Waveform data represents important information and can provide valuable insights about the patient health, for example about cardiac dysfunction that can be induced by sepsis. However, only a few studies have utilized waveform data when developing machine learning models for ICU-relevant applications. Our project partner is working on extracting raw waveform data from bed-side monitors in the ICU. To support the involved clinicians in validating the data quality, we are developing a graphical interface in MATLAB to display the recorded signals.
The main functionalities are:
- Display different channels of ECG, SpO2, and blood pressure curves aligned over time
- Slide through time by changing the position and length of the displayed window
- Slider to scale the y-axis for the signals separately
- De-/select curves and groups of curves to display
- Scale the background grid based on ECG paper speed.
Screenshot:
The code uses the implementation of the Pan-Tompkins QRS-detector from https://de.mathworks.com/matlabcentral/fileexchange/45840-complete-pan-tompkins-implementation-ecg-qrs-detector
H. Sedghamiz, "Matlab Implementation of Pan Tompkins ECG QRS detector.", March 2014. https://www.researchgate.net/publication/313673153_Matlab_Implementation_of_Pan_Tompkins_ECG_QRS_detect
J. Pan.J, W.J. Tompkins. ,"A Real-Time QRS Detection Algorithm" IEEE Transactions on Biomedical Engineering, vol. BME-32, No. 3, 1985.