Choice Of Mechanomyography Sensors For Diverse Types Of Muscle Activities

Skeletal muscles contribute to the movement produced in the human body.They are therefore of vital importance for the study of muscles in various applications of movement including exercise,sports,prosthesis,rehabilitation,etc. The movement produced by skeletal muscles can be analyzed through various techniques like mechanomyography (MMG) and electromyography (EMG).MMG is a novel technique to assess skeletal muscle function through the oscillations produced during muscle contractions.MMG advocates well for its reliability,performance,and ease in application to other presently used techniques.MMG employs several types of sensors to observe vibrations in skeletal muscles.These sensors vary widely from application to type of movement and muscle.This review provides a comprehensive chunk of information on MMG sensor selection according to its placement,muscle function and condition,and limb movement and application. Recommendations for the choice of MMG sensor are given through extensive literature search over here

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

APPLICATION OF SINGLE WIRELESS HOLTER TO SIMULTANEOUS EMG, MMG AND EIM MEASUREMENT OF HUMAN MUSCLES ACTIVITY

This paper describes application and design of wireless holter with innovative functionality, used it in field of human muscle monitoring. In our experiments we monitored EMG (electromyography), MMG (mechanomyography) and EIM (electrical impedance myography) all by single device. It is first time when these all parameters were monitored simultaneously taking advantage of the holter device data output in order to find the signals interconnection. Our data were compared with normally used medical device and signal quality was verified

The application of digital accelerometers for wired and non-wired Mechanomyography

The objective of this paper is to consider the use of digital accelerometers for Mechanomyographic applications. The digital outputs of the accelerometer require the consideration of additional interfacing hardware for any commercial data acquisition systems being considered. The Arduino open-source platform is shown to meet this requirement. This platform also provides access to set the data registers on the accelerometer to output data at the resolution, speed and format required. Results show that digital accelerometers provide an accurate representation of the MMG signal. The second objective of this work was to extend this digital platform to design a wireless MMG sensor. This has been completed using open-source components and libraries. The wireless sensor can provide an inexpensive accurate representation of the MMG response for distances in excess of 30 meters

Updated Perspectives on the Role of Biomechanics in COPD: Considerations for the Clinician

Patients with chronic obstructive pulmonary disease (COPD) demonstrate extra-pulmonary functional decline such as an increased prevalence of falls. Biomechanics offers insight into functional decline by examining mechanics of abnormal movement patterns. This review discusses biomechanics of functional outcomes, muscle mechanics, and breathing mechanics in patients with COPD as well as future directions and clinical perspectives. Patients with COPD demonstrate changes in their postural sway during quiet standing compared to controls, and these deficits are exacerbated when sensory information (eg, eyes closed) is manipulated. If standing balance is disrupted with a perturbation, patients with COPD are slower to return to baseline and their muscle activity is differential from controls. When walking, patients with COPD appear to adopt a gait pattern that may increase stability (eg, shorter and wider steps, decreased gait speed) in addition to altered gait variability. Biomechanical muscle mechanics (ie, tension, extensibility, elasticity, and irritability) alterations with COPD are not well documented, with relatively few articles investigating these properties. On the other hand, dyssynchronous motion of the abdomen and rib cage while breathing is well documented in patients with COPD. Newer biomechanical technologies have allowed for estimation of regional, compartmental, lung volumes during activity such as exercise, as well as respiratory muscle activation during breathing. Future directions of biomechanical analyses in COPD are trending toward wearable sensors, big data, and cloud computing. Each of these offers unique opportunities as well as challenges. Advanced analytics of sensor data can offer insight into the health of a system by quantifying complexity or fluctuations in patterns of movement, as healthy systems demonstrate flexibility and are thus adaptable to changing conditions. Biomechanics may offer clinical utility in prediction of 30-day readmissions, identifying disease severity, and patient monitoring. Biomechanics is complementary to other assessments, capturing what patients do, as well as their capability

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