This dissertation of various aspects of electromyogram (EMG: muscle electrical activity) signal processing is comprised of two projects in which I was the lead investigator and two team projects in which I participated. The first investigator-led project was a study of reconstructing continuous EMG discharge rates from neural impulses. Related methods for calculating neural firing rates in other contexts were adapted and applied to the intramuscular motor unit action potential train firing rate. Statistical results based on simulation and clinical data suggest that performances of spline-based methods are superior to conventional filter-based methods in the absence of decomposition error, but they unacceptably degrade in the presence of even the smallest decomposition errors present in real EMG data, which is typically around 3-5%. Optimal parameters for each method are found, and with normal decomposition error rates, ranks of these methods with their optimal parameters are given. Overall, Hanning filtering and Berger methods exhibit consistent and significant advantages over other methods. In the second investigator-led project, the technique of signal whitening was applied prior to motion classification of upper limb surface EMG signals previously collected from the forearm muscles of intact and amputee subjects. The motions classified consisted of 11 hand and wrist actions pertaining to prosthesis control. Theoretical models and experimental data showed that whitening increased EMG signal bandwidth by 65-75% and the coefficients of variation of temporal features computed from the EMG were reduced. As a result, a consistent classification accuracy improvement of 3-5% was observed for all subjects at small analysis durations (< 100 ms). In the first team-based project, advanced modeling methods of the constant posture EMG-torque relationship about the elbow were studied: whitened and multi-channel EMG signals, training set duration, regularized model parameter estimation and nonlinear models. Combined, these methods reduced error to less than a quarter of standard techniques. In the second team-based project, a study related biceps-triceps surface EMG to elbow torque at seven joint angles during constant-posture contractions. Models accounting for co-contraction estimated that individual flexion muscle torques were much higher than models that did not account for co-contraction.

No description available.

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (p. 96-104).

Upper limb deficiencies in children may be the result of trauma, disease, or congenital problems. Although biomechanical losses are the primary problem associated with a limb deficiency, the loss of such an obvious body part has cosmetic and psychosocial implications as well. Fitting a child with a prosthesis typically is the treatment chosen by families. Presently, there are three types of prostheses available for pediatric amputees, including passive, cable-operated, and myoelectric arms, but the myoelectric appears to be the most popular choice of children and their families. However, there is growing concern among clinicians that, despite its advanced technological capabilities, the myoelectric prosthesis is chosen for aesthetic rather than functional reasons. It is difficult, then, to justify the expense of fitting a myoelectric prosthesis when a more inexpensive prosthesis, or none at all, would be a more appropriate prescription. The question of when to prescribe a myoelectric prosthesis for a pediatric patient remains one of the most controversial questions in the field of prosthetics today due to this cost/benefit issue. In this study, the researcher examined psychological factors that may influence whether or not a child will wear a prosthesis and how that prosthesis will be used. Thirty prosthetics patients of Texas Scottish Rite Hospital for Children and their parents answered questionnaires indicating self-perception, social acceptance, and family functioning. A prosthetic usage diary also was completed. Results indicated a significant relationship between optimal residual limb length and increased wearing time. Other trends in the data are discussed. Consideration of these variables by medical staff can be useful in developing appropriate expectations of adherence to treatment by the patient and the family. Recommendations are made for the prescription of pediatric prostheses that are both cost-effective and beneficial.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (p. 120-126).

No description available.

Above-elbow myoprostheses aim to restore the functionality of amputated limbs and improve the quality of life of amputees. By using electromyography electrodes attached to the surface of the skin, amputees are able to control motors in myoprostheses by voluntarily contracting the muscles of their residual limb. An advance in myoelectric control called targeted muscle reinnervation (TMR) reinnervates severed nerves into healthy muscle tissue and increases the number of muscle sites available for use in control purposes. In order to improve rehabilitation after TMR surgery, an inexpensive myoelectric training tool has been developed in collaboration with the Glenrose Rehabilitation Hospital that can be used by TMR patients for biofeedback applications. The training tool consists of a robotic arm, signal acquisition hardware, controller software, and a graphical user interface. This dissertation describes the design and evaluation of the training tool and its use as a research platform for testing novel controllers.

Thesis (M.S.)--Michigan State University. Dept. of Electrical and Computer Engineering, 2006. / Title from PDF t.p. (viewed on Nov. 20, 2008) Includes bibliographical references (p. 51-52). Also issued in print.

A prosthesis control strategy using a nearest neighbor electromyographic pattern classifier was investigated with both a real time microprocessor-based controller and offline computational facilities. Four active electrodes for myoelectric signal amplitude detection were interfaced with a microcomputer for data logging and pattern classification. A nearest neighbor algorithm correctly identified arm motions as belonging to one of six pattern classes from 72 percent to 100 percent of the time. There were five vectors for each class in the look-up table. The nearest neighbor pattern classifier was compared to a minimum error rate Bayes classifier under the assumption that the probability densities were distributed as a multivariate normal distribution. Comparable error rates were obtained with the same data vectors. A condensed nearest neighbor classifier was constructed to determine what minimum number of vectors was necessary in the look-up table. This minimum number of vectors ranged from two to six for the majority of the classes. Larger numbers of vectors were placed in the look-up table for classes that were more difficult to classify. / Ph. D.

While research shows that a patient’s success in using a myoelectric prosthetic arm is dependent on receiving effective training, current methods of training are not designed to effectively hold attention long enough for optimal training. This study focused on evaluating a novel myoelectric training device, consisting of a toy car controlled by EMG signals from the arm. Subjects’ performance with the trainer was evaluated to determine its ability to provide experience with EMG controls. Eight healthy adult subjects were taken through typical initial stages of myoelectric training, then asked to drive the car through a slalom course while the time, number of errors, and reversals required to complete the course were recorded, as well as the degree of difficulty subjects reported. The learning induced by using the trainer was found to be statistically significant (p < 0.002), with subjects demonstrating dramatic improvements (> 49%) in performance.