Cycling fatigue evaluation using weighted-cumulated methodology

Abstract

In this paper, the weighted-cumulated methodology designed for the objective muscle fatigue estimation using surface electromyography is improved and extended for cycling applications. An automatic signal burst segmentation is proposed for dynamic electromyography, which is robust to signal amplitude fluctuations and abrupt variation of the experimental protocol parameters. The developed algorithm is integrated into a single instrumental tool. To evaluate the proposed methodology, nine participants performed cycling exercise until muscular failure in three different experimental protocols. In the first protocol, angular velocity was kept constant and exercise power was increased. In the second protocol, power was kept constant and the angular velocity was increased. The third protocol is maintained constant in both power and angular velocity at relatively high values. During the tests, surface electromyography signal was acquired from vastus lateralis. Behavioral characteristics and performance comparison involving the proposed experimental protocols are shown. The interpretations associated with objective metric to estimate muscle fatigue are discussed. The experimental results, obtained using improved weighted-cumulated methodology, are shown to be sensitive enough to distinguish spectral signature changes in the cycling electromyographic signals associated with muscle fatigue. The weighted-cumulated methodology has been shown to be fully applicable in dynamic physical protocols such as cycling. However, the investigations point out that the specification of the experimental protocol is also very important for the results reliability.