Standing and sidelying external rotation exercises produce high activation of the deltoid and infraspinatus. Holding a towel roll under the arm at 30° shoulder abduction during these exercises may decrease deltoid activity and increase infraspinatus activity. The objective was to determine if the addition of a towel under the arm during standing and sidelying external rotation affects EMG activity of the infraspinatus, middle and posterior deltoid, and pectoralis major, compared to the no towel condition. 20 male volunteers (age; 26 ± 3, height; 1.80 m ± .07 m, weight; 77 kg ± 10 kg) had right dominant hand, bilaterally healthy shoulders with no current cervical pathology, and no skin infection or lesion of the shoulder. Maximal voluntary isometric contraction for the infraspinatus, middle and posterior deltoid, and pectoralis major and external rotation in standing and sidelying with and without a towel roll were performed. Normalized average and peak EMG amplitude was compared between the towel conditions during standing and sidelying external rotation. Both infraspinatus and pectoralis major activity had no significant differences between the towel conditions in standing and sidelying (P > .05). In standing and sidelying, posterior deltoid activity was significantly greater with a towel roll (.008 ≤ P ≤ .035 and .008 ≤ P ≤ .018, respectively). Middle deltoid activity had no significant differences between the towel conditions in standing (P > .05). However, in sidelying, middle deltoid activity was significantly lower with a towel roll (.011 ≤ P ≤ .000). The only muscle activation change during standing external rotation with the application of a towel roll was an increase of the posterior deltoid. During sidelying external rotation, holding a towel roll decreased middle deltoid activity and increased posterior deltoid activity. Thus, this study indicates that holding a towel roll under the arm during standing external rotation exercise does not appear to produce desired effects on muscle activation. However, application of a towel roll under the arm could be recommended during sidelying external rotation exercise in order to possibly reduce the superior glide of the humerus, due to decrease muscle activation of the middle deltoid.

Projektet syftade till att undersöka skillnaden på tre olika utformningar av fotledsortoser när det kommer till muskel-aktivitet i underbenet vid gång. Det genomfördes på grund av att det finns få studier på hur olika fotledsortoser förhåller sig till varandra, därmed är kunskapen begränsad. Tillvägagångssättet var att skriva ett matlabskript som manipulerade och analyserade all indata och levererade jämförbara resultat för de enskilda ortoserna. Analysen skedde i fyra övergripande moment där det första var att manipulera EMG:ts rådata för att förenkla analysen av den, det andra momentet var att definiera stegtider utifrån fotsuletrycksdata. Tredje momentet innefattade att manipulera referensdata på samma sätt som i moment ett och det fjärde var att uttrycka EMG-data i procent av referensdatan.Efter att EMG-data analyserats så jämfördes de olika ortoserna genom att medelvärden från samtliga försökspersoner beräknades i Excel. Resultaten visade att muskelaktiviteten i "Triceps Surae" överlag verkar minska med ökad plantarflexion. Slutsatsen fick delas upp muskel för muskel och har ingen genomgående trend utan slutsatsen blev olika för varje muskel. / The aim of this project is to investigate the differences in muscle activity of the lower leg between three types of ankle foot orthoses. The reason behind the project is that there is little knowledge about differences between different types of orthoses. The method used to tackle this task was to write a Matlab script that manipulated and anlyzed all the data required to yield a result for each individual orthoses that then could be used to compare them to each other. This was done in four major steps, the first of which was to manipulate the EMG-data of the chosen file so that it became easier to analyze, the second step was to use the data from a pressure sole to determine when steps started and ended. Thirdly, the reference data was manipulated in the same way as in step one. The fourth and final step was to express the chosen file in percent of the reference data. Finally, Excel was used to compare the different orthoses by calculating mean values from the test subjects data. The results showed that the muscel actvity in "Triceps Surae" seems to decrease with increased plantarflexion.The conclussion had to be divided into one conclussion per muscle, the different conlussions differed for every muscle.

