An official website of the United States government
Remote monitoring and evaluation of pulmonary diseases via telemedicine are important to disease diagnosis and management, but current telemedicine solutions have limited capability of objectively examining the airway's internal physiological conditions that are crucial to pulmonary disease evaluation. Existing solutions based on smartphone sensing are also limited to externally monitoring breath rates, respiratory events, or lung function. In this paper, we present PTEase, a new system design that addresses these limitations and uses commodity smartphones to examine the airway's internal physiological conditions. PTEase uses active acoustic sensing to measure the internal changes of lower airway caliber, and then leverages machine learning to analyze the sensory data for pulmonary disease evaluation. We implemented PTEase as a smartphone app, and verified its measurement error in lab-controlled settings as <10%. Clinical studies further showed that PTEase reaches 75% accuracy on disease prediction and 11%-15% errors in estimating lung function indices. Given that such accuracy is comparable with that in clinical practice using spirometry, PTEase can be reliably used as an assistive telemedicine tool for disease evaluation and monitoring.
more »
« less
Out-Clinic Pulmonary Disease Evaluation via Acoustic Sensing and Multi-Task Learning on Commodity Smartphones
Pulmonary diseases, such as asthma and Chronic Obstructive Pulmonary Disease (COPD), constitute a major public health challenge. The disease symptoms, including airway obstruction and inflammation, usually result in changes in airway mechanical properties, such as the caliber and impedance of the airway. To measure such airway properties for disease evaluation and diagnosis purposes, pulmonary function tests (PFT) has been widely adopted. However, most existing PFT systems require expensive and cumbersome hardware that are impossible to be used out of clinic. To allow out-clinic continuous pulmonary disease evaluation, in this paper we present AWARE, a new sensing and AI system that supports accurate and reliable PFT using commodity smartphones. AWARE uses a smartphone to transmit acoustic signals and reconstructs the profile of human airway based on the analysis of reflected acoustic waves captured from the smartphone's microphone. The subject's pulmonary condition is then evaluated by a multi-task learning model that integrates both the airway measurements and the subject's lung function records as the ground truth. Evaluations on 75 human subjects demonstrate that AWARE has the capability to achieve 80% accuracy on distinguishing between humans with healthy pulmonary function and with asthma symptoms.
more »
« less
- PAR ID:
- 10454228
- Date Published:
- Journal Name:
- Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems
- Page Range / eLocation ID:
- 1182 to 1188
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
First- and second-hand exposure to smoke or air pollutants is the primary cause of chronic obstructive pulmonary disease (COPD) pathogenesis, where genetic and age-related factors predispose the subject to the initiation and progression of obstructive lung disease. Briefly, airway inflammation, specifically bronchitis, initiates the lung disease, leading to difficulty in breathing (dyspnea) and coughing as initial symptoms, followed by air trapping and inhibition of the flow of air into the lungs due to damage to the alveoli (emphysema). In addition, mucus obstruction and impaired lung clearance mechanisms lead to recurring acute exacerbations causing progressive decline in lung function, eventually requiring lung transplant and other lifesaving interventions to prevent mortality. It is noteworthy that COPD is much more common in the population than currently diagnosed, as only 16 million adult Americans were reported to be diagnosed with COPD as of 2018, although an additional 14 million American adults were estimated to be suffering from COPD but undiagnosed by the current standard of care (SOC) diagnostic, namely the spirometry-based pulmonary function test (PFT). Thus, the main issue driving the adverse disease outcome and significant mortality for COPD is lack of timely diagnosis in the early stages of the disease. The current treatment regime for COPD emphysema is most effective when implemented early, on COPD onset, where alleviating symptoms and exacerbations with timely intervention(s) can prevent steep lung function decline(s) and disease progression to severe emphysema. Therefore, the key to efficiently combatting COPD relies on early detection. Thus, it is important to detect early regional pulmonary function and structural changes to monitor modest disease progression for implementing timely interventions and effectively eliminating emphysema progression. Currently, COPD diagnosis involves using techniques such as COPD screening questionnaires, PFT, arterial blood