ArticleDigital health
Intelligent wearable devices with audio collection capabilities to assess chronic obstructive pulmonary disease severity.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05551169 (Establishment of an Algorithm That Can Detect and Infer the Severity Level of COPD by Intelligent Terminal Device), which is not on this map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Establishment of an Algorithm That Can Detect and Infer the Severity Level of COPD by Intelligent Terminal Device
Who cites it
4 citing papers in PubMed.
- Mobile health for chronic obstructive pulmonary disease: a bibliometric analysis based on integrated databases (2000-2025).Frontiers in medicine · 2026Review
- Patients' preferences and perceptions of point-of-care technologies: Survey results from the lung disease community.Journal of clinical and translational science · 2026Article
- Fusion of Generative AI Techniques and Machine Learning Models to Generate and Investigate Biosignals for Glucose Sensors.ACS omega · 2025Article
- The value of cough sound monitoring via an audio-enabled smartwatch for OSA screening in COPD patients: a cross-sectional exploratory study.Frontiers in medicine · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Intelligent wearable devices have potential for chronic obstructive pulmonary disease (COPD) monitoring, but the effectiveness of combining cough and blowing sounds for disease assessment is unclear. Objective: The objective was to assess COPD severity via physiological parameters and audio data collected by a smartwatch. Methods: COPD patients underwent lung function tests, electrocardiograms, blood gas analysis, and 6-min walk tests. The patients' peripheral arterial oxygen saturation (SpO Results: Twenty-nine stable patients, with a mean age of 67.0 ± 5.8 years, were enrolled, and 89.7% were male. HR, HRV, RR, cough sounds, and blowing sounds were significantly correlated with the Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade, with cough sounds showing the highest correlation (r = 0.7617, Conclusions: Audio data were more strongly correlated with lung function in COPD patients than were physiological parameters. A smartwatch with audio collection capabilities effectively assessed COPD severity. Trial Registration: ClinicalTrials.gov NCT05551169.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.