One-dimensional Sonomyography (SMG) for Skeletal Muscle Assessment and Prosthetic Control.

摘要

Sonomyography (SMG) is the signal we previously termed to describe muscle contraction using real-time muscle morphological changes extracted from ultrasound images or signals. With the advantages of being less expensive, more compact, A-mode ultrasound was introduced to detect the dynamic thickness change of skeletal muscles during contraction, named as one-dimensional sonomyography (1D SMG). The 1D SMG signal was extracted from the ultrasound signal by automatically tracking the shift of echoes from tissue interfaces and the muscle thickness change was calculated. Compared with surface EMG (SEMG), 1D SMG could discriminate activity of deep muscles from more superficial muscles. It was also found that 1D SMG signal linearly correlated with the wrist extension angle.;Moreover, the least squares support vector machine (LS-SVM) and artificial neural networks (ANN) were used to predict dynamic wrist angles from 1D SMG signals. An LS-SVM model together with back-propagation (BP) and radial basis function (RBF) ANN was trained using the data sets collected at the rate of 22.5 cycles/min for each subject. It was concluded that the wrist angle could be precisely estimated from the thickness changes of the extensor carpi radialis using LS-SVM or ANN models.;In this thesis, the potential of 1D SMG in prosthetic control was also investigated. The performances of SMG and SEMG signal in tracking the guided patterns of wrist extension, discrete tracking tasks and a real prosthetic control were evaluated and compared. The results suggest that SMG signal has great potential to be an alternative method to SEMG to evaluate muscle function and control prostheses.;Finally, an amputee subject was recruited to perform the control tasks. The performance of the subject using 1D SMG and SEMG signals were evaluated to see whether 1D SMG signal could really used by the amputee. The feasibility of using 1D SMG by the amputee was demonstrated.;To sum up, we have successfully demonstrated that SMG (related to muscle architectural properties) can provide complementary information about muscle function in comparison with SEMG (related to muscle bioelectrical properties), which has been commonly used for muscle activity assessment and prosthetic control.