READ ME File For 'Dataset in support of the thesis 'Model Predictive Valve Control to Assist in Tracking a Lung Pressure Profile''

Dataset DOI: 10.5258/SOTON/D3383

ReadMe Author: MICHAEL CALLUM THOMPSON, University of Southampton, https://orcid.org/https://orcid.org/0000-0002-3254-6804

This dataset supports the thesis entitled: Model Predictive Valve Control to Assist in Tracking a Lung Pressure Profile
AWARDED BY: Univeristy of Southampton
DATE OF AWARD: 2025

DESCRIPTION OF THE DATA:

Data includes all control datasets for this research as well as all identification datasets. These are in '.xlsx' format requiring Microsoft Excel software or similar. This data was collected using the equipment stated in the thesis.

Each control file title gives:
Waveform type and the minimum step possible - e.g. Rand5 (Random - 5cmH2O)
Minimum pressure - e.g. 10 (10cmH2O)
Maximum pressure - e.g. 40 (40cmH2O)
Time between each pressure change - e.g. 3 (3 seconds)
Type of control - e.g. Prop (proportional), roll (PI control), Cons160 (constant 160 cmH2O/L/s)
Number of data points - e.g. 2705 (2705 datapoints at 100Hz = 27.05 seconds)
(Possibly) 11 - there were two types of MPVC, 11 corresponds to the EKF setup as mentioned in the thesis.

Each identification file title gives:
Waveform type - Flat (i.e. a constant pressure reference)
Target pressure - e.g. 10 (10cmH2O)
Resistance value - Cons160 (constant 160 cmH2O/L/s)
Number of data points - e.g. 200 (200 datapoints at 100Hz = 2 seconds)
Type of ID procedure - vstep (a change in resistance from 1000 cmH2O/L/s to the resistance value given), rstep (start from 0 cmH2O and reach the target pressure)


Additional files include:

'.m' files - these are Matlab codes used to process the data collected
'.mat' files - these are Matlab matrix files generated by the Matlab code
'.csv' files - these are files that are generated by the Matlab code and can be opened using Excel or Matlab


This dataset contains:
The above mention data and corresponding processing code files of data collected for the thesis from human participants



Date of data collection: 01/01/2024 - 30/03/2024


Information about geographic location of data collection: 
Collected at University of Southampton Highfield Campus

Licence:
CC BY

Related projects/Funders:
UKRI - EPSRC

Related publications:

Model predictive valve control of lung pressure profile tracking
Model predictive valve control for lung pressure profile tracking assistance
Model Predictive Valve Control to Assist Lung Pressure Profile Tracking (Accepted - not published as of 14/02/2025 - IEEE CST Journal)
Model Predictive Valve Control to Assist in Tracking a Lung Pressure Profile - Thesis

Date that the file was created: February, 2025