Automated Organization Profile

Institute of Technical Medicine, Furtwangen University

Current S-Index

3.3

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.7

Average Dataset Index per dataset

Total Datasets

2

Total datasets in this organization

Average FAIR Score

73.1%

Average FAIR Score per dataset

Total Citations

2

Total citations to the organization's datasets

Total Mentions

0

Total mentions of the organization's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Respiratory and heart rate monitoring dataset from aeration study (Version: latest)

A study was conducted to collect respiratory pressure and flow data for model-based assessment, alongside electrical impedance tomography (EIT) aeration,electrocardiogram (ECG), and heart-rate belt (HRB) data. A 20 subjects set wasselected with no known significant respiratory abnormalities, under Universityof Canterbury Human Research Ethics Committee (HREC) consent (HREC 2023/30/LR-PS). Subject demographic data was collected using a combination ofmeasurements and a self-reported questionnaire. Subject demographicinformation to ascertain: sex; height; weight; age; any history of asthma,smoking, or vaping; and approximate thoracic cage and breast tissue volumes.The trial was setup with subjects breathing through the pressure and flowmeterusing a full-face mask and filter. Inspiratory and expiratory flow wereseparated using one-way valves for measurement purposes and both ports wererapidly occluded every 200ms to generate passive mechanics assessmentintervals. A continuous positive airway pressure (CPAP) machine was used toprovide positive airway pressure (PEEP) in series with the inspiratory port.Three trials were conducted per subject. Two of which, involved increasingPEEP (0, 4, and 8 cmH2O), and in one of which subjects were asked to performtwo 10s breath holds at each level. The third was a recording of three forcedexpiratory manoeuvres (FEM). These tests were conducted to provide an initialcomparison of current respiratory techniques to model-based methods, whichaims to inform the design of future clinical testing on subjects with knownrespiratory abnormalities.

Authors

  • Guy, Ella Frances Sophia ;
  • Flett, Isaac ;
  • Clifton, Jaimey Anne ;
  • Caljé-van der Klei, Trudy ;
  • Chen, Rongqing ;
  • Knopp, Jennifer ;
  • Moeller, Knut ;
  • Chase, James Geoffrey
0 Citations0 Mentions73% FAIR0.8 Dataset Index
10.13026/cpeg-7b46January 2024

Respiratory and heart rate monitoring dataset from aeration study (Version: 1.0.0)

A study was conducted to collect respiratory pressure and flow data for model-based assessment, alongside electrical impedance tomography (EIT) aeration,electrocardiogram (ECG), and heart-rate belt (HRB) data. A 20 subjects set wasselected with no known significant respiratory abnormalities, under Universityof Canterbury Human Research Ethics Committee (HREC) consent (HREC 2023/30/LR-PS). Subject demographic data was collected using a combination ofmeasurements and a self-reported questionnaire. Subject demographicinformation to ascertain: sex; height; weight; age; any history of asthma,smoking, or vaping; and approximate thoracic cage and breast tissue volumes.The trial was setup with subjects breathing through the pressure and flowmeterusing a full-face mask and filter. Inspiratory and expiratory flow wereseparated using one-way valves for measurement purposes and both ports wererapidly occluded every 200ms to generate passive mechanics assessmentintervals. A continuous positive airway pressure (CPAP) machine was used toprovide positive airway pressure (PEEP) in series with the inspiratory port.Three trials were conducted per subject. Two of which, involved increasingPEEP (0, 4, and 8 cmH2O), and in one of which subjects were asked to performtwo 10s breath holds at each level. The third was a recording of three forcedexpiratory manoeuvres (FEM). These tests were conducted to provide an initialcomparison of current respiratory techniques to model-based methods, whichaims to inform the design of future clinical testing on subjects with knownrespiratory abnormalities.

Authors

  • Guy, Ella Frances Sophia ;
  • Flett, Isaac ;
  • Clifton, Jaimey Anne ;
  • Caljé-van der Klei, Trudy ;
  • Chen, Rongqing ;
  • Knopp, Jennifer ;
  • Moeller, Knut ;
  • Chase, James Geoffrey
2 Citations0 Mentions73% FAIR2.6 Dataset Index
10.13026/e4dt-f689January 2024