Abstract
This paper presents a novel multi-fractal detrended fluctuation analysis-based approach for fatigue estimation. This approach exploits the statistical self-similarity and long-range correlation of surface electromyography signals at different time scales in which the myoelectric manifestation of fatigue is more significant compared to the influence of varying force, muscle length (joint angle), and innervation zone. This approach provides a fatigue index which outperforms the conventional median frequency during cyclic and random contractions. This type of analysis is promising an efficient framework for analysis of surface electromyography signals with several potential applications.
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