In ymatts/emgR: surface electromyography (sEMG) analyzer with R

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

emgR overview

• Analysis suites for surface electromyography (sEMG) data
• Basic process functionality
  • Bandpass filter
  • Qunatification
  • Normalization
• Advanced analysis
  • Waveform simililarity analysis
    • Coherence analysis (incl. wavelet)
    • Auto/cross correlation analysis
  • Similiarity based muscle network analysis

Install emgR package

# install.packages("devtools") if not installed
devtools::install_github("https://github.com/ymatts/emgR")
library(emgR)

Data acquisition

• From Santuz et al. (2018)
• 13 muscles sEMG (1000 Hz) records during gait cycle
• Time data will be required for constructing emgR object

data(emg)
head(emg,3)

Constructing object

• emgList is a method for constructing emgR object
• emgList object is simply a list data structure
• Input time (sec) and multi channel sEMG data
  • Time is in row and Muscles are in colums

tt = emg$Time # Time record
xx = emg[,-1] # EMG record
obj = emgR::emgList(x = xx,t = tt)
obj

Filtering sEMG signals

• Bandpass filter using butterworth filter
• Filtered objects will be overwride in emgR
• Default setting is order 4 and [5,200] bandpass filter

obj = emgR::btw(obj,order = 4,filtFreq = c(5,200))
obj

Normalize sEMG signals

• Several normalizing methods will be implemted
  • Default setting use simple Maximum Voluntary Contruct (MVC)

obj = emgR::normalize(obj)
obj

Waveform similiarity analysis

• Coherence analysis
  • Linear coherence / Wavelet coherence
• Correlation analysis
  • Auto/Cross-correlation, Distance correlation etc.
• Default setting is linear coherence by stats::spec.pgram() function

obj = emgR::coherence(obj)
obj

Visualize coherence function

• Muscle $^times$ Muscle smoothed coherences are plotted
• The plot is saved in file path with files
• cohRange is which frequency range should be considered
• This takes several time

plot(obj,type="coh",files = "myCoh.jpg",cohRange=c(0,100))

Visualize coherence functions

knitr::include_graphics("~/Dropbox/matsui/git/emgR/myCoh.jpg")

Aggregate coherence function into means within frequency bands

• Average aggregation by frequecies such as $\alpha$, $\beta$, $\gamma$ bands.
• Frequency can be specified with cohRange by vector.
  • Following example shows averaged coherence from 15 Hz to 20 Hz.
• Heatmap of aggregated coherence can be visulized by plot.it argument

obj = emgR::aggrCoh(obj,cohRange = c(15,20),plot.it = FALSE)
obj

Aggregate coherence function into means within frequency bands

obj = emgR::aggrCoh(obj,cohRange = c(15,20),plot.it = TRUE)

Coherent muscle network construction

• Network is constructed via aggregated coherence
• Two mode of networks:
  • Weighted network can be constructed with mode="weighted"
  • Not weighted network can be constructed with mode="bin"
• Coherence is binarized with thres argument
  • Default thres is 0.25
• You can visualize network via plot.it argument.

obj = emgR::cohNet(obj,mode = "bin",thres = 0.25,plot.it = FALSE)

Coherent muscle network construction

obj = emgR::cohNet(obj,mode = "bin",thres = 0.25,plot.it = TRUE)

ymatts/emgR documentation built on March 7, 2020, 12:52 a.m.