Keywords: biological signal, electromyography (EMG), feature reduction, Matlab, myoelectric control, myoelectric signals (MES), pattern classification, prosthetic control, prosthesis, signal processing
If you are using these files (or a modification of these files) provide an acknowledgment (e.g. in publications) for their usage.
The Matlab files will enable people researching MES/EMG classification methods to have a common methodology to compare against. The methodology used is a relatively simple and direct approach using ULDA feature reduction and a LDA classifier; however, has shown to be quite effective. Usage of these files (or a modification of these files) should reference:
| 09-10-06 | MECexample.zip | Example code and data to classify eight channels of myoelectric data to predict seven upper arm motions (i.e. using electromyography (EMG) signals for control of upper limb prostheses). |
| getrmsfeat.m | root mean square feature | |
| getmavfeat.m | mean absolute value feature | |
| getiavfeat.m | integrated absolute value feature | |
| getarfeat.m | autoregressive feature | |
| getzcfeat.m | zero crossing feature | |
| getsscfeat.m | slope sign change feature | |
| getwlfeat.m | waveform length feature | |
| scatterplot.m | creates a scatter plot of the feature vector (likely want to use pca or ulda feature reduction first) |
| pca_feature_reduction.m | principal component analysis feature reduction | |
| ulda_feature_reduction.m | uncorrelated linear discriminant analysis feature reduction |
| score_classify.m | converts columns of scores into classification outputs (numbers) | |
| confmat.m | generates a confusion matrix | |
| plotconfmat.m | plots a confusion matrix | |
| plotconfmattext.m | plots a confusion matrix in text format | |
| find_rank.m | find the rank of a particular class given columns of scores | |
| rank_classify.m | converts columns of scores into ranks | |
| majority_vote.m | performs majority vote post processing on classification decisions | |
| classification_timeplot.m | plots classification results as a function of time | |
| lda_classify.m | classification performed by linear discriminant analysis | |
| knn_classify.m | classification performed by k-nearest neighbors |
| meanfrequency.m | computes the mean frequency | |
| 09-10-07 | medianfrequency.m | computes the median frequency |
| SMratio.m | computes the signal-to-motion artifact ratio | |
| DPratio.m | computes the maximum-to-minimum drop in power density | |
| SNratio.m | computes the signal-to-noise ratio | |
| OHMratio.m | computes the spectral deformation |
| remove_transitions.m
|
will remove transitional data (e.g. from a time series of feature vectors) |
| anc_lms.m | adaptive filter using the LMS algorithm | |
| anc_rls.m | adaptive filter using the RLS algorithm |
| find_delay.m | finds the delay (in samples) between two signals | |
| approxequal.m | logical function to compare numbers to see if they are within a certain tolerance of each other | |
| remove_mean.m | removes the mean from signals that arranged in columns | |
| gausspdf.m | computes the Gaussian probability distribution function | |
| loggausspdf.m | computes the log Gaussian probability distribution function | |
| prd.m | computes the percent residual difference | |
| M15GUI | software to configure the Grass-Telefactor Model 15 Neurodata Amplifier System | |
| findqrs_mobd.m | this function is an implementation of the MOBD algorithm for QRS detection |
The files provided are distributed "AS IS" and "WITH ALL FAULTS". We do not offer a warranty for the content or use of these files nor do we guarantee their quality, accuracy, fitness for a particular purpose, or safety - either expressed or implied. All questions, complaints, issues, and claims related to files should be directed to the contributing author.
You assume all risk associated with downloading these files from this site. You are solely responsible for protecting yourself against viruses, and backing up data, files and hardware used in conjunction with the files.
Matlab is a registered trademark of The Mathworks, Inc.
Last updated 09-10-07