Skip to contents

EMG Amplitude Features (ARV, MAV, iEMG, RMS)

Source: R/emg-features.R
emgAmplitudeFeatures.Rd

Computes time-domain amplitude features of an EMG signal over a sliding window. The signal is divided into overlapping windows and, for each window and channel, the requested features are computed:

arv

Average rectified value, \(\frac{1}{N}\sum |x_i|\).

mav

Mean absolute value, \(\frac{1}{N}\sum |x_i|\) (identical to ARV for an unweighted window).

iemg

Integrated EMG, \(\sum |x_i|\,\Delta t\) with \(\Delta t = 1 / f_s\); the time integral of the rectified signal, in signal-units times seconds.

rms

Root mean square, \(\sqrt{\frac{1}{N}\sum x_i^2}\).

The window geometry (window and step sizes in samples) matches emgFatigue() and emgSpectralMoments() for identical window_sec and overlap, so amplitude and spectral features align window-for-window.

Usage

emgAmplitudeFeatures(
  x,
  features = c("arv", "mav", "iemg", "rms"),
  window_sec = 1,
  overlap = 0.5,
  assay_name = NULL
)

Arguments

x

A PhysioExperiment object with EMG data.

features

Character vector selecting which features to return; any of "arv", "mav", "iemg", "rms" (default: all four).

window_sec

Analysis window in seconds (default: 1.0).

overlap

Overlap fraction between consecutive windows, in \([0, 1)\) (default: 0.5).

assay_name

Input assay name (default: first assay).

Value

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

channel

Integer channel index.

window

Integer window index within the channel (1-based).

time_sec

Window start time in seconds.

arv, mav, iemg, rms

The requested amplitude features (only the columns named in features are present).

If no full window fits in the signal, a 0-row data.frame with these columns is returned.

References

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

Hermens, H.J. et al. (2000). "Development of recommendations for SEMG sensors and sensor placement procedures (SENIAM)." Journal of Electromyography and Kinesiology, 10(5), 361-374. doi:10.1016/S1050-6411(00)00027-4

See also

emgEnvelope() for a per-sample amplitude envelope, emgFatigue() for windowed spectral fatigue features, emgSpectralMoments() for spectral moments on the same window grid

Examples

# 2 s of two-channel EMG at 1000 Hz
set.seed(1)
m <- matrix(rnorm(2000 * 2, sd = 0.3), nrow = 2000, ncol = 2)
pe <- PhysioExperiment(
  assays = list(raw = m),
  colData = S4Vectors::DataFrame(label = c("EMG1", "EMG2"),
                                 type = c("EMG", "EMG")),
  samplingRate = 1000)
feats <- emgAmplitudeFeatures(pe, window_sec = 0.5, overlap = 0.5)
head(feats)
#>   channel window time_sec       arv       mav      iemg       rms
#> 1       1      1     0.00 0.2395552 0.2395552 0.1197776 0.3033508
#> 2       1      2     0.25 0.2542875 0.2542875 0.1271437 0.3167806
#> 3       1      3     0.50 0.2545804 0.2545804 0.1272902 0.3171735
#> 4       1      4     0.75 0.2496032 0.2496032 0.1248016 0.3129471
#> 5       1      5     1.00 0.2424656 0.2424656 0.1212328 0.3025909
#> 6       1      6     1.25 0.2467168 0.2467168 0.1233584 0.3094300