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Capturing Inhalation Eiciency with Acoustic Sensors in Mobile Phones Olga Saukh TU Graz / CSH Vienna, Austria [email protected] ABSTRACT Increasing popularity of inhaled therapy for the treatment of asthma and chronic obstructive pulmonary disease (COPD) stimulates re- search on both drug formulations and smart devices to support eਖ਼cient pulmonary drug delivery. A major concern is the variabil- ity of the drug dose delivered to the lungs from the inhalation devices, due to the following three factors: 1) the drug formulation, 2) the device design, and 3) the patients inhalation prole [23]. य़is paper investigates the use of microphones embedded in modern smartphones to accurately monitor the patients inhalation manouvre. In our experiments we focus on dry powder inhalers (DPIs) with a breath-activated capsule spinning mechanism, such as Breezhaler fl . We design an algorithm to capture inhalation pro- les and evaluate it against measurements obtained with a precise gas ow meter. Our algorithm achieves an average error of up to 4.89 slm (standard liters per minute) given typical inspiratory ow rates through a Breezhaler fl between 60 and 130 slm. We detect capsule rotation to ensure the inhalation was eective, and observe that the capsule spinning mechanism helps reduce measurement errors by 2 slm. Given a proper calibration, the proposed algorithm can be used with other capsule-based DPIs, such as HandiHaler fl . CCS CONCEPTS ۦInformation systems މMobile information processing systems ۦ;Applied computing މConsumer health; Health care information systems; KEYWORDS Medication adherence, mHealth, capsule-based DPI, microphone 1 INTRODUCTION Over one billion people worldwide suer from respiratory diseases including asthma, chronic obstructive pulmonary disease (COPD), disordered breathing, tuberculosis, cystic brosis and respiratory infection [10]. COPD, being associated with the impact of inhaled pollutants, is among the leading causes of death worldwide, al- though its development and progression are poorly understood [6]. Nowadays, treatment of most respiratory diseases is delivered pri- marily through the inhalation path using various devices. य़e ben- et of inhaled therapy is that medication is delivered directly into the airways where it exerts its curing eects locally within the lungs. Unwanted systemic eects on other organs are minimised since the medication acts with maximum pulmonary specicity. As a result, inhaled therapy is the key to modern treatment for asthma and COPD. Inhalers, Adherence and Medical IoT. Optimal disease control highly depends on patient medication adherence. य़ere is a broad range of inhalers available on the market including pressurized metered-dose inhalers (pMDIs), breath-actuated pMDIs, dry powder inhalers (DPIs), nebulizers and soॏ mist inhalers [21]. Inhalers of each type come with their specic usage requirements that orig- inate from their working principle. For patients to gain control of their asthma or COPD, they need to use the inhalers correctly by synchronizing their own inhalation manoeuvre with the drug re- lease paern of the inhaler. However, studies show that 50% of patients use their inhalers incorrectly [2, 11] resulting in wasted medications and higher healthcare costs. य़is motivates the need to take advantage of the medical Internet of य़ings (IoT) by track- ing inhalation eਖ਼ciency, giving patients real-time feedback and pesonalized recommendations. Capsule-based DPIs and Inhalation Prole. DPIs are becom- ing increasingly popular since they support patient adherence by design: they rely on the patients ability to produce suਖ਼cient airow through the device. Inhalers with low airow resistance allow air to ow through them more easily and are, therefore, beer suit- able for COPD patients with muscular weakness or severe airow limitation [4, 7]. Inspiratory ow together with the resistance of a DPI produces the turbulent energy which de-agglomerates the formulation and provides eective emied dose [17]. Each DPI has a minimum threshold energy below which de-agglomeration is inef- cient. Below the minimum threshold energy, the patient will re- ceive no or very lile therapeutic eect from the drug [21]. If the ow acceleration is fast at the start of inhalation, de-agglomeration is increased. By measuring the inhalation ow it can be determined if the drug delivery was eective. In this paper, we run experiments with a Breezhaler fl , a capsule-based DPI that has low airow resistance [27, 31] and is able to deliver a consistent dose of inhaