Name
Title | ||
|---|---|---|
Long-term, Ambulatory Respiratory Monitoring of COPD Patients using Garment-Adhered Sensors |
Abstract | ||
|---|---|---|
Management of chronic pulmonary diseases currently lacks longitudinal, high-compliant respiratory datasets. Such datasets have the potential to provide insight into the behavioral and physiological factors that predict disease progression and deterioration. Producing such datasets requires devices that can withstand real-world use and yet are unobtrusive enough to yield high patient adherence. This article first describes a set of necessary characteristics for a device to address these issues, informed by stakeholders in pulmonary health monitoring. It then describes Health Tags, a cardiorespiratory sensing platform whereby each device in a set is adhered to a patient's undergarments to ease patient adherence. The paper reports on the longitudinal use of Health Tags among high-risk COPD patients in the home environment. There, Health Tags were worn an average of 78.7% of each 24-hour cycle and 87.1% of daytime hours during an average enrollment period of 35.5 days. No sign of a novelty effect was observed. The results are encouraging for the creation and application of clinically accurate, longitudinal, continuous pulmonary datasets. Such datasets can assist clinicians to improve care and help researchers generate and explore new endpoints related to respiratory disease. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MeMeA.2019.8802187 | 2019 IEEE International Symposium on Medical Measurements and Applications (MeMeA) |
Keywords | Field | DocType |
pulmonary,sensor,wearable,clothing,adhered,longitudinal,respiration,breathing chronic disease management | COPD,Ambulatory,Intensive care medicine,Respiratory disease,Disease progression,Respiratory monitoring,Novelty,Medicine,Cardiorespiratory fitness | Conference |
ISBN | Citations | PageRank |
978-1-5386-8429-0 | 0 | 0.34 |
References | Authors | |
1 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Neema Moraveji | 1 | 0 | 0.34 |
| Phil Golz | 2 | 0 | 0.34 |
| Joanne Hollenbach | 3 | 0 | 0.34 |
| Mark Holt | 4 | 0 | 0.34 |
| Richard Murray | 5 | 0 | 0.34 |