The development of an advanced human–machine interface has always been an interesting
research topic in the field of rehabilitation, in which biomedical signals, such as myoelectric …

In recent decades, transportation planning researchers have used diverse types of machine
learning (ML) algorithms to research a wide range of topics. This review paper starts with a …

To develop effective wildfire evacuation plans, it is crucial to study evacuation decision-
making and identify the factors affecting individuals' choices. Statistic models (eg, logistic …

As surface electromyogram (sEMG) signals have the ability to detect human movement
intention, they are commonly used to be control inputs. However, gait sub-phase …

For realizing multi-DOF interfaces in wearable computer system, accelerometers and
surface EMG sensors are used synchronously to detect hand movement information for …

In the last decades, the researchers of the human arm prosthesis are using different types of
machine learning algorithms. This review article firstly gives a brief explanation about type of …

For realizing a multi-DOF myoelectric control system with a minimal number of sensors,
research work on the recognition of twenty-four hand gestures based on two-channel …

This work presents a new neural network model related to EMG signal classification for
myoelectric control. The aim of this work is to develop a more accurate method for pattern …

We are developing a compiler that translates ordinary MATLAB scripts into code suitable for
compilation and execution on parallel computers supporting C and the MPI message …

This paper presents a novel artificial neural network approach to control an intelligent
wheelchair using myoelectric signals. The work is divided into six stages out of which feature …