Powered exoskeletons can assist patients suffering from motor dysfunctions. Recent researches are focused on how to improve the communication system between patient and device. Further research is needed in order to design an EMG based robotic assistive device able to convey intended motions to the patient. The primary need is the understanding of how EMG patterns from different muscles contribute to motions. Studies on muscle synergy have shown how different muscles of lower limbs contribute to gait. This study is aimed to expand the analysis to motions other than gait by analysing ten muscles around the right knee joint. The chosen muscle were soleus, gastrocnemius medialis, gastrocnemius lateralis, peroneus longus, tibialis anterior, rectus femoris, vastus medialis, vastus lateralis, biceps femoris and semitendinosus. The main hypothesis is that specific movements are controlled by specific muscle synergies. Motion data and EMG data of eight healthy subjects have been compared in order to outline a coordination pattern specific to four different movements: gait, gait stop and balance, sit to stand and stand to sit. Through the analysis of EMG signals, three muscle synergies have been identified including muscles from the same group, i.e. four plantar flexors, three quadriceps and two hamstrings. It was possible to conclude that the four movements were controlled by the same muscle synergies with different coordination patterns. Further research is recommended to expand the knowledge about muscle synergies.

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Graph Signal Processing (GSP) has been used in the analysis of functional Magnetic Resonance Imaging(fMRI). As a holistic view of brain function and the connections between and within brain regions, by structuring data as node points within the brain and modelling the edge connections between nodes. Many studies have used GSP with Blood Oxygenation Level Dependent (BOLD) imaging of the brain and brain activation. Meanwhile, the methodology has seen little use in muscle imaging. Similar to brain BOLD, muscle BOLD (mBOLD) also aims to demonstrate muscle activation. Muscle BOLD depends on oxygenation, vascularization, fibre type, blood flow, and haemoglobin count. Nevertheless the mBOLD signal still follows muscle activation closely. Electromyography (EMG) is another modality for measuring muscle activation. Both mBOLD and EMG can be represented and analyzed with GSP. In order to better understand muscle activation during contraction the proposed method focused on using GSP to model mBOLD data both alone and jointly with EMG. Simultaneous mBOLD imaging and EMG recording of the calf muscles was performed, creating a multimodal dataset. A generalized filtering methodology was developed for the removal of the MRI gradient artifact in EMG sensors within the MR bore. The filtered data was then used to generate a GSP model of the muscle, focusing on gastrocnemius, soleus, and tibialis anterior muscles. The graph signals were constructed along two edge connection dimensions; coherence and fractility. For the standalone mBOLD graph signal models, the models’ goodness of fits were 1.3245 × 10-05 and 0.06466 for coherence and fractility respectively. The multimodal models showed values of 2.3109 × -06 and 0.0014799. These results demonstrate the promise of modelling muscle activation with GSP and its ability to incorporate multimodal data into a singular model. These results set the stage for future investigations into using GSP to represent muscle with mBOLD, EMG, and other biosignal modalities. / Thesis / Master of Applied Science (MASc) / Magnetic Resonance Imaging(MRI) and electromyography (EMG) are techniques used in the analysis of muscle, for detecting injury or deepening the understanding of muscle function. Graph Signal Processing (GSP) is a methodology used to represent data and the information flow between positions. While GSP has been used in modelling the brain, applications to muscle are scarce. This work aimed to model muscle activation using GSP methods, using both MRI and EMG data. To do so, a method for being able to simultaneously record MRI and EMG data was developed through hardware construction and the software implementation of EMG signal filtering. The collected data were then used to construct multiple GSP models based on the coherence and complexity of the signals, the goodness of fit for each of the constructed models were then compared. In conclusion, it is feasible to use GSP to model muscle activity with multimodal MRI and EMG data. This shows promise for future investigations into the applications of GSP to muscle research.

