The effect of accelerometer location on the classification of single-site forearm mechanomyograms

<p>Abstract</p> <p>Background</p> <p>Recently, pattern recognition methods have been deployed in the classification of multiple activation states from mechanomyogram (MMG) signals for the purpose of controlling switching interfaces. Given the propagative properties of MMG signals, it has been suggested that MMG classification should be robust to changes in sensor placement. Nonetheless, this purported robustness remains speculative to date. This study sought to quantify the change in classification accuracy, if any, when a classifier trained with MMG signals from the muscle belly, is subsequently tested with MMG signals from a nearby location.</p> <p>Methods</p> <p>An arrangement of 5 accelerometers was attached to the flexor carpi radialis muscle of 12 able-bodied participants; a reference accelerometer was located over the muscle belly, two peripheral accelerometers were positioned along the muscle's transverse axis and two more were aligned to the muscle's longitudinal axis. Participants performed three classes of muscle activity: wrist flexion, wrist extension and semi-pronation. A collection of time, frequency and time-frequency features were considered and reduced by genetic feature selection. The classifier, trained using features from the reference accelerometer, was tested with signals from the longitudinally and transversally displaced accelerometers.</p> <p>Results</p> <p>Classification degradation due to accelerometer displacement was significant for all participants, and showed no consistent trend with the direction of displacement. Further, the displaced accelerometer signals showed task-dependent de-correlations with respect to the reference accelerometer.</p> <p>Conclusions</p> <p>These results indicate that MMG signal features vary with spatial location and that accelerometer displacements of only 1-2 cm cause sufficient feature drift to significantly diminish classification accuracy. This finding emphasizes the importance of consistent sensor placement between MMG classifier training and deployment for accurate control of switching interfaces.</p

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity

Synchronization of muscular oscillations between two subjects during isometric interaction

Muscles oscillate with a frequency around 10 Hz. But what happens with myofascial oscillations, if two neuromuscular systems interact? The purpose of this study was to examine this question, initially, on the basis of a case study. Oscillations of the triceps brachii muscles of two subjects were determined through mechanomyography (MMG) during isometric interaction. The MMG-signals were analyzed concerning the interaction of the two subjects with algorithms of nonlinear dynamics. In this case study it could be shown, that the muscles of both neuromuscular systems also oscillate with the known frequency (here 12 Hz) during interaction. Furthermore, both subjects were able to adapt their oscillations against each other. This adjustment induced a significant ( &lt; .05) coherent behavior, which was characterized by a phase shifting of approximately 90°. The authors draw the conclusion, that the complementary neuromuscular partners potentially have the ability of mutual synchronization

Design of a low-cost sensor matrix for use in human-machine interactions on the basis of myographic information

Myographic sensor matrices in the field of human-machine interfaces are often poorly developed and not pushing the limits in terms of a high spatial resolution. Many studies use sensor matrices as a tool to access myographic data for intention prediction algorithms regardless of the human anatomy and used sensor principles. The necessity for more sophisticated sensor matrices in the field of myographic human-machine interfaces is essential, and the community already called out for new sensor solutions. This work follows the neuromechanics of the human and designs customized sensor principles to acquire the occurring phenomena. Three low-cost sensor modalities Electromyography, Mechanomyography, and Force Myography) were developed in a miniaturized size and tested in a pre-evaluation study. All three sensors comprise the characteristic myographic information of its modality. Based on the pre-evaluated sensors, a sensor matrix with 32 exchangeable and high-density sensor modules was designed. The sensor matrix can be applied around the human limbs and takes the human anatomy into account. A data transmission protocol was customized for interfacing the sensor matrix to the periphery with reduced wiring. The designed sensor matrix offers high-density and multimodal myographic information for the field of human-machine interfaces. Especially the fields of prosthetics and telepresence can benefit from the higher spatial resolution of the sensor matrix

Dinamik kasılmalarda kas yorgunluğunun elektromiyogram ve mekanomiyogram ölçümleri ile analizi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Kas yorgunluğunu tanımlayabilecek indeksleri arttırmak ve çeşitli parametrelerle ilişkisini belirlemek, kişilere özel antrenman programlarının geliştirilmesine, kişinin günlük hayattaki aktivite programını düzenlenmesine ve olası kas hasarlarının engellenmesine destek olacaktır. Bu doğrultuda yapılan çalışmada, Bruce protokolü ve 100m sprint performans testi ile gönüllülerin kaslarında oluşturulan yorgunluğun, farklı parametreler kullanılarak belirlenmesi hedef alınmıştır. Ayrıca çalışmaya katılan gönüllülerin antrene olup olmamasının, kas yorgunluğu tespiti üzerine etkileri de incelenmiştir. Literatürde yer alan yorgunluk tespit çalışmalarından farklı olarak bu çalışmada, sadece EMG, sadece MMG ve EMG-MMG kombinasyonları karşılaştırmalı olarak değerlendirilmiştir. Analizler için ilk olarak, spor geçmişi olan fakat şuan aktif bir spor dalıyla uğraşmayan kişilerden oluşan bir gönüllü grubu oluşturulmuştur. Çalışmanın başında antrene olmayan bu gönüllü grubunun belirlenen prosedüre göre kayıtları alınmıştır. Daha sonra aynı grup 8 hafta boyunca eğim antrenmanlarına katılmış ve kasları anterene hale geldiğinde, gönüllülere aynı prosedür tekrar uygulanmıştır. Elde edilen kayıtlar önişleme, DPD tabanlı enerji değerlerinin hesaplanması ve sınıflandırma aşamalarından geçirilmiştir. DPD ayrışımı 8 seviyede gerçekleştirilmiş ve sınıflandırma yapmak için ÇKYSA kullanılmıştır. Çalışma sonucunda EMG ve MMG kayıtlarının kombine uygulamasının, antrene olmayan kişilerin kas yorgunluğunu belirlemede daha başarılı bir yöntem olduğu tespit edilmiştir. Antrene kişilerin kas yorgunluğunun belirlenmesinde ise sadece EMG kayıtlarının kullanılması durumunda en başarılı sonuçlara ulaşılmıştır. Yine antrene kişilerde MMG'nin, EMG ile kombinasyona girmesi sonucunda bu yüksek test başarı değerlerini düşürdüğü görülmüştür. Ayrıca kas yorgunluğunun belirlenmesinde kullanılacak parametrelerin sadece kendi başına değerlendirilemeyeceği, EMG ve MMG kayıtlarının alındığı kişilerin antrenman düzeyinin, yaptığı aktivite ya da sporun EMG ve MMG'nin kas yorgunluğu belirlemedeki etkinliğini tamamen değiştirdiği açıkça ortaya konulmuştur.Increasing the indexes that can define muscle fatigue and determining it's relationship with various parameters will help the development of personel training programs, the regulation of personel daily life activity program and the prevention of possible muscle impairment. Therefore, in this study carried out, determination of the fatigue, which occurs in the volunteers' muscles via Bruce protocol and 100 m sprint performance test, was aimed by using various parameters. Moreover, the effects of whether the volunteers being trained or not, over the determination of muscle fatigue were analysed as well. Differently from the fatigue determination studies that are present in the literature, the records of solely Electromyogram (EMG), solely Mechanomyogram (MMG) and the combination of EMG and MMG were evaluated comperatively. For the analysis, firstly, a volunteers group, made of people who had a suport background in the past but now does not engage in any sport branches were performed. At the beginning of the study, the records of this group of volunteers who were untrained were taken according to the determined procedure. Afterwards, the same group participated in the trainings for 8 weeks and once their muscles became trained, the same procedure was applied to the volunteers again. The obtained records were passed through the stages of pre-processing, calculation of energy values based Wavelet Packet Transform (WPT), and classification. Decomposition of WPT was carried out in 8 levels and the Multi-layer Perceptron Artificial Neural Network (MLPNN) was used for classification. As the result of the study, it was determined that the combined application of EMG and MMG records was a more successful method for determining the muscle fatigue of those who were untrained. As for the determination of fatigue levels of those who were trained, the most successful results were attained by the use of solely EMG records. Once again, it was clearly revealed that the parameters to be used for the determination of muscle fatigue should not be evaluated single-handedly, and the training level of the persons, whose EMG and MMG records were taken, the daily activities they do and the sport activities they take part in totaly changed the effectiveness of determination of muscle fatigue by using EMG and MMG

Acoustic myography - The signal from contracting skeletal muscles

Muscular contraction is associated with low frequency transverse mechanical waves called acoustic myograph (AMG). It can be recorded by microphones and accelerometer. The origin of AMG is thought to be due to the lateral movement of the muscle as a whole. The signal is implicated in many reports as having great potential as force indicator during muscular contraction and could be use clinically in distinguishing healthy and disease, and evaluate force in muscles normally with little clinical access. The aim of this series of investigation was to assess the feasibility of using AMG as a force indicator, especially in situations where direct force measurement is not practical and in FES applications as fatigue indicator. Attempts were made to clarify AMG signal characteristics and assess the possible parameters which could be deployed to describe the AMG signal. Two series of experiments were carried out: one on voluntary contractions of human quadriceps and the other on stimulated contractions of rabbit anterior tibialis. Strain gauges were used to measure force and accelerometers were used to record AMG signal from the skin surface of the thigh on human and from the muscle surface of rabbit anterior tibialis. The AMG signal was recorded between 0.5Hz and wideband frequency and sampled at 512Hz. AMG signal amplitude was calculated by both the rectify-integrated and room-mean-square methods. Frequency content of AMG signal was analyzed by Fast-Fourier-Transform method. The studies carried out on human quadriceps were to: 1) Locate the possible optimal recording site for AMG. 2) Investigate the relationship between AMG and force production during isometric constant force and varying force contractions. 3) Study the AMG-force relationship during sustained and intermittent contractions till fatigue. The study performed on rabbit anterior tibialis were to: 1) Investigate the AMG signal characteristic with changing muscle length both under twitch and tetanic contractions. 2) Examine the AMG signal change with stimulation frequencies both at fixed and varied muscle lengths. 3) Assess the possible association between force and AMG in stimulated contraction till fatigue by both continuous and intermittent stimulation. 4) Study the influence of fatigue on AMG-force relationship under different stimulation frequencies. Results shown that there is no single optimal position for AMG recording on human quadriceps. But high AMG signal intensity were recorded at the mid and proximal-lateral region. The data presented in this report collaborated a linear relationship between AMG and force level in isometric contractions of human quadriceps muscle. This close link between AMG signal intensity and force production is also present in fatigue induced by sustained muscle contractions but not by intermittent contractions. The data obtained from rabbit tibialis anterior muscle showed less systemic relationships between AMG and force production. AMG signal intensity did not display a close relationship with force under condition of changing muscle length, stimulation frequency and fatigue. There were no significant change in AMG signal median frequency during voluntary contractions and AMG signal recorded during stimulated contractions were dominated by stimulation frequency. The good correlation between AMG and force in voluntary contractions, shows promise as an indicator of voluntary force from isometric contractions and fatigue by sustained contractions. The possible clinical use of AMG could be in the area of assessing force output from muscles with limited access, such as paraspinal muscle and facial muscles. It could also be used in conjunction with EMG to assess the state of the muscle function in health and disease and muscle mechanic in training. The use of AMG as force indicator in stimulated contractions, such as FES applications, requires further investigation. It did not appear to relate strongly to force output under conditions investigated. Alternative properties of AMG signal, such as power content in specific frequency range, should be investigated further for FES applications. The AMG median frequency certainly is not a good force indicator under all conditions tested in the experiment

A Biomechanical Characterisation of Eccentric and Concentric Loading of the Triceps Surae Complex.

PhDThis thesis presents a biomechanical characterisation of eccentric (EL) and concentric loading (CL) of the triceps surae. EL is commonly adopted as an effective treatment for Achilles tendinopathy, with notably better treatment success compared with CL. However, there is a lack of consensus about the most appropriate protocols for completing triceps surae exercises. Exercise parameters such as speed and load are important and may affect the stimuli sensed by the muscle-tendon unit and thus influence repair. This thesis aims to biomechanically characterise and compare EL and CL as a basis for trying to understand treatment effects. A measuring system comprising motion tracking, 2D ultrasound, force plates and EMG was adopted and a semi-automatic tracking algorithm developed to track the muscle-tendon junction throughout the loading cycle (Chapter 3). Having validated the accuracy of measurements (Chapter 4), the effect of variables such as speed of exercise (chapter 5) and addition of load (Chapter 6) were assessed on Achilles tendon force, stiffness, stress, strain and force perturbations as well as muscle activation and contraction frequency (Chapter 7), in healthy subjects. It was found that EL and CL do not differ in terms of tendon force, stiffness or strain. However, EL is characterised by lower muscle activation and by 10 Hz perturbations present within the tendon. These perturbations were found to be significantly dependent on movement speed and load applied during EL movements only. However, no effect of speed was found on tendon force, stiffness and strain during either exercise movement. Finally, temporo-spatial analysis of the calf revealed region specific variations in muscle activation during both EL and CL, with 10 Hz perturbations coming predominantly from medial soleus and medial gastrocnemius muscle activity. These studies provide new information about the biomechanics of EL or CL, which should enhance understanding, and development, of conservative Achilles tendinopathy management