EMG Spectral Moments

Computes spectral moments (M0, M1, M2) over sliding windows. M0 is total power, M1 is the first spectral moment (related to mean frequency), and M2 is the second moment (related to bandwidth). These can be combined to derive the mean frequency (M1/M0) and spectral bandwidth.

Usage

emgSpectralMoments(x, window_sec = 1, overlap = 0.5, assay_name = NULL)

Arguments

x

A PhysioExperiment object with EMG data.

window_sec

Analysis window in seconds (default: 1.0).

overlap

Overlap fraction (default: 0.5).

assay_name

Input assay name (default: first assay).

Value

A data.frame with one row per channel per window, containing columns:

channel

Integer channel index.

window

Integer window number (1-indexed).

m0

Zeroth spectral moment (total power).

m1

First spectral moment (frequency-weighted power).

m2

Second spectral moment (frequency-squared-weighted power).

References

De Luca, C.J. (1984). "Myoelectrical manifestations of localized muscular fatigue in humans." Critical Reviews in Biomedical Engineering, 11(4), 251-279.

Merletti, R. & Parker, P.A. (2004). "Electromyography: Physiology, Engineering, and Non-Invasive Applications." Wiley-IEEE Press. doi:10.1002/0471678384

See also

emgFatigue() for median and mean frequency tracking, emgFatigueIndex() for summary fatigue metric, emgEnvelope() for time-domain amplitude analysis

Examples

pe <- make_emg_fatigue(n_time = 10000, sr = 1000)
sm <- emgSpectralMoments(pe, window_sec = 1.0)
head(sm)
#>   channel window       m0       m1      m2
#> 1       1      1 44.01779 6658.242 1707670
#> 2       1      2 45.21600 6962.068 1797298
#> 3       1      3 42.96837 6748.368 1786980
#> 4       1      4 42.65274 6505.444 1739663
#> 5       1      5 45.46966 6868.128 1832330
#> 6       1      6 45.33071 7076.748 1931638