Two different electro-biological signal based Interfaces for impaired people were developed: EMG and EEG based. Such interfaces present like main characteristics relatively simple acquisition and processing systems, which need of few hardware and software resources, so that they are computational and financial low cost solutions. Both interfaces have been applied to robotic systems (emulating a...

The human hand is a complex structure that performs various functions for activities of daily living and occupations. This paper presents a literature review on the methodologies used to evaluate hand functions from a biomechanics standpoint, including anthropometry, kinematics, kinetics, and electromyography (EMG). Anthropometry describes the dimensions and measurements of the hand. Kinematics...

Appropriate cancellation of the baseline fluctuation (BLF) is an important issue when recording EMG signals as it may degrade signal quality and distort qualitative and quantitative analysis. We present two techniques, statistical and filter-design approach for cancellation of the BLF based on several signal processing techniques used sequentially. The methodology is to estimate the spectral co...

This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent no...

To test whether electromyogram (EMG) is nonlinear deterministic signal or just random noise, we comprehensively analyze four EMGs of an adult woman. At first, we calculate the correlation time, L-Z complexity, approximate entropy (ApEn), maximum Lyapunov exponent (Ly1) and correlation dimension (Dcorr) of each EMG data and its ten surrogate data. We find that all the results are quite different...

This paper presents the work on a technology for Real time EMG acquisition and recognition of head movement. EMG signal detection and analysis is useful in various clinical and biomedical applications such as generation of control signal for prosthetic tool, but better solutions for detecting noise free EMG signals need to be developed. In this paper a simple and cost effective method for estim...

Electromyographic (EMG) signal directly represents muscle activity. When recording EMG signals of closely located muscles on skin surface the problem of source separation arises, each acquired channel records signals coming from different muscles [1]. Working on extrinsic finger extensors EI (index) and EDM (little finger) provides a system with muscles that are closely located and independentl...