Emotion recognition is of major importance towards the acceptability of Human-Computer Interaction systems, and several approaches to emotion classification using features extracted from biosignals have already been developed. This analysis is, in general, performed on a signal-specific basis, and can bring a significant complexity to those systems. In this paper we propose a signal-independent...

Blind Source Separation (BSS) is a statistical approach to separating individual signals from an observed mixture of a group of signals. BSS relies on only very weak assumptions on the signals and the mixing process (hence the “blind” descriptor) and this blindness enables the technique to be used in a wide variety of situations. Research in the field of Blind Source Separation has resulted in ...

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorde...

Introduction It is electromyogram (EMG) that represents interference signals of electrical activities in many motor units (MUs). An EMG decomposition method is the procedure by which the signal is classified into its constituent motor unit action potential trains (MUAPTs). So far the classification to each MUAPT in multi-channel EMGs by means of an EMG decomposition method is directly performed...

one of the most common signals used for achieving high range resolution in radar is stepped-frequency signals. when a target is stationary in these radars, dft (discrete fourier transform) based processing is used to attain high range resolution profile (hrrp). however, in the case of moving target, due to spreading of the echo signal spectrum, dft based processing is not optimal and decreases ...

In the field of digital signal processing, the function of a filter is to remove unwanted parts of the signal such as random noise that is also undesirable. To remove noise from the speech signal transmission or to extract useful parts of the signal such as the components lying within a certain frequency range. Filters are broadly used in signal processing and communication systems in applicati...

The effect of subcutaneous fat on myoelectric signal amplitude and cross-talk was studied using finite element (FE) models of electromyogram (EMG) signal propagation. A FE model of the upper arm consisted of skin, fat, muscle and bone tissues in concentric layers. Single muscle fibre action potentials were simulated for muscle fibres at a variety of depths and combined to simulate surface EMG i...

Although traditional signal-based structural health monitoring algorithms have been successfully employed for small structures, their application for large and complex bridges has been challenging due to non-stationary signal characteristics with a high level of noise. In this paper, a promising damage detection algorithm is proposed by incorporation of adaptive signal processing and Artificial...

On of the major difficulties faced by those who are fitted with prosthetic devices is the great mental effort needed during the first stages of training. When working with myographic prosthesis, that effort increases dramatically. In this sense, the authors decided to devise a mechanism to help patients during the learning stages, without actually having to wear the prosthesis all the time. The...

Together with 3D kinematics of the lower extremities, pelvis, and lumbar spine, ground reaction forces (GRF) and surface EMG signals from the following bilateral trunk muscle groups were recorded: external and internal abdominal obliques; rectus abdominus; lumbar and thoracic erector spinae; and latissimus dorsi. Kinematic and GRF data were incorporated in a “bottom-up” inverse dynamical linked...