Physiological Signal Analysis and Visualization Software
Laurent Giovangrandi, Omer T. Inan, and Gregory T.A. Kovacs
Electrical Engineering Department, Integrated Circuits Lab, Stanford University
Objectives:
New physiological monitors enable the gathering of multi-parametric physiological data such as ECG, respiration, SpO2, activity and even positional data over long periods of time. The ability to quickly analyze, extract and present pertinent information from these large sets of heterogeneous data has become of prime importance. This project aims at developing a software tool (PhysioExplorer) for the analysis and visualization of these physiological data sets, with an emphasis on intuition-building and interactivity.
The objectives are:
- Development of a modular platform for physiological signal analysis
- Implementation of basic analysis capabilities
- Investigation into new visualization techniques
- Development of novel analysis and data fusion algorithms
Technical Approach:
- The software is implemented under Matlab®, offering both cross-platform compatibility and stand-alone distribution
- Analysis tools are based on published and custom-designed algorithms.
- Data sets are gathered with CPODs monitoring devices, jointly developed by Stanford University and NASA/Ames. These devices simultaneously record 2-lead ECG, respiration (impedance plethysmography), temperature, activity & posture (3-axis accelerometer), SpO2, and optionally blood pressure and GPS data.
Results:
The current version of the software has the following capabilities:
- Fast, interactive browsing
- Extensive plotting capabilities (e.g., Xt, XY, PSD, histogram)
- Signal conditioning (e.g., noise, baseline removal)
- Extraction of respiration and heart rate
- Full ECG delineation (P, Q, R, S and T waves with on/offsets), with PVC detector
- Activity index
- Event triggering (static and dynamic thresholds)
- Export of high-quality plots (EPS, TIFF, JPG)
- Import (EDF+) and export functions (Matlab, CSV)
In addition, the software package has been used to analyze data from recordings in various extreme environments such as KC-135 parabolic flights and high-altitude expeditions at Licancabur, Chile (analyses performed with the support of Dr. Yvonne D. Cagle, consulting professor of medicine at Stanford University and NASA astronaut, and Dr. Judith L. Swain., former chair of medicine at Stanford University, now director of the Singapore Institute for Clinical Sciences).
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| Figure 1. Snapshot of the main GUI, showing the multiple traces in two different time base, timing and trace controls, and the numeric display. | Figure 2. Example of a specialized plot – a power spectrum density plot of heart rate |
Publications:
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