PhysioLab

PhysioLab is a multivariate signal toolbox created in Matlab to simplify physiological signal processing, especially for out-of-the-lab fitness experiments. The toolbox is intended to assist both researchers and non-experts in the arduous task of processing physiological signals, allowing cross-comparisons between each signal, an automatic feature extraction with manual adjustments and providing a novel visualization for CRF assessment. The toolbox graphically shows the effects of multiple signal processing methods, which facilitates the understanding and prevent common mistakes such as include motion artifacts.

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Physiological Signals

The software provides a wide variety of signal processing methods and artifact removal filters for:

  • Electromyography (EMG): Envelope, RMS, OnSet, FFT, MeanFrequency, MedianFrequency.
  • Electrocardiography (ECG): R-Peak, RRI, HR, HRV, SDNN, RMSD, LF, HF, VLF, LH/HF.
  • Electrodermal Activity (EDA): SCL, MaxVel SCL, GSRs.

Final parameters and processed signals can be exported easily by PhysioLab which supports data from multiple low-cost physiological sensors and allows performing data pre-processing and feature extraction. Multiple features from each signal are extracted to provide the most widely used and documented parameters.

Visualization using radar plots

Additionally, PhysioLab contains a novel tool to visualize multiple physiological parameters in specialized fitness domains using radar plots, providing contextual normative data and facilitating data interpretation.

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Developed by: John Muñoz

If you want to know more about the visualization, please check:
Muñoz, J. E., et al. "Visualization of multivariate physiological data for cardiorespiratory fitness assessment through ECG (R-peak) analysis." 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. (Download)