Calculating Integrated EMG, RMS, Median Frequency, and Mean Power Frequency for Electromyography Signals

This implementation calculates integral EMG (iEMG), root mean square (RMS), median frequency, and mean power frequency for electromyography signals. For iEMG calculation, you can sum all signal sample points sequentially, which in MATLAB can be implemented using the cumsum() function for cumulative integration or simple summation with sum() for total iEMG value. RMS value serves as a crucial indicator of signal energy intensity, calculated as the square root of the mean of squared signal values - implementable using rms() function or manual calculation with sqrt(mean(signal.^2)). Median frequency represents the central frequency in the signal spectrum, determinable through spectral analysis where half the power resides below this frequency; this can be computed using medfreq() function with periodogram or pwelch methods. Mean power frequency indicates the average frequency of the signal power spectrum, obtained by performing spectral analysis and calculating the frequency-weighted average power distribution, implementable with meanfreq() function. By computing these parameters, researchers can comprehensively understand EMG signal characteristics and behavior for clinical and research applications. Code implementation typically involves signal preprocessing, frequency domain transformation using FFT, and statistical calculations on the resulting power spectrum.