Blind Separation of Surface Electromyographic Mixtures from Two Finger Extensor Muscles

International audienceBlind source separation (BSS) was performed to reduce the crosstalk in the surface electromyografic signals (SEMG) for the muscle force estimation applications. A convolutive mixture model was employed to separate the SEMG signals from two finger extensor muscles using a frequency-domain approach. It was assumed that the tension of each muscle varies independently and the independence of the SEMG was replaced by minimization of the covar-iance of muscle forces represented by integrated SEMG. This covariance was also used to resolve the permutation ambiguity inherent to the frequency-domain BSS. The forces estimated by the reconstructed sources were compared with the measured forces to calculate the crosstalk reduction efficiency. The proposed algorithm was shown to be more effective in frequency domain than an ICA algorithm for extensor muscles crosstalk reduction

The Relationship between Anthropometric Variables and Features of Electromyography Signal for Human-Computer Interface

http://doi.org/10.4018/978-1-4666-6090-8 ISBN 13 : 9781466660908 EISBN13: 9781466660915International audienceMuscle-computer interfaces (MCIs) based on surface electromyography (EMG) pattern recognition have been developed based on two consecutive components: feature extraction and classification algorithms. Many features and classifiers are proposed and evaluated, which yield the high classification accuracy and the high number of discriminated motions under a single-session experimental condition. However, there are many limitations to use MCIs in the real-world contexts, such as the robustness over time, noise, or low-level EMG activities. Although the selection of the suitable robust features can solve such problems, EMG pattern recognition has to design and train for a particular individual user to reach high accuracy. Due to different body compositions across users, a feasibility to use anthropometric variables to calibrate EMG recognition system automatically/semi-automatically is proposed. This chapter presents the relationships between robust features extracted from actions associated with surface EMG signals and twelve related anthropometric variables. The strong and significant associations presented in this chapter could benefit a further design of the MCIs based on EMG pattern recognition

Disassembly task evaluation by muscle fatigue estimation in a virtual reality environment

International audienceToday, disassembly operations play a very important role during the initial design phase of industrial products considering the role played by these operations throughout the product life cycle. Current simulation platforms do not offer the necessary information and versatility required for a complete disassembly process simulation, including human/operator physiological data management. The paper deals with a new method for disassembly sequence evaluation. It is based on metabolic energy expenditure and muscle fatigue estimation. For this purpose, the analytical model for mechanical energy expenditure is proposed. In this model, the required mechanical work is used as a parameter that allows comparing the relationships among fatigue levels when performing disassembly sequences. Then, the fatigue levels are evaluated by analyzing the recorded electromyography signal on an operator’s arm. The proposed method is validated by a set of experimental disassembly tests performed in a virtual reality environment. The comparison of the analytical and experimental results has shown good correlation between them. The main result of this study is the proposed model for assessing muscle fatigue and its validation by experimental procedure. The proposed method provides the feasibility to integrate human muscle fatigue into disassembly sequence evaluation via mechanical energy expenditure when performing disassembly operation simulations

Disassembly Task Evaluation in Virtual Reality Environment

International audienceThe influence of virtual reality (VR) on human behavior with using biomechanical analysis methods and its application for assembly/disassembly operations simulation is presented in this paper. A new haptic model for mechanical energy expenditure is proposed where the required mechanical work is used as main parameter. The fatigue levels are evaluated by analyzing the recorded electromyography (EMG) signals on the most involved muscles of operator’s arm. A set of experimental disassembly tests realized in a VR environment are performed thus allowing to validate the proposed method. The comparison of the analytical and experimental results has shown good correlation between them. The proposed method provides the feasibility to integrate human muscle fatigue into disassembly sequence evaluation via mechanical energy expenditure when performing disassembly operation simulations in the initial stage of product design

Improving hand biomechanical modeling with motor control theories and EMG data

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Biomechanics of the human digits

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The dynamic role of anticipatory postural adjustments in a rocking on heels movement

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Intégration des membres supérieurs comme supports posturaux dans la relation posture-mouvement (analyse biomécanique)

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