TY - JOUR AU - Daniuseviciute, L. AU - Pukenas, K. AU - Brazaitis, M. AU - Skurvydas, A. AU - Sipaviciene, S. AU - Ramanauskiene, I. AU - Linonis, V. PY - 2010/10/12 Y2 - 2024/03/28 TI - Wavelet-Based Entropy Analysis of Electromyography during 100 Jumps JF - Elektronika ir Elektrotechnika JA - ELEKTRON ELEKTROTECH VL - 104 IS - 8 SE - DO - UR - https://eejournal.ktu.lt/index.php/elt/article/view/9237 SP - 93-96 AB - <p>Muscle fatigue is a complex process that is most often defined as an exercise induced reduction in the ability of a muscle to generate force, and has been studied over numerous exercises for decades in an attempt to understand and indentify the mechanisms that lead to the loss of force production. One of muscle fatigue estimation is to assess changes in frequency measures of muscle electromiography signals. Electromiography signal is essentially a non-stationary signal, where muscle contraction can reach very high or small amplitudes. We used wavelet-based Shannon entropy to estimate the complexity of electromiography signals. Wavelet analysis is suitable tool for detecting and characterizing specific phenomena in time and frequency planes.</p> ER -