Muscle fiber conduction velocity (MFCV) can be measured by estimating the time delay between surface EMG signals recorded by electrodes aligned with the fiber direction. In the case of dynamic contractions, the EMG signal is highly non-stationary and the time delay between recording sites may vary rapidly over time. Thus, the processing methods usually applied in the case of static contractions do not hold anymore and the delay estimation requires processing techniques that are adapted to non-stationary conditions. The current paper investigates several methods based on time-frequency approaches or adaptive filtering in order to solve the time-varying delay estimation problem. These approaches are theoretically analyzed and compared by Monte–Carlo simulations in order to determine if their performance is sufficient for practical applications. Moreover, results obtained on experimental signals recorded during cycling from the vastus medialis muscle are also shown. The study presents for the first time a set of approaches for instantaneous delay estimation from two-channels EMG signals. 
Time-varying delay estimators for measuring muscle fiber conduction velocity from the surface electromyogram