Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníese por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Classificação de atividade eletromiográfia facial de indivíduos saudáveis e com hanseníase por meio de máquina de vetores de suporte

A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

Application of a new method in the study of pelvic floor muscle passive properties in continent women

The aim of this study was to present a new methodology for evaluating the pelvic floor muscle (PFM) passive properties. The properties were assessed in 13 continent women using an intra-vaginal dynamometric speculum and EMG (to ensure the subjects were relaxed) in four different conditions: (1) forces recorded at minimal aperture (initial passive resistance); (2) passive resistance at maximal aperture; (3) forces and passive elastic stiffness (PES) evaluated during five lengthening and shortening cycles; and (4) percentage loss of resistance after 1 min of sustained stretch. The PFMs and surrounding tissues were stretched, at constant speed, by increasing the vaginal antero-posterior diameter; different apertures were considered. Hysteresis was also calculated. The procedure was deemed acceptable by all participants. The median passive forces recorded ranged from 0.54 N (interquartile range 1.52) for minimal aperture to 8.45 N (interquartile range 7.10) for maximal aperture while the corresponding median PES values were 0.17 N/mm (interquartile range 0.28) and 0.67 N/mm (interquartile range 0.60). Median hysteresis was 17.24 N∗mm (interquartile range 35.60) and the median percentage of force losses was 11.17% (interquartile range 13.33). This original approach to evaluating the PFM passive properties is very promising for providing better insight into the patho-physiology of stress urinary incontinence and pinpointing conservative treatment mechanisms.

Effects of pelvic floor muscle rehabilitation on PFM function and morphology in older women

Aims The purpose of this study was to examine the effect of a pelvic floor muscle (PFM) rehabilitation program on incontinence symptoms, PFM function, and morphology in older women with SUI. Methods Women 60 years old and older with at least weekly episodes of SUI were recruited. Participants were evaluated before and after a 12-week group PFM rehabilitation intervention. The evaluations included 3-day bladder diaries, symptom, and quality of life questionnaires, PFM function testing with dynamometry (force) and electromyography (activation) during seven tasks: rest, PFM maximum voluntary contraction (MVC), straining, rapid-repeated PFM contractions, a 60 sec sustained PFM contraction, a single cough and three repeated coughs, and sagittal MRI recorded at rest, during PFM MVCs and during straining to assess PFM morphology. Results Seventeen women (68.9 ± 5.5 years) participated. Following the intervention the frequency of urine leakage decreased and disease-specific quality of life improved significantly. PFM function improved significantly: the participants were able to perform more rapid-repeated PFM contractions; they activated their PFMs sooner when coughing and they were better able to maintain a PFM contraction between repeated coughs. Pelvic organ support improved significantly: the anorectal angle was decreased and the urethrovescial junction was higher at rest, during contraction and while straining. Conclusions This study indicated that improvements in urine leakage were produced along with improvements in PFM co-ordination (demonstrated by the increased number of rapid PFM contractions and the earlier PFM activation when coughing), motor-control, pelvic organ support.

Application of a new method in the study of pelvic floor muscle passive properties in continent women

The aim of this study was to present a new methodology for evaluating the pelvic floor muscle (PFM) passive properties. The properties were assessed in 13 continent women using an intra-vaginal dynamometric speculum and EMG (to ensure the subjects were relaxed) in four different conditions: (1) forces recorded at minimal aperture (initial passive resistance); (2) passive resistance at maximal aperture; (3) forces and passive elastic stiffness (PES) evaluated during five lengthening and shortening cycles; and (4) percentage loss of resistance after 1 min of sustained stretch. The PFMs and surrounding tissues were stretched, at constant speed, by increasing the vaginal antero-posterior diameter; different apertures were considered. Hysteresis was also calculated. The procedure was deemed acceptable by all participants. The median passive forces recorded ranged from 0.54 N (interquartile range 1.52) for minimal aperture to 8.45 N (interquartile range 7.10) for maximal aperture while the corresponding median PES values were 0.17 N/mm (interquartile range 0.28) and 0.67 N/mm (interquartile range 0.60). Median hysteresis was 17.24 N∗mm (interquartile range 35.60) and the median percentage of force losses was 11.17% (interquartile range 13.33). This original approach to evaluating the PFM passive properties is very promising for providing better insight into the patho-physiology of stress urinary incontinence and pinpointing conservative treatment mechanisms.

Effects of pelvic floor muscle rehabilitation on PFM function and morphology in older women

Aims The purpose of this study was to examine the effect of a pelvic floor muscle (PFM) rehabilitation program on incontinence symptoms, PFM function, and morphology in older women with SUI. Methods Women 60 years old and older with at least weekly episodes of SUI were recruited. Participants were evaluated before and after a 12-week group PFM rehabilitation intervention. The evaluations included 3-day bladder diaries, symptom, and quality of life questionnaires, PFM function testing with dynamometry (force) and electromyography (activation) during seven tasks: rest, PFM maximum voluntary contraction (MVC), straining, rapid-repeated PFM contractions, a 60 sec sustained PFM contraction, a single cough and three repeated coughs, and sagittal MRI recorded at rest, during PFM MVCs and during straining to assess PFM morphology. Results Seventeen women (68.9 ± 5.5 years) participated. Following the intervention the frequency of urine leakage decreased and disease-specific quality of life improved significantly. PFM function improved significantly: the participants were able to perform more rapid-repeated PFM contractions; they activated their PFMs sooner when coughing and they were better able to maintain a PFM contraction between repeated coughs. Pelvic organ support improved significantly: the anorectal angle was decreased and the urethrovescial junction was higher at rest, during contraction and while straining. Conclusions This study indicated that improvements in urine leakage were produced along with improvements in PFM co-ordination (demonstrated by the increased number of rapid PFM contractions and the earlier PFM activation when coughing), motor-control, pelvic organ support.

New methods for movement technique development in cross-country skiing using mathematical models and simulation

This Licentiate Thesis is devoted to the presentation and discussion of some new contributions in applied mathematics directed towards scientific computing in sports engineering. It considers inverse problems of biomechanical simulations with rigid body musculoskeletal systems especially in cross-country skiing. This is a contrast to the main research on cross-country skiing biomechanics, which is based mainly on experimental testing alone. The thesis consists of an introduction and five papers. The introduction motivates the context of the papers and puts them into a more general framework. Two papers (D and E) consider studies of real questions in cross-country skiing, which are modelled and simulated. The results give some interesting indications, concerning these challenging questions, which can be used as a basis for further research. However, the measurements are not accurate enough to give the final answers. Paper C is a simulation study which is more extensive than paper D and E, and is compared to electromyography measurements in the literature. Validation in biomechanical simulations is difficult and reducing mathematical errors is one way of reaching closer to more realistic results. Paper A examines well-posedness for forward dynamics with full muscle dynamics. Moreover, paper B is a technical report which describes the problem formulation and mathematical models and simulation from paper A in more detail. Our new modelling together with the simulations enable new possibilities. This is similar to simulations of applications in other engineering fields, and need in the same way be handled with care in order to achieve reliable results. The results in this thesis indicate that it can be very useful to use mathematical modelling and numerical simulations when describing cross-country skiing biomechanics. Hence, this thesis contributes to the possibility of beginning to use and develop such modelling and simulation techniques also in this context.

Proprioception in ankle sprain from exercises and bandages

Ankle sprains are the most common injuries in sports, usually causing damage to the lateral ligaments. Recurrence has as usual result permanent instability, and thus loss of proprioception. This fact, together with residual symptoms, is what is known as chronic ankle instability, CAI, or FAI, if it is functional. This problem tries to be solved by improving musculoskeletal stability and proprioception by the application of bandages and performing exercises. The aim of this study has been to review articles (meta-analisis, systematic reviews and revisions) published in 2009-2015 in PubMed, Medline, ENFISPO and BUCea, using keywords such as “sprain instability”, “sprain proprioception”, “chronic ankle instability”. Evidence affirms that there does exist decreased proprioception in patients who suffer from CAI. Rehabilitation exercise regimen is indicated as a treatment because it generates a subjective improvement reported by the patient, and the application of bandages works like a sprain prevention method limiting the range of motion, reducing joint instability and increasing confidence during exercise. As podiatrists we should recommend proprioception exercises to all athletes in a preventive way, and those with CAI or FAI, as a rehabilitation programme, together with the application of bandages. However, further studies should be generated focusing on ways of improving proprioception, and on the exercise patterns that provide the maximum benefit.

