Summary:
UCLA researchers in the Department of Medicine have developed a novel software that is capable of analyzing and interpreting standardized cardiopulmonary exercise data and facilitating pattern recognition and data visualization, providing users key insights from raw data.
Background:
A wide array of exercises exist to evaluate cardiopulmonary health. Interpretation of raw exercise data can be a challenge, as this data varies significantly across exercise type. Standard output formats include work rate, oxygen uptake, carbon dioxide output, heart rate and ventilation. However, identifying key metrics and valuable trends from raw data remains a challenge due to the variety and sheer quantity of data recorded. On top of inconsistent data processing, faulty data visualization can also lead to inconsistent interpretation of these cardiopulmonary tests. These shortcomings in the state of the art have ultimately led to a roadblock to valuable interpretation of data. In order to increase the likelihood that the output of these cardiopulmonary exercise tests is correctly interpreted, there is a clear need for user-friendly software that is capable of reproducible data analysis and visualization.
Innovation:
To address this issue, researchers at UCLA led by Prof. Christopher Cooper have developed a novel cardiopulmonary exercise data analysis tool. This software uses a series of embedded algorithms to robustly analyze data from standard exercise data file formats. The software then generates visuals for the repeatable interpretation of this health data. Together these features increase the reproducibility and efficacy of standard cardiopulmonary exercise tests. This innovation facilitates the interpretation of exercise test data via visualization, empowering end-users with valuable and actionable information.
Potential Applications:
• Cardiopulmonary exercise data interpretation
• Biometric analysis
• Athletic performance tests
Advantages:
• Standardized data analysis algorithms
• Robust data smoothing and processing
• Interpretable data visualization
Development to Date:
Prototype software has been successfully generated and tested on existing Cardiopulmonary Exercise Data.