Muscle Fatigue Analysis With Optimized Complementary Ensemble Empirical Mode Decomposition and Multi-Scale Envelope Spectral Entropy

The preprocessing of surface electromyography (sEMG) signals with complementary ensemble empirical mode decomposition (CEEMD) improves frequency identification precision and temporal resolution, and lays a good foundation for feature extraction. However, a mode-mixing problem often occurs when the CEEMD decomposes an sEMG signal that exhibits intermittency and contains components with a near-by spectrum into intrinsic mode functions (IMFs). This paper presents a method called optimized CEEMD (OCEEMD) to solve this problem. The method integrates the least-squares mutual information (LSMI) and the chaotic quantum particle swarm optimization (CQPSO) algorithm in signal decomposition. It uses the LSMI to calculate the correlation between IMFs so as to reduce mode mixing and uses the CQPSO to optimize the standard deviation of Gaussian white noise so as to improve iteration efficiency. Then, useful IMFs are selected and added to reconstruct a de-noised signal. Finally, considering that the IMFs contain abundant frequency and envelope information, this paper extracts the multi-scale envelope spectral entropy (MSESEn) from the reconstructed sEMG signal. Some original sEMG signals, which were collected from experiments, were used to validate the methods. Compared with the CEEMD and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the OCEEMD effectively suppresses mode mixing between IMFs with rapid iteration. Compared with approximate entropy (ApEn) and sample entropy (SampEn), the MSESEn clearly shows a declining tendency with time and is sensitive to muscle fatigue. This suggests a potential use of this approach for sEMG signal preprocessing and the analysis of muscle fatigue

Snakes and strings: New robotic components for rescue operations

Abstract. The Japanese government is establishing an International Rescue Complex to promote research and development of key technologies for realization of practical search-and-rescue robots, anticipating for future large-scale earthquakes and other catastrophic disasters. This paper proposes a new paradigm called “snakes and strings”, for developing practical mobile robot systems that may be useful in such situations. “Snakes ” stands for snake-like robots, which can skillfully move among the debris of the collapsed buildings. “Strings”, on the other hand, means robotic systems using strings or tethers, such as proposed in the “hyper-tether” research [9]. Theters can continuously supply energy, accomplish reliable communication link, and also exhibit high traction force. This paper will present many new mechanical implementations of snake-like robots developed in our lab., and also explain in detail the new paradigm.