Objective Methods for Characterizing Physical Exposures which may contribute to Work-related Musculoskeletal Disorders in Agricultural Workers

Thesis (Ph.D.)--University of Washington, 2016-08

IoT Based Pain Management using Physiological Parameters

The continuous technology evaluation is benefiting our lives to a great extent. The evolution of Internet of things and deployment of wireless sensor networks is making it possible to have more connectivity between people and devices used extensively in our daily lives. Almost every discipline of daily life including health sector, transportation, agriculture etc. is benefiting from these technologies. There is a great potential of research and refinement of health sector as the current system is very often dependent on manual evaluations conducted by the clinicians. There is no automatic system for patient health monitoring and assessment which results to incomplete and less reliable heath information. Internet of things has a great potential to benefit health care applications by automated and remote assessment, monitoring and identification of diseases. Acute pain is the main cause of people visiting to hospitals. An automatic pain detection system based on internet of things with wireless devices can make the assessment and redemption significantly more efficient. The contribution of this research work is proposing pain assessment method based on physiological parameters. The physiological parameters chosen for this study are heart rate, electrocardiography, breathing rate and galvanic skin response. As a first step, the relation between these physiological parameters and acute pain experienced by the test persons is evaluated. The electrocardiography data collected from the test persons is analyzed to extract interbeat intervals. This evaluation clearly demonstrates specific patterns and trends in these parameters as a consequence of pain. This parametric behavior is then used to assess and identify the pain intensity by implementing machine learning algorithms. Support vector machines are used for classifying these parameters influenced by different pain intensities and classification results are achieved. The classification results with good accuracy rates between two and three levels of pain intensities shows clear indication of pain and the feasibility of this pain assessment method. An improved approach on the basis of this research work can be implemented by using both physiological parameters and electromyography data of facial muscles for classification.

Perceção de emoções no canto: a importância dos estímulos auditivo e visual

Este estudo pretendeu examinar a importância dos estímulos auditivo (interpre-tação vocal do cantor) e visual (expressão facial do cantor) na perceção de emo-ções pelo público de uma performance de canto. Para tal, foram gravados, atra-vés de vídeo e áudio, dois cantores a interpretar pequenas frases melódicas com a intenção de expressar, isoladamente, as seis emoções básicas: alegria, tristeza, raiva, medo, surpresa e nojo. Para validar a expressividade dos canto-res, foi medida, através de eletromiografia, a atividade dos músculos faciais du-rante a performance da emoção e foram apresentadas as gravações áudio a um painel de especialistas que as caracterizaram em termos acústicos. Com base nas gravações audiovisuais dos cantores, foi criado um teste percetual no qual se pretendia que o ouvinte reconhecesse a emoção comunicada a partir apenas do áudio, apenas do vídeo, ou ambos. Comparando as respostas dadas, os re-sultados evidenciaram que o estímulo visual é mais eficaz do que o auditivo, e que a junção dos dois estímulos é a modalidade mais eficiente na perceção de emoções pelo público de uma performance de canto.

Avaliação do comportamento ingestivo utilizando eletromiografia de superfície do músculo masseter

Physiologists and animal scientists try to understand the relationship between ruminants and their environment. The knowledge about feeding behavior of these animals is the key to maximize the production of meat and milk and their derivatives and ensure animal welfare. Within the area called precision farming, one of the goals is to find a model that describes animal nutrition. Existing methods for determining the consumption and ingestive patterns are often time-consuming and imprecise. Therefore, an accurate and less laborious method may be relevant for feeding behaviour recognition. Surface electromyography (sEMG) is able to provide information of muscle activity. Through sEMG of the muscles of mastication, coupled with instrumentation techniques, signal processing and data classification, it is possible to extract the variables of interest that describe chewing activity. This work presents a new method for chewing pattern evaluation, feed intake prediction and for the determination of rumination, food and daily rest time through ruminant animals masseter muscle sEMG signals. Short-term evaluation results are shown and discussed, evidencing employed methods viability.

Gait analysis of the hind limb in Labrador Retrievers with and without cranial cruciate ligament disease

Cranial cruciate ligament (CCL) deficiency is the leading cause of lameness affecting the stifle joints of large breed dogs, especially Labrador Retrievers. Although CCL disease has been studied extensively, its exact pathogenesis and the primary cause leading to CCL rupture remain controversial. However, weakening secondary to repetitive microtrauma is currently believed to cause the majority of CCL instabilities diagnosed in dogs. Techniques of gait analysis have become the most productive tools to investigate normal and pathological gait in human and veterinary subjects. The inverse dynamics analysis approach models the limb as a series of connected linkages and integrates morphometric data to yield information about the net joint moment, patterns of muscle power and joint reaction forces. The results of these studies have greatly advanced our understanding of the pathogenesis of joint diseases in humans. A muscular imbalance between the hamstring and quadriceps muscles has been suggested as a cause for anterior cruciate ligament rupture in female athletes. Based on these findings, neuromuscular training programs leading to a relative risk reduction of up to 80% has been designed. In spite of the cost and morbidity associated with CCL disease and its management, very few studies have focused on the inverse dynamics gait analysis of this condition in dogs. The general goals of this research were (1) to further define gait mechanism in Labrador Retrievers with and without CCL-deficiency, (2) to identify individual dogs that are susceptible to CCL disease, and (3) to characterize their gait. The mass, location of the center of mass (COM), and mass moment of inertia of hind limb segments were calculated using a noninvasive method based on computerized tomography of normal and CCL-deficient Labrador Retrievers. Regression models were developed to determine predictive equations to estimate body segment parameters on the basis of simple morphometric measurements, providing a basis for nonterminal studies of inverse dynamics of the hind limbs in Labrador Retrievers. Kinematic, ground reaction forces (GRF) and morphometric data were combined in an inverse dynamics approach to compute hock, stifle and hip net moments, powers and joint reaction forces (JRF) while trotting in normal, CCL-deficient or sound contralateral limbs. Reductions in joint moment, power, and loads observed in CCL-deficient limbs were interpreted as modifications adopted to reduce or avoid painful mobilization of the injured stifle joint. Lameness resulting from CCL disease affected predominantly reaction forces during the braking phase and the extension during push-off. Kinetics also identified a greater joint moment and power of the contralateral limbs compared with normal, particularly of the stifle extensor muscles group, which may correlate with the lameness observed, but also with the predisposition of contralateral limbs to CCL deficiency in dogs. For the first time, surface EMG patterns of major hind limb muscles during trotting gait of healthy Labrador Retrievers were characterized and compared with kinetic and kinematic data of the stifle joint. The use of surface EMG highlighted the co-contraction patterns of the muscles around the stifle joint, which were documented during transition periods between flexion and extension of the joint, but also during the flexion observed in the weight bearing phase. Identification of possible differences in EMG activation characteristics between healthy patients and dogs with or predisposed to orthopedic and neurological disease may help understanding the neuromuscular abnormality and gait mechanics of such disorders in the future. Conformation parameters, obtained from femoral and tibial radiographs, hind limb CT images, and dual-energy X-ray absorptiometry, of hind limbs predisposed to CCL deficiency were compared with the conformation parameters from hind limbs at low risk. A combination of tibial plateau angle and femoral anteversion angle measured on radiographs was determined optimal for discriminating predisposed and non-predisposed limbs for CCL disease in Labrador Retrievers using a receiver operating characteristic curve analysis method. In the future, the tibial plateau angle (TPA) and femoral anteversion angle (FAA) may be used to screen dogs suspected of being susceptible to CCL disease. Last, kinematics and kinetics across the hock, stifle and hip joints in Labrador Retrievers presumed to be at low risk based on their radiographic TPA and FAA were compared to gait data from dogs presumed to be predisposed to CCL disease for overground and treadmill trotting gait. For overground trials, extensor moment at the hock and energy generated around the hock and stifle joints were increased in predisposed limbs compared to non predisposed limbs. For treadmill trials, dogs qualified as predisposed to CCL disease held their stifle at a greater degree of flexion, extended their hock less, and generated more energy around the stifle joints while trotting on a treadmill compared with dogs at low risk. This characterization of the gait mechanics of Labrador Retrievers at low risk or predisposed to CCL disease may help developing and monitoring preventive exercise programs to decrease gastrocnemius dominance and strengthened the hamstring muscle group.

Ambiente para aquisição e processamento de sinal eletromiográfico de superfície

In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.