CAT Score Prediction for COPD Patients using a Chest-Wearable Respeck

The COPD Assessment Test (CAT) consists of 8 questions, each one scored by patients on a scale of 0 to 5 points, and the aggregate score provides a self-assessment of the impact of their symptoms on their well-being. In the nature of questionnaires, the numeric CAT score is a subjective assessment by COPD patients on the effect of symptoms on their personal condition. This paper evaluates the pulmonary response of COPD patients wearing the Respeck device, during exertion when performing pulmonary rehabilitation (PR) exercises at home, as a measure of their wellbeing. Machine learning models were developed to use features derived from the Respeck respiratory rate and physical activity data during the PR exercises as objective measures to associate with the CAT score on the same day and to predict the CAT score for the next day. Results are presented for COPD patients in terms of standard error metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and clinically-relevant minimum clinically important difference (MCID).

Authors

Institutions

Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1109/bibe63649.2024.10820481
Citations
1
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
0.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CAT Score Prediction for COPD Patients using a Chest-Wearable Respeck

Laura J. Gray, M. Prior, Pam Peters, C. A. Bates et al.
1 citations
Cardiovascular Function and Risk Factors
0.40
article

CAT Score Prediction for COPD Patients using a Chest-Wearable Respeck

Laura J. Gray, M. Prior, Pam Peters, C. A. Bates, D. K. Arvind
article en
1 citations

Abstract

The COPD Assessment Test (CAT) consists of 8 questions, each one scored by patients on a scale of 0 to 5 points, and the aggregate score provides a self-assessment of the impact of their symptoms on their well-being. In the nature of questionnaires, the numeric CAT score is a subjective assessment by COPD patients on the effect of symptoms on their personal condition. This paper evaluates the pulmonary response of COPD patients wearing the Respeck device, during exertion when performing pulmonary rehabilitation (PR) exercises at home, as a measure of their wellbeing. Machine learning models were developed to use features derived from the Respeck respiratory rate and physical activity data during the PR exercises as objective measures to associate with the CAT score on the same day and to predict the CAT score for the next day. Results are presented for COPD patients in terms of standard error metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and clinically-relevant minimum clinically important difference (MCID).

Borders General Hospital (GB), University of Edinburgh (GB)
Gender equality
Openalex Percentile: Top 29%
Cardiovascular Function and Risk Factors
0.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.