Research Resources
Data
If you would like access to particular data, please contact me via email.
Biomedical Signal Quality Analysis
The Matlab files will enable people researching biomedical signal quality analysis to have a common methodology to compare against.
Keywords: biological signal, biosignal, electrocardiogram (EMG), Matlab, signal quality index (SQI), signal processing, signal quality analysis
Usage
If you are using these files (or a modification of these files) provide an acknowledgment (e.g. in publications) for their usage. Usage of these files (or a modification of these files) should reference:
(20-07-16) Example code of SQI that contaminates ECG with motion artifact at different levels of SNR and shows how the SQI varies with SNR.
signal quality index for ECG
Motion Artifact Signal Generation Toolkit
These files include simulated motion artifact, pretrained models to simulate motion artifact, and the ability to train new models. The models include an autoregressive (AR) model, a Markov chain model, and a recurrent neural network (RNN). The simulated motion artifact can be added to bioelectric signal recordings (e.g., ECG, EMG) for biomedical signal quality analysis research.
Keywords: biological signal, biosignal, electrocardiogram (EMG), motion artifact, python, signal processing, signal quality analysis
Usage
If you are using these files (or a modification of these files) provide an acknowledgment (e.g. in publications) for their usage. Usage of these files (or a modification of these files) should reference:
(22-08-08) Simulated motion artifact, pretrained models to simulate motion artifact, and software to train and simulate motion artifact.
Motion Artifact Signal Database
These files include motion artifact signals obtained by taking 84 ambulatory ECG recordings from the and removing the ECG. Each recording is about 24-hours in length.
Keywords: biological signal, biosignal, motion artifact, signal quality analysis
Usage
If you are using these files (or a modification of these files) provide an acknowledgment (e.g. in publications) for their usage. Usage of these files (or a modification of these files) should reference:
- Kulpa J, Chan ADC, “Electrocardiogram Removal to Establish a Motion Artifact Database”, submitted to IEEE Canadian Conference on Electrical and Computer Engineering, Regina SK, Canada, 2023.
(23-04-22) A sample of 10 motion artifact signals, each around 24-hours in length.
Myoelectric Control (MECLab)
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 an LDA classifier; however, it has shown to be quite effective.
Keywords: biological signal, electromyography (EMG), feature reduction, Matlab, myoelectric control, myoelectric signals (MES), pattern classification, prosthetic control, prosthesis, signal processing
Usage
If you are using these files (or a modification of these files) provide an acknowledgment (e.g. in publications) for their usage. Usage of these files (or a modification of these files) should reference:
Myoelectric Control Example
(10-02-08) 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).
Feature Extraction
root mean square feature
mean absolute value feature
integrated absolute value feature
autoregressive feature
zero crossing feature
slope sign change feature
waveform length feature
creates a scatter plot of the feature vector (likely want to use pca or ulda feature reduction first)
Feature Reduction
principal component analysis feature reduction
uncorrelated linear discriminant analysis feature reduction
Classification
converts columns of scores into classification outputs (numbers)
generates a confusion matrix
plots a confusion matrix
plots a confusion matrix in text format
find the rank of a particular class given columns of scores
converts columns of scores into ranks
performs majority vote post processing on classification decisions
plots classification results as a function of time
classification performed by linear discriminant analysis
classification performed by k-nearest neighbors
Myoelectric signal processing
computes the mean frequency
(09-10-07) computes the median frequency
computes the signal-to-motion artifact ratio
computes the maximum-to-minimum drop in power density
computes the signal-to-noise ratio
computes the spectral deformation
Miscellaneous
(10-02-08) will remove transitional data (e.g. from a time series of feature vectors)
ECG Person Identification
Keywords: biological signal, electrcardiography (ECG), electrcardiogram, wavelet, Matlab, biometric, person identification
Usage
If you are using these files (or a modification of these files) provide an acknowledgment (e.g. in publications) for their usage. Usage of these files (or a modification of these files) should reference:
ECG from 10 subjects from three sessions on separate days.
wavelet distance measure
Adaptive Signal Processing
adaptive filter using the LMS algorithm
adaptive filter using the RLS algorithm
Miscellaneous
finds the delay (in samples) between two signals
logical function to compare numbers to see if they are within a certain tolerance of each other
removes the mean from signals that are arranged in columns
computes the Gaussian probability distribution function
computes the log Gaussian probability distribution function
computes the percent residual difference
computes fft with corresponding frequencies (fftshift is optional)
software to configure the Grass-Telefactor Model 15 Neurodata Amplifier System
this function is an implementation of the MOBD algorithm for QRS detection
this function loads data from Axon file (generated from AxoScope)
Disclaimer
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