Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications

Investigation into the control of an upper-limb myoelectric prosthesis

SIGLEAvailable from British Library Document Supply Centre- DSC:DXN053608 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Use of wavelet analysis techniques with surface EMG and MMG to characterise motor unit recruitment patterns of shoulder muscles during wheelchair propulsion and voluntary contraction tasks

The high demand on the upper extremity during manual wheelchair use contributes to a high prevalence of shoulder pathology in people with spinal cord injury. The overall purpose of this thesis was to investigate shoulder muscle recruitment patterns and wheelchair kinetics in able-bodied participants over a range of daily activities and mobility tasks requiring manual wheelchair propulsion. With a complete understanding of the muscle recruitment patterns, physiotherapists and wheelchair users can improve rehabilitation protocols and wheelchair propulsion performance to prevent shoulder pathology and maintain comfort during locomotion. Motor unit recruitment patterns were examined first during isometric and isotonic contractions to determine if spectral properties from EMG and MMG could be related to the different motor units in biceps brachii by using wavelet techniques coupled with principle component analysis. The results indicated that motor unit recruitment patterns can be indicated by the spectral properties of the EMG and MMG signals. EMG activity of 7 shoulder muscles was recorded with surface electrodes on 15 able-bodied participants over a range of manual wheelchair propulsion activities. Wavelet and principle component analysis was used to simultaneously decompose the signals into time and frequency domain. There are three main conclusions that can be drawn: 1) Uphill and faster speed (1.6m/s) propulsion required higher activity levels in the shoulder muscles and greater resultant joint force than did slow speed propulsion on the ergometer (0.9m/s), thus potentially\ud resulting in shoulder pathology. 2) Prolonged wheelchair propulsion and greater muscle activity may result in fatigue and play a factor in the development of shoulder pain and pathology over time. 3) The instructed semicircular pattern has a positive effect on shoulder muscle recruitment patterns. Further investigations need to focus on a systematic integrated data collection and analysis of kinematic, kinetic, and electromyography (EMG) data from people with spinal cord injuries

In vivo investigation of muscle behaviour during voluntary and electrically induced muscle contraction using B-Mode ultrasound imaging

Musculoskeletal Ultrasound Imaging (USI) is a growing field in literature. It has been proven to be a useful tool for investigating the properties of the muscle. There is growing interest in ultrasound imaging techniques for the description of skeletal muscle function, and different algorithms have been developed for this purpose. The majority of studies limit their focus on a particular area of the muscle, such as the aponeuroses, or on architectural parameters such as fiber length and pennation angle. The investigation of the entire muscle visualised on the ultrasound image may help elucidate the muscle function under normal conditions or when external factors compromise or alter the muscle function. Functional electrical stimulation (FES) is a technique based on the use of electrical current to activate skeletal muscles and facilitate their contraction. It is commonly used for strength training or in rehabilitation to accelerate or enhance the recovery of skeletal muscle's function. The ability of this technique to improve muscle performance in both healthy and diseased muscles has been demonstrated in research and in clinical practice. However the artificial nature of the muscle activation during FES leads to some important differences from the voluntary muscle contraction. Ultrasound Imaging (USI) is a potential tool that could provide objective measurements of the muscle's response during electrical stimulation, thus helping to describe and understand these differences. The aim of this study is to develop techniques based on USI that helps to elucidate the muscle function during electrical stimulation and allow comparison with voluntary contractions. Ultrasound videos were collected from healthy participants during experimental procedures involving voluntary and electrically induced muscle contractions. The videos were analysed using software algorithms for the tracking of features in US images. The resulting parameters were used as the basis for characterisation methods to describe the muscle contraction, both globally and locally. The effectiveness of the USI analysis techniques was tested and methods for extraction of physiological information from the video analysis were implemented. The regional distribution of muscle displacement during the tasks was analysed. Larger displacements were observed at deeper portions of the muscle in both the voluntary and the electrically induced contractions. Differential displacements across muscle depths were observed to differ during voluntary and FES contractions. The electric currents applied induce a uniform muscle contraction across different depths, most likely influenced by the way the electric field recruits muscle fibers. Muscle displacement was correlated to the force exerted by the muscle. Areas close to the deep aponeurosis have higher correlation with torque exerted and a second order polynomial can be used to define the relationship between displacement and torque. The relationship between the whole muscle displacement at different depths and the torque exerted was described using a polynomial surface fitting. Mechanical strain was used to map the muscle activation. Middle areas of the muscle undergo higher positive vertical strain (i.e. the muscle thickens) while deeper portions of the muscle are the most affected by shortening horizontal strain (i.e. the muscle shortens) in both voluntary and FES contractions. The muscle contractility was analysed through strain rate. A time-frequency analysis of the strain rate was performed. More frequency components and higher bandwidths were observed in FES induced contractions when compared to the voluntary. The frequency components might reflect the motor unit activation, suggesting that during FES all the motor units, firing at different rates, are recruited. In this project, USI was used as a tool to characterise the muscle behaviour locally. Regional muscle displacement and strain distribution have been used to elucidate the muscle function and quantify how different muscle areas are mechanically involved in the contraction. Strain rate was correlated with the muscle contractility and hypotheses regarding the correlation with motor units firing rate have been proposed. In conclusion a number of techniques were developed with the purpose to investigate the muscle function in normal conditions and when external factors, such as electrical stimulation, alter the natural muscle behaviour

Twelfth Annual Conference on Manual Control

Main topics discussed cover multi-task decision making, attention allocation and workload measurement, displays and controls, nonvisual displays, tracking and other psychomotor tasks, automobile driving, handling qualities and pilot ratings, remote manipulation, system identification, control models, and motion and visual cues. Sixty-five papers are included with presentations on results of analytical studies to develop and evaluate human operator models for a range of control task, vehicle dynamics and display situations; results of tests of physiological control systems and applications to medical problems; and on results of simulator and flight tests to determine display, control and dynamics effects on operator performance and workload for aircraft, automobile, and remote control systems

Design, Control, and Perception of Bionic Legs and Exoskeletons

Bionic systems---wearable robots designed to replace, augment, or interact with the human body---have the potential to meaningfully impact quality of life; in particular, lower-limb prostheses and exoskeletons can help people walk faster, better, and safer. From a technical standpoint, there is a high barrier-to-entry to conduct research with bionic systems, limiting the quantity of research done; additionally, the constraints introduced by bionic systems often prohibit accurate measurement of the robot's output dynamics, limiting the quality of research done. From a scientific standpoint, we have begun to understand how people regulate lower-limb joint impedance (stiffness and damping), but not how they sense and perceive changes in joint impedance. To address these issues, I first present an open-source bionic leg prosthesis; I describe the design and testing process, and demonstrate patients meeting clinical ambulation goals in a rehabilitation hospital. Second, I develop tools to characterize open-loop impedance control systems and show how to achieve accurate impedance control without a torque feedback signal; additionally, I evaluate the efficiency of multiple bionic systems. Finally, I investigate how well people can perceive changes in the damping properties of a robot, similar to an exoskeleton. With this dissertation, I provide technical and scientific advances aimed at accelerating the field of bionics, with the ultimate goal of enabling meaningful impact with bionic systems.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163108/1/afazocar_1.pd