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PulmoListener: Continuous Acoustic Monitoring of Chronic Obstructive Pulmonary Disease in the Wild

Published: 27 September 2023 Publication History

Abstract

Prior work has shown the utility of acoustic analysis in controlled settings for assessing chronic obstructive pulmonary disease (COPD) --- one of the most common respiratory diseases that impacts millions of people worldwide. However, such assessments require active user input and may not represent the true characteristics of a patient's voice. We propose PulmoListener, an end-to-end speech processing pipeline that identifies segments of the patient's speech from smartwatch audio collected during daily living and analyzes them to classify COPD symptom severity. To evaluate our approach, we conducted a study with 8 COPD patients over 164 ± 92 days on average. We found that PulmoListener achieved an average sensitivity of 0.79 ± 0.03 and a specificity of 0.83 ± 0.05 per patient when classifying their symptom severity on the same day. PulmoListener can also predict the severity level up to 4 days in advance with an average sensitivity of 0.75 ± 0.02 and a specificity of 0.74 ± 0.07. The results of our study demonstrate the feasibility of leveraging natural speech for monitoring COPD in real-world settings, offering a promising solution for disease management and even diagnosis.

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  • (2024)Feasibility of a wearable self-management application for patients with COPD at home: a pilot studyBMC Medical Informatics and Decision Making10.1186/s12911-024-02461-y24:1Online publication date: 5-Mar-2024

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 7, Issue 3
September 2023
1734 pages
EISSN:2474-9567
DOI:10.1145/3626192
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Published: 27 September 2023
Published in IMWUT Volume 7, Issue 3

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  1. datasets
  2. gaze detection
  3. neural networks
  4. text tagging

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  • (2024)Feasibility of a wearable self-management application for patients with COPD at home: a pilot studyBMC Medical Informatics and Decision Making10.1186/s12911-024-02461-y24:1Online publication date: 5-Mar-2024

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