Browsing by Author "Biswas, Rajoshi"

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    Data-Driven Modeling of Lung Deposition of Aerosol Medication Delivered by Metered Dose Inhalers
    (2018-07-12) Biswas, Rajoshi; Sabharwal, Ashutosh; Grande-Allen, Jane
    Chronic pulmonary diseases such as Asthma and COPD (Chronic Obstructive Pulmonary Disease) affect over 510 million worldwide. The most common form of treatment for the management of the diseases is a Metered Dose Inhaler (MDI). Numerous large-scale studies have demonstrated that 70-90% of patients misuse their MDIs leading to wasted medication and poor health outcomes. Due to the nature of inhaled therapy and delayed impact of MDI misuse on health outcomes, patients are unaware of their MDI use technique as well as the resulting lung deposition. In this thesis, I have developed and validated a predictive model of lung deposition corresponding to any MDI technique in three phases. Phase I: I conducted the first pilot study that quantitatively measured MDI technique from 23 physician-diagnosed asthma and COPD adult patients in an outpatient clinic setting. Our results showed that all patients made at least one technique error and 74% made at least three; our quantitative method of measurement recorded 60% more errors than the current gold standard method (using observation alone). Further, I derived an MDI technique model using a parameterized model with a trapezoidal approximation to inspiration curves and includes actuation timing and instantaneous flow-based parameterization. Phase II: To derive lung deposition for any MDI technique (ground truth estimation), I constructed and validated the first in vitro experimental testbed designed to emulate both inspiration and actuation mechanisms of any MDI use in a lab setting. Using this testbed, I determined the significance of inspiration and actuation parameters on in vitro lung deposition of aerosols delivered by Ventolin MDIs. Our results demonstrated that actuation parameters affected lung deposition more significantly (23% difference in lung deposition) than inspiratory flow parameters (<5%). Phase III: With a training dataset of MDI techniques and corresponding in vitro lung deposition, I determined that the model specification for a linear mixed effects model of lung deposition of aerosol from Ventolin MDIs was a function of quadratic inspiration and actuation parameters. I validated the model against in vitro lung deposition measured for the MDI techniques (non-trapezoidal) recorded from patients and had a testing RMSE of 2.3% lung deposition. Hence, we demonstrated the methodology and validation for developing a data-driven model of lung deposition of aerosol medication delivered by any MDI, based on patient representative inhaler use techniques.
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    Measuring Competence in Metered Dose Inhaler Use Using Capmedic Electronic Inhaler MonitoringﾠTool
    (American College of Chest Physicians, 2016) Biswas, Rajoshi; Patel, Gaurav; Mohsin, Ali; Hanania, Nicola A.; Sabharwal, Ashutosh
    It is estimated that up to 70-90% of asthma and COPD patients use their Metered Dose Inhalers (MDIs) incorrectly. However, clinicians often fail to detect patients’ incorrect MDI technique by observation alone. In this study, we quantitatively examined the accuracy of MDI technique of 23 physician-diagnosed asthma and COPD patients in an outpatient clinic setting using CapMedic, an electronic MDI technique-monitoring tool (Cognita Labs, Houston, TX). We used these quantitative data to determine accuracy and limitations of the current practice that empirically assess MDI use by observation alone.
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    SmartInhaler : A Platform for Measurement of Inhaler Usage in Asthma Patients
    (2013-12-06) Biswas, Rajoshi; Sabharwal, Ashutosh; Veeraraghavan, Ashok; Zhong, Lin
    Asthma is a widespread chronic pulmonary disease. Poor management of Asthma results in over 450,000 hospitalizations each year, the majority of which are preventable by strict adherence to asthma control medication. In this thesis, we propose, design and benchmark SmartInhaler, a system which performs automated and unobtrusive measurement of inhaler usage behavior and tracking of outdoor air quality parameters. SmartInhaler consists of an attachment to Metered Dose Inhalers (MDI) developed as a con gurable platform with an aim to measure patient ad- herence to asthma control medication. The attachment is designed to track the parameters associated with asthma medication dosage: number of dosages, time stamp of dosage, location of use and verify the patient taking the medication. Furthermore, based on the location of use, Smart- Inhaler can also track outdoor air quality parameters (concentration of pollutants) using readily available online pollution data. Tracking air quality is useful for the asthma patients since their lung airways can be sensitive to air pollutants. The SmartInhaler attachment communicates with smart phones or tablets through a custom Android application developed for delay-tolerant data collection for both adherence and air quality. In this thesis, we also demonstrate a proof of concept training module for correcting MDI dosage administration technique through air-flow modeling.