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Normalize EMG Signal

Source: R/preprocess_normalize.R
normalize_emg.Rd

Normalizes EMG signals using various methods to allow comparison across channels, subjects, or sessions.

Usage

normalize_emg(data, method = "max", reference = NULL, per_channel = TRUE)

Arguments

data

EMG signal. Can be a numeric vector (single channel), a matrix (T x M, time x channels), or a list of matrices.

method

Normalization method:

  • "max": Divide by maximum value (default)

  • "mvc": Divide by Maximum Voluntary Contraction reference

  • "mean": Divide by mean value

  • "zscore": Z-score standardization (subtract mean, divide by SD)

  • "range": Min-max normalization to [0, 1]

  • "median": Divide by median value (robust to outliers)

reference

Reference values for MVC normalization. Can be a single value (applied to all channels) or a vector (one value per channel). Only used when method = "mvc".

per_channel

Logical. If TRUE (default), normalize each channel independently. If FALSE, use global statistics across all channels.

Value

Normalized EMG signal, same structure as input.

Details

Normalization is essential for:

  • Comparing EMG across different muscles

  • Comparing EMG across different subjects

  • Comparing EMG across different recording sessions

MVC normalization (method = "mvc") is the gold standard in EMG research, expressing activation as a percentage of maximum voluntary contraction. Requires separate MVC trials for reference.

Max normalization (method = "max") is useful when MVC data is not available, normalizing to the peak value in the data.

Examples

# Max normalization (0 to 1 range)
emg <- matrix(rnorm(1000), ncol = 4)
norm_emg <- normalize_emg(emg, method = "max")

# MVC normalization (% MVC)
mvc_values <- c(100, 150, 80, 120)  # MVC for each channel
norm_emg <- normalize_emg(emg, method = "mvc", reference = mvc_values)

# Z-score normalization
norm_emg <- normalize_emg(emg, method = "zscore")