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We present the method for classifying kinematical data required for control of a rehabilitation robot for upper extremities. The classification to two cases (success, no-success) was analyzed by two methods: Bayes estimation and artificial neural network (ANN). The results are presented for an example being envisioned for rehabilitation: playing the Wii bowling with the specially constructed pantograph...
The following topics are dealt with: neural networks for rehabilitation of sensory-motor systems; wind power forecast based on neural networks; neural adaptive FIR filters; and neural networks based signal processing.
The gait disturbances in Parkinson's disease (PD) patients occur occasionally and intermittently, appearing in a random, inexplicable manner. These disturbances include festinations, shuffling, and complete freezing of gait (FOG). Alternation of walking pattern decreases the quality of life and may result in falls. In order to recognize disturbances during walking in PD patients, we recorded gait...
The nucleotide genomic signal (NuGS) methodology is based on the conversion of symbolic nucleotide sequences into digital genomic signals. There have been several attempts to represent nucleotide sequences as digital signals, most using some specific property of the nitrogeneous bases, e.g., the electronion interaction (EII) potential. Unfortunately, the resulting representation tends to be biased,...
This paper presents machine learning (ML) techniques for development of a control scheme to be used in functional electrical stimulation (FES) of hemiplegic walking. The goal is to make an electrical stimulation pattern by mapping the sensors signals acquired during walking (input) to activities of muscles (output) acting around knee and ankle joints. Two machine learning techniques with ability of...
Alternative and more efficient approaches for microwave applicators modeling, in respect to conventional numerical techniques, are presented in the paper. These approaches are based on artificial neural networks incorporating previously acquired partially knowledge about problem domain. Neural models, created using the suggested approaches, provide the similarly accuracy as numerical methods but performing...
Summary form only given. The contemporary robotics technology is broadening its applications from factory to more general-purpose applications in domestic and public use, e.g., partner to the elderly, rehabilitations, search and rescue, etc. If robotics technology is to be successful in such complex, unstructured, dynamic environments with high level of uncertainties, it will need to meet new levels...
In this paper we describe a database, noted as RadEch Database, containing radar echoes from various targets. The data has been collected in controlled test environments at the premises of Military Academy - Republic of Serbia. Our goal is to provide a balanced and comprehensive database to enable reproducible research results in the field of classification of ground moving targets (pattern recognition)...
The genetic code is analyzed as one of the major natural codes, which as such can reveal the deeper principles of optimal coding. The analysis is based on a discovery that the symmetrical architecture of genetic code and the nucleon number of its constituents - the free canonical amino acids and bases, are strictly determined by the prime number with a cycling digit property -037. A detailed derivation...
The aim of this paper is to discuss and compare two neural approaches applied in small-signal modelling of microwave FETs. One of them is completely based on artificial neural networks, while the other is a hybrid model putting together artificial neural networks and an equivalent circuit representation of a microwave transistor. Devices with different gate width are considered in this paper. Different...
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