This doctoral thesis is about a rather new model-based signal processing methodology that is based on factor graphs and message-passing algorithms. Using this, we have developed exemplary signal processing algorithms for various biomedical applications. The main application to evaluate and demonstrate this new methodology was in the field of electromyographic (EMG) signal analysis. EMG signals ...

In this paper we present our investigations on the potential of wavelet-based preprocessing for surface electromyographic speech recognition. We implemented several variants of the Discrete Wavelet Transform and applied them to electromyographical data. First we examined different transforms with various filters and decomposition levels and found that the Redundant Discrete Wavelet Transform pe...

Electromyographic (EMG) signal provide a significant source of information for diagnosis, treatment and management of neuromuscular disorders.Neuromuscular diseases changes, the shape and characteristics of the motor unit action potentials (MUAPs). The MUAPs detected from myopathic patients are characterized by high frequency contents, low peak-to-peak amplitude and MUAPs neuropathic patients a...

Surface electromyography (EMG) is a widely used, straight-forward, technique which allows to investigate patterns of neuromuscular activation. In contrast to the relative simplicity of the recording technique, the analysis of the derived electric signals may be rather sophisticated. The last decade, in particular, has been characterized by the development of a several quantitative approaches to...

Voluntary muscle force control is accomplished both by recruitment of motor units (MUs) and by firing rate modulation of active MUs. Typically, MU recruitment and firing rate organization is assessed using piecemeal intramuscular recordings drawn from different experiments, or even from different subjects. As a consequence, it is often difficult to assemble a systematic description of the relat...

This paper presents a novel approach to optimize pattern recognition system using genetic algorithm (GA) to identify the type of hand motion employing artificial neural networks (ANNs) with high performance and accuracy suited for practical implementations. To achieve this approach, electromyographic (EMG) signals were obtained from sixteen locations on the forearm of six subjects in ten hand m...

In this paper, we present a simultaneous and continuous kinematics estimation method for multiple DoFs across shoulder and elbow joint. Although simultaneous and continuous kinematics estimation from surface electromyography (EMG) is a feasible way to achieve natural and intuitive human-machine interaction, few works investigated multi-DoF estimation across the significant joints of upper limb,...

PURPOSE The objective of this study was to investigate EMG signals of cervical muscles in five directional efforts from chronic neck pain patients and compare them with those of the healthy controls to discern differences between patients and controls with respect to strength and EMG characteristics. METHOD Seventeen male and 17 female idiopathic and non-specific chronic neck pain patients wi...