<p> The interrelationship of force, surface elecrograms (EMG) and joint position for static voluntary contractions of Quadriceps Femoris muscle group in man were investigated before and during partial curarization induced by d-tubocurarine. </p> <p> Four normal male volunteers were studied. Each performed a series of brief isometric contractions (by extension of the lower leg against resistance) at different levels of force and at three knee-joint positions while lying in the supine position. All series were repeated for both a normal state and a partially paralyzed state under the :influence of curare. Torque generated about the knee-joint was measured with a Cybex isokinetic system and the nyoelectric activity of three quadriceps muscles was monitored using bipolar surface electrodes. </p> <p> Traditional parameters of nyoelectric activity (mean-rectified-EMG [MRE], and root-mean-squared-DG [RMSE]) were calculated using a minicomputer (PDPll/34), which had also acquired and processed the data. In addition, EMG power spectra were computed by Fast Fourier Transform techniques in an attempt to provide further insight into the effects of curare on human muscle. </p> <p> In order to provide a basis for comparison of the normal state with the parially curarized state, force-EMG relationships were computed for each subject, muscle, knee-joint angle, and condition. Statistical methods (three-way ANOVA' s) were then employed to both quantify any differences that may have existed between the two states and to identify sources of differences within each state. A similar statistically- based comparison of the power spectra was undertaken utilizing several indices that described the shape of the spectra. A general description of the activities of the quadriceps femoris muscles followed after collating all the information that the surface DIG provided in conjunction with the external forces measured. </p> <p> It was concluded that curare did not have any significant effects on the force-EMG relationship. There appeared to be a slight effect of curare on the power spectra however, with a general trend of increasing lower frequency power. The greatest source of variation of force-EMG relationships and power spectra was attributed to the position of the knee-joint. </p> / Thesis / Master of Engineering (MEngr)

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No description available.

The relationship between sEMG signals and muscle force, and associated joint torque, is an object of study for clinical applications such as rehabilitation robotics and commercial applications as wearable motion control devices. The information type and quality obtained by sEMG can impact the classification and prediction accuracy of ankle joint torque. In this thesis project, HD-sEMG based data was collected together with ankle joint torque measurements from 5 subjects during MVIC of plantarflexors and dorsiflexors. Machine learning approaches ideally suited for nonlinear regression tasks, such as MLP and LSTM, have been implemented and evaluated to best predict joint torque profiles given extracted features from sEMG data. An evaluation of machine learning performances using HD-sEMG data over bipolar sEMG data has been conducted in intra-session, inter-subjective and intra-subjective study cases.

Running injuries have been linked to poor lower extremity dynamic alignment, increased whole body and joint loading, and insufficient modulation of stiffness throughout stance phase. Upper body muscle activity and movement have a relationship to lower body dynamics; however, the literature has largely neglected their role during running. To date, biomechanical gait analysis has primarily focused on lower extremity mechanics and muscle activation patterns with no studies investigating the role of functional muscle synergies on stability and loading during running. Therefore, the primary objective of this project is to determine the role of the Back Functional Line (BFL), via measure of latissimus dorsi (LD), gluteus maximus (GM), and vastus lateralis (VL) muscle activity, during running and to determine their influence on lower extremity kinematics and kinematic predictors of loading that are linked to running-related injuries (RRI). We used conditions of arm swing constraint to manipulate the action of the LD and investigate the response in GM and VL muscles. Our main variables of interest include: 1) BFL muscle activity, specifically mean and peak amplitude, onset, and co-activation of the LD and GM 2) frontal plane lower extremity kinematics, and 3) kinematic predictors of kinetics, specifically foot inclination angle at initial contact and vertical COM displacement. Twenty healthy recreational runners (10 M; 10 F) participated in this study. Male runners tended to be slighter older with a higher weekly running mileage and longer running history. All participants were between the ages of 18 and 55 years old and consistently ran at least once per week. Participants ran under three arm conditions - free arm swing, unilateral arm swing constraint, and bilateral arm swing constraint. During the running trials, surface EMG and lower extremity kinematics were collected over the gait cycle. We operationally defined the primary BFL as the muscle synergy composed of the non-dominant upper extremity (i.e., constrained side during unilateral condition) LD muscle, the dominant GM muscle, and the dominant VL muscle. The secondary BFL was defined as the dominant upper extremity (i.e., unconstrained during unilateral condition) LD muscle, the non-dominant GM muscle, and the non-dominant VL muscle. Primary and secondary BFL muscle synergy activity were analyzed during two specific phases of gait - the pre-activation (PA) phase and the loading response (LR) phase. In support of the hypothesis, the primary BFL LD mean amplitude decreased during both the PA and LR phases of gait. GM and VL muscle mean amplitude demonstrated a varied response. During the PA phase, both the GM and VL muscles increased during the unilateral condition and decreased during the bilateral condition. During LR phase, GM and VL muscles increased during both arm swing constraint conditions. The highest increase in amplitude was seen during the unilateral condition. Peak amplitudes for each muscle did not change dramatically across conditions for either the PA or LR phases of gait. Secondary BFL LD and GM mean and peak amplitude increased during both the PA and LR phases of gait, with changes during the LR phase reaching significance for both muscles. Secondary BFL VL also increased in mean and peak amplitude during the bilateral constraint condition. GM and VL mean and peak muscle amplitude were significantly correlated during the LR phase, but not for the PA phase. This indicates that the lower extremity muscles of the BFL (GM and VL) may not be preparing for impact similarly but are adjusting muscle activity in a similar fashion as the lower limb is loaded. The increase in muscle amplitude for secondary BFL muscles, particularly during the LR phase of gait, may have resulted from a difference between lower limb strength or lower extremity single leg stability. Onset of muscle activity during loading response did not significantly differ across conditions for the LD, GM, or VL muscles, however, analysis of co-activation demonstrated that LD and GM were in-phase throughout the gait cycle. This suggests that this portion of the BFL may be acting together to stabilize the lumbopelvic-hip complex (LPHC) during running. LD and GM appeared to be co-activated throughout the gait cycle regardless of arm swing variation. Instability, either from asymmetrical movement patterns or poor single leg stability may contribute to the activation of the BFL muscle synergy. GM increased during the unilateral arm swing constraint during both phase and for both BFL synergies, indicating that asymmetrical movement patterns may induce a potential instability or an unstable state requiring the need for greater stability around the LPHC. Knee frontal plane kinematics changed significantly across conditions. Knee abduction angle showed the greatest increase during the unilateral arm swing constraint condition suggesting that asymmetrical movement patterns effect lower extremity mechanics more so than symmetrical patterns (i.e., bilateral arm swing restriction or free arm swing). Hip adduction and contralateral pelvic drop angles did not differ significantly across conditions. Our study did not find a significant relationship between BFL muscle activity and knee abduction angles. Participants demonstrated larger knee abduction angles on their non-dominant limb at midstance. The corresponding (secondary) BFL LD and GM demonstrated a significant increase during the LR phase. This may indicate that BFL muscle activity is engaged when the need for lower limb stability is greater, either due to poor single leg dynamic control or abnormal frontal plane mechanics. Kinematic predictors of joint and whole-body loading differed across conditions. Vertical COM displacement was significantly decreased during the bilateral arm swing constraint condition. Foot inclination angle at initial contact did not significantly change with arm swing constraint. Differences were found between right and left lower extremity foot strikes (i.e., foot inclination angle) across all conditions; the non-dominant limb demonstrated greater plantarflexion during initial contact. Knee flexion angle at initial contact and peak knee flexion during stance did not demonstrate a significant change. Muscle activity was not significantly correlated to kinematic predictors. Spatiotemporal measures altered with arm swing suppression. Stride length decreased and step rate increased significantly. Taken together, these results suggest that runners alter spatiotemporal measures more so than sagittal plane kinematics when adjusting to arm swing suppression. The role of the BFL muscle synergy during running remains unclear. Asymmetrical movement patterns and arm swing restriction appear to influence BFL muscle activity and lower extremity kinematics. Single leg stability, particularly during the LR phase, may alter BFL muscle activity due to the need for increased stabilization of the loaded limb and the LPHC. Future research is needed to determine how these variables impact BFL muscle activation and whether injured runners respond differently to arm swing constraint during running. / Physical Therapy