Predicting COPD symptoms from wearable sensor data

What is it about?

This paper investigates the use of sensing technologies to monitor people with a lung disease called COPD directly from their homes. Data from 30 patients monitored for three months is used to predict how severe patients' COPD symptoms are. We found that medical information and air quality data are essential for understanding the overall severity of the disease. At the same time, sleep and physical activity help predict changes in the condition over time. This study shows that remote monitoring has the potential for managing COPD and helps us understand which information is most helpful.

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Photo by Towfiqu barbhuiya on Unsplash

Photo by Towfiqu barbhuiya on Unsplash

Why is it important?

COPD is a widespread and debilitating lung disease affecting millions globally. Exploring remote patient monitoring is especially important in the context of the COVID-19 pandemic and the increasing need for telehealth solutions. Thus, developing predictive models to evaluate disease severity would reduce the burden on health providers and make another step towards personalized healthcare.