gas analysis, and/or lung imaging, but these modalities are limited in their capability for early diagnosis and real-time disease monitoring of regional lung function changes. Hence, promising emerging techniques, such as X-ray phase contrast, photoacoustic tomography, ultrasound computed tomography, electrical impedance tomography, the forced oscillation technique, and the impulse oscillometry system powered by robust artificial intelligence and machine learning analysis capability are emerging as novel solutions for early detection and real time monitoring of COPD progression for timely intervention. We discuss here the scope, risks, and limitations of current SOC and emerging COPD diagnostics, with perspective on novel diagnostics providing real time regional lung function monitoring, and predicting exacerbation and/or disease onset for prognosis-based timely intervention(s) to limit COPD–emphysema progression.more » « less
-
Recent respiratory outbreaks have garnered substantial attention, yet most respiratory monitoring remains confined to physical signals. Exhaled breath condensate (EBC) harbors rich molecular information that could unveil diverse insights into an individual’s health. Unfortunately, challenges related to sample collection and the lack of on-site analytical tools impede the widespread adoption of EBC analysis. Here, we introduce EBCare, a mask-based device for real-time in situ monitoring of EBC biomarkers. Using a tandem cooling strategy, automated microfluidics, highly selective electrochemical biosensors, and a wireless reading circuit, EBCare enables continuous multimodal monitoring of EBC analytes across real-life indoor and outdoor activities. We validated EBCare’s usability in assessing metabolic conditions and respiratory airway inflammation in healthy participants, patients with chronic obstructive pulmonary disease or asthma, and patients after COVID-19 infection.more » « less
-
Since its invention in the late 1980s, the air-liquid-interface (ALI) culture system has been the standard in vitro model for studying human airway biology and pulmonary diseases. However, in a conventional ALI system, cells are cultured on a porous plastic membrane that is much stiffer than human airway tissues. Here, we develop a gel-ALI culture system by simply coating the plastic membrane with a thin layer of hydrogel with tunable stiffness matching that of healthy and fibrotic airway tissues. We determine the optimum gel thickness that does not impair the transport of nutrients and biomolecules essential to cell growth. We show that the gel-ALI system allows human bronchial epithelial cells (HBECs) to proliferate and differentiate into a pseudostratified epithelium. Further, we discover that HBECs migrate significantly faster on hydrogel substrates with stiffness matching that of fibrotic lung tissues, highlighting the importance of mechanical cues in human airway remodeling. The developed gel-ALI system provides a facile approach to studying the effects of mechanical cues in human airway biology and in modeling pulmonary diseases.more » « less
-
null (Ed.)Idiopathic Pulmonary Fibrosis (IPF) is a chronically progressive interstitial lung that affects over 3 M people worldwide and rising in incidence. With a median survival of 2–3 years, IPF is consequently associated with high morbidity, mortality, and healthcare burden. Although two antifibrotic therapies, pirfenidone and nintedanib, are approved for human use, these agents reduce the rate of decline of pulmonary function but are not curative and do not reverse established fibrosis. In this review, we discuss the prevailing epithelial injury hypothesis, wherein pathogenic airway epithelial cell-state changes known as Epithelial Mesenchymal Transition (EMT) promotes the expansion of myofibroblast populations. Myofibroblasts are principal components of extracellular matrix production that result in airspace loss and mortality. We review the epigenetic transition driving EMT, a process produced by changes in histone acetylation regulating mesenchymal gene expression programs. This mechanistic work has focused on the central role of bromodomain-containing protein 4 in mediating EMT and myofibroblast transition and initial preclinical work has provided evidence of efficacy. As nanomedicine presents a promising approach to enhancing the efficacy of such anti-IPF agents, we then focus on the state of nanomedicine formulations for inhalable delivery in the treatment of pulmonary diseases, including liposomes, polymeric nanoparticles (NPs), inorganic NPs, and exosomes. These nanoscale agents potentially provide unique properties to existing pulmonary therapeutics, including controlled release, reduced systemic toxicity, and combination delivery. NP-based approaches for pulmonary delivery thus offer substantial promise to modify epigenetic regulators of EMT and advance treatments for IPF.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3560905.3568437
