the electrode attached to the skin are two major challenges to overcome in force estimation during dynamic contractions. The objective of this work is to improve the accuracy of SEMG-based force estimation under static conditions, and devise methods that can be applied to force estimation under dynamic conditions. To achieve this objective, a novel calibration technique is proposed, which corrects for variations in the SEMG with changing joint angle. In addition, a modeling technique, namely parallel cascade identification (PCI) that can deal with non-linearities and dynamics in the SEMG-force relationship is applied to the force estimation problem. Finally, a novel integrated sensor that senses both SEMG and surface muscle pressure (SMP) is developed and the two signal modalities are used as input to a force prediction model. The experimental results show significant improvement in force prediction using data calibrated with the proposed calibration method, compared to using non-calibrated data. Joint angle dependency and the sensitivity to the location of the sensor in the SEMG-force relationship is reduced with calibration. The SEMG-force estimation error, averaged over all subjects, is reduced by 44\% for PCI modeling compared to another modeling technique (fast orthogonal search) applied to the same dataset. Significantly improved force estimation results are also achieved for dynamic contractions when joint angle based calibration and PCI are combined. Using SMP in addition to SEMG leads to significantly better force estimation compared to using only SEMG signals. The proposed methods have the potential to be combined and used to obtain better force estimation in more complicated dynamic contractions and for applications such as improved control of remote robotic systems or powered prosthetic limbs. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-08-20 20:46:56.897

This thesis presents a method for estimating the positions of human limbs during motion that can be applied to wearable, textile-based sensors. The method was validated for the elbow and shoulder joints with data from two garments with resistive, thread-based sensors sewn into the garments at multiple locations. The proposed method was able to estimate the elbow joint position with an average error of 2.2 degrees. The method also produced an average difference in Euclidean distance of 3.7 degrees for the estimated shoulder joint position using data from nine sensors placed around the subject's shoulder. The most accurate combination of sensors on the shoulder garment was found to produce an average difference in distance of 3.4 degrees and used only six sensors. The characteristics of the resistive, thread-based sensor used to validate the method are also detailed as some of their behaviors proved to affect the accuracy of the method negatively. / Master of Science / Human motion capture systems gather data on the position of the human body during motion. The data is then used to recreate and analyze the motion digitally. There is a need for motion capture devices capable of measuring long-term data on human motion, especially in physical therapy. However, the currently available motion capture systems have limitations that make long-term or daily use either impossible or uncomfortable. This thesis presents a method that uses data from wearable, textile-based sensors to estimate the positions of human limbs during motion. Two garments were used to validate the method on the elbow and shoulder joints. The proposed method was able to measure the elbow and shoulder joints with an average accuracy that is within the acceptable range for clinical settings.

Dans un environnement intérieur, le problème de l'extraction du composant l'Angle de Arrivée de la Line-of-Sight entre un émetteur et un récepteur Wi-Fi utilisant un lien SIMO est la principale préoccupation de cette thèse. Un des principaux défis à relever est dû au riche canal multipath que les environnements intérieurs apprécient. C'est ainsi parce que multipath résulte du fait que le canal de propagation se compose de plusieurs obstacles et réflecteurs. Ainsi, le signal reçu arrive comme un ensemble imprévisible de réflexions et / ou d'ondes directes avec son degré d'atténuation et de retard. D'autres défis sont la limitation des ressources, telles que le nombre d'antennes, la bande passante disponible et le rapport Signal / Bruit; sans parler des «imperfections» Wi-Fi, telles que les disparités de gain / phase entre les antennes et les problèmes de synchronisation entre l'émetteur et le récepteur. Dans cette thèse, notre objectif principal est de mettre en place un système en temps réel qui pourrait mesurer l'angle entre un émetteur et un récepteur en présence de tous les défis. En particulier, nous avons pris en compte tous les facteurs qui perturbent le problème d'estimation de l'angle articulaire et du délai et formulé un modèle de système en conséquence. Ces facteurs sont les suivants: Sampling Frequency offset (SFO), Carrier Frequency Offset (CFO), et Phase/Delay offsets à chaque antenne. Pour compenser l'efficacité de ces facteurs critiques, nous proposons une méthode d'étalonnage optimale pour compenser tous leurs effets. Cette thèse comprendra également d'autres méthodes théoriques qui doivent faire face au problème d'estimation de l'angle d'arrivée, à partir du point de vue de la compression et du traitement du signal. / In an indoor environment, the problem of extracting the Angle-of-Arrival of the Line-of-Sight component between a transmitter and Wi-Fi receiver using a SIMO link is the main concern of this thesis. One main challenge in doing so is due to the rich multipath channel that indoor environments enjoy. This is so because multipath results from the fact that the propagation channel consists of several obstacles and reflectors. Thus, the received signal arrives as an unpredictable set of reflections and/or direct waves each with its own degree of attenuation and delay. Other challenges are limitation of resources, such as number of antennas, available bandwidth, and Signal-to-Noise-Ratio; not to mention the Wi-Fi ”imperfections”, such as gain/phase mismatches between antennas and synchronisation issues between transmitter and receiver. In this thesis, our main focus is implementing a real-time system that could measure the angle between a transmitter and receiver in the presence of all challenges. In particular, we have taken into account all factors that perturb the Joint Angle and Delay estimation problem and formulated a system model accordingly. These factors are: Sampling Frequency offset (SFO), Carrier Frequency Offset (CFO), Phase and Delay offsets at each antenna. To compensate for the effect of these critical factors, we propose an offline calibration method to compensate for all their effects. This thesis will also include other theoretical methods that have to deal with Angle-of-Arrival Estimation problem from compressed sensing and signal processing point of views.

The electrical activity of skeletal muscle¡ªthe electromyogram (EMG)¡ªis of value to many different application areas, including ergonomics, clinical biomechanics and prosthesis control. For many applications the EMG is related to muscular tension, joint torque and/or applied forces. In these cases, a goal is for an EMG-torque model to emulate the natural relationship between the central nervous system and peripheral joints and muscles. This thesis mainly describes an experimental study which relates the simultaneous biceps/triceps surface EMG of 12 subjects to elbow torque at seven joint angles (ranging from 45¡ÃƒÂ£to 135¡ÃƒÂ£) during constant-posture, quasi-constant-torque contractions. The contractions ranged between 50% maximum voluntary contractions (MVC) extension and 50% MVC flexion. Advanced EMG amplitude (EMG¦Ãƒâ€™) estimation processors were investigated, and three nonlinear EMG¦Ãƒâ€™-torque models were evaluated. Results show that advanced (i.e., whitened, multiple-channel) EMG¦Ãƒâ€™ processors lead to improved joint torque estimation, compared to unwhitened, single-channel EMG¦Ãƒâ€™ processors. Depending on the joint angle, use of the multiple-channel whitened EMG¦Ãƒâ€™ processor with higher polynomial degrees produced a median error that was 50%-66% that found when using the single-channel, unwhitened EMG¦Ãƒâ€™ processor with a polynomial degree of 1. The best angle-specific model achieved a minimum error of 3.39% MVCF90 (i.e., error referenced to MVC at 90¢X flexion), yet it does not allow interpolation across angles. The best model which parameterizes the angle dependence achieved an error of 3.55% MVCF90. This thesis also summarizes other collaborative research contributions performed as part of this thesis. (1) Decomposition of needle EMG data was performed as part of a study to characterize motor unit behavior in patients with amyotrophic lateral sclerosis (ALS) [with Spaulding Rehabilitation Hospital, Boston, MA]. (2) EMG-force modeling of force produced at the finger tips was studied with the purpose of assessing the ability to determine two or more independent, continuous degrees of freedom of control from the muscles of the forearm [with WPI and Sherbrooke University]. (3) Identification of a nonlinear, dynamic EMG-torque relationship about the elbow was studied [WPI]. (4) Signal whitening preprocessing for improved classification accuracies in myoelectric control of a prosthesis was studied [with WPI and the University of New Brunswick].

The primary purpose of this thesis was to assess the effect of knee-joint angle on the neuromechanics of maximal and explosive contractions, specifically torque and neuromuscular activation, as well as the influence of isometric resistance training (RT) on these variables and thus joint angle specificity of training adaptations. It was found that electrode location had a pronounced effect on surface electromyography (sEMG) amplitude during maximum isometric voluntary contractions (MVCs) and moderate relationship between subcutaneous tissue thickness and sEMG amplitude (R2=0.31 up to 0.38) was reduced but not consistently removed by maximal M-Wave (MMAX) normalization [up to R2= 0.16 (peak-to-peak) and R2= 0.23 (Area)]. Thus, MMAX peak-to-peak was the better normalization parameter that removed the influence of electrode location and substantially reduced the influence of subcutaneous tissue thickness. Maximal torque-angle relationship presented an inverted U shape with both, agonist (measure by two different techniques) and antagonist neuromuscular activation both differing with knee-joint angle and thus, both likely contributing to the torque-angle relationship. Absolute explosive torque-angle relationship exhibited higher torques at mid-range knee joint angles in a similar manner to maximal strength, whilst the ability to explosively express the available torque (i.e. relative to maximal strength) revealed only subtle differences between joint angles. Agonist neuromuscular activation showed increases from extended to flexed positions during both maximum and explosive contractions (at all time points; ~6% to ~34%) and evoked contractile properties presented opposite patterns with twitch torque increasing (~5% to ~30%) and octet torque decreasing (~2% to ~14%) with knee flexion. Finally, after 4 weeks of RT at a 65° knee-joint angle evidence of joint angle specificity was provided from both within-group (greater gains at 3 angles than others) and between-group evidence (greater gains at 2 angles than others) for maximal strength but not for explosive strength and neuromuscular activation. In summary, this thesis demonstrated: (1) higher strength values at middle knee-joint positions than more flexed and/or extended positions during maximal and explosive contractions; (2) how agonist neuromuscular activation contributes to the beforementioned changes in strength; (3) how muscle contractile properties contribute to the explosive strength across knee-joint angles; and finally (4) that joint angle specificity has a neural basis.

Modelling of human motion is used in a wide range of applications. An important aspect of accurate representation of human movement is the ability to customize models to account for individual differences. The following work proposes a methodology using Hill-based candidate functions in the Fast Orthogonal Search (FOS) method to predict translational force at the wrist from flexion and extension torque at the elbow. Within this force estimation framework, it is possible to implicitly estimate subject-specific physiological parameters of Hill-based models of upper arm muscles. Surface EMG data from three muscles of the upper arm (biceps brachii, brachioradialis and triceps brachii) were recorded from 10 subjects as they performed isometric contractions at varying elbow joint angles. Estimated muscle activation level and joint kinematic data (joint angle and angular velocity) were utilized as inputs to the FOS model. The resulting wrist force estimations were found to be more accurate for models utilizing Hill-based candidate functions, than models utilizing candidate functions that were not physiologically relevant. Subject-specific estimates of optimal joint angle were determined via frequency analysis of the selected FOS candidate functions. Subject-specific optimal joint angle estimates demonstrated low variability and fell within the range of angles presented in the literature. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2008-10-30 01:32:01.606

No description available.

abstract: Individuals fluent in sign language who have at least one deaf parent are considered native signers while those with non-signing, hearing parents are non-native signers. Musculoskeletal pain from repetitive motion is more common from non-natives than natives. The goal of this study was twofold: 1) to examine differences in upper extremity (UE) biomechanical measures between natives and non-natives and 2) upon creating a composite measure of injury-risk unique to signers, to compare differences in scores between natives and non-natives. Non-natives were hypothesized to have less favorable biomechanical measures and composite injury-risk scores compared to natives. Dynamometry was used for measurement of strength, electromyography for ‘micro’ rest breaks and muscle tension, optical motion capture for ballistic signing, non-neutral joint angle and work envelope, a numeric pain rating scale for pain, and the modified Strain Index (SI) as a composite measure of injury-risk. There were no differences in UE strength (all p≥0.22). Natives had more rest (natives 76.38%; non-natives 26.86%; p=0.002) and less muscle tension (natives 11.53%; non-natives 48.60%; p=0.008) for non-dominant upper trapezius across the first minute of the trial. For ballistic signing, no differences were found in resultant linear segment acceleration when producing the sign for ‘again’ (natives 27.59m/s2; non-natives 21.91m/s2; p=0.20). For non-neutral joint angle, natives had more wrist flexion-extension motion when producing the sign for ‘principal’ (natives 54.93°; non-natives 46.23°; p=0.04). Work envelope demonstrated the greatest significance when determining injury-risk. Natives had a marginally greater work envelope along the z-axis (inferior-superior) across the first minute of the trial (natives 35.80cm; non-natives 30.84cm; p=0.051). Natives (30%) presented with a lower pain prevalence than non-natives (40%); however, there was no significant difference in the modified SI scores (natives 4.70 points; non-natives 3.06 points; p=0.144) and no association between presence of pain with the modified SI score (r=0.087; p=0.680). This work offers a comprehensive analysis of all the previously identified UE biomechanics unique to signers and helped to inform a composite measure of injury-risk. Use of the modified SI demonstrates promise, although its lack of association with pain does confirm that injury-risk encompasses other variables in addition to a signer’s biomechanics. / Dissertation/Thesis / Doctoral Dissertation Exercise and Nutritional Sciences 2018

A finite element (FE) model for the generation of single fiber action potentials (SFAPs) in a muscle undergoing various degrees of fiber shortening has been developed. The muscle is assumed to be fusiform with muscle fibers following a curvilinear path described by a Gaussian function. Different degrees of fiber shortening are simulated by changing the parameters of the fiber path and maintaining the volume of the muscle constant. The conductivity tensor is adapted to the muscle fiber orientation. At each point of the volume conductor, the conductivity of the muscle tissue in the direction of the fiber is larger than that in the transversal direction. Thus, the conductivity tensor changes point-by-point with fiber shortening, adapting to the fiber paths. An analytical derivation of the conductivity tensor is provided. The volume conductor is then studied with an FE approach using the analytically derived conductivity tensor (Mesin, Joubert, Hanekom, Merletti&Farina 2006). Representative simulations of SFAPs with the muscle at different degrees of shortening are presented. It is shown that the geometrical changes in the muscle, which imply changes in the conductivity tensor, determine important variations in action potential shape, thus affecting its amplitude and frequency content. The model is expanded to include the simulation of motor unit action potentials (MUAPs). Expanding the model was done by assigning each single fiber (SF) in the motor unit (MU) a random starting position chosen from a normal distribution. For the model 300 SFs are included in an MU, with an innervation zone spread of 12 mm. Only spatial distribution was implemented. Conduction velocity (CV) was the same for all fibers of the MU. Representative simulations for the MUAPs with the muscle at different degrees of shortening are presented. The influence of interelectrode distance and angular displacement are also investigated as well as the influence of the inclusion of the conductivity tensor. It has been found that the interpretation of surface electromyography during movement or joint angle change is complicated owing to geometrical artefacts i.e. the shift of the electrodes relative to the muscle fibers and also because of the changes in the conductive properties of the tissue separating the electrode from the muscle fibers. Detection systems and electrode placement should be chosen with care. The model provides a new tool for interpreting surface electromyography (sEMG) signal features with changes in muscle geometry, as happens during dynamic contractions. / Dissertation (MEng (Bio-Engineering))--University of Pretoria, 2008. / Electrical, Electronic and Computer Engineering / MEng (Bio-Engineering) / unrestricted