Recent studies in Electromyogram (EMG) pattern recognition reveal a gap between
research findings and a viable clinical implementation of myoelectric control strategies. One …

The extraction of the accurate and efficient descriptors of muscular activity plays an
important role in tackling the challenging problem of myoelectric control of powered …

In this study, a minimal setup for the ankle joint kinematics estimation is proposed relying
only on proximal information of the lower-limb, ie thigh muscles activity and joint kinematics …

Feature selection is one of the most common and critical tasks in database classification. It
reduces the computational cost by removing insignificant features. Consequently, this makes …

Electromyography (EMG) signal is gaining popularity to develop intelligent bionics and
prosthetic devices using machine learning techniques. Feature extraction is essential step …

Feature selection often involves two conflicting objectives of minimizing the feature subset
size and the maximizing the classification accuracy. In this paper, a multi-objective artificial …

Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical
decision making. Machine learning can build upon prior sub-grouping approaches by using …

The classification of upper-limb movements based on surface electromyography (EMG)
signals is an important issue in the control of assistive devices and rehabilitation systems …

This study aimed to investigate the feasibility of integrating image features computed from
both spatial and frequency domain to better describe the tumor heterogeneity for precise …

The Commercial Aviation Safety Team found the majority of recent international commercial
aviation accidents attributable to loss of control inflight involved flight crew loss of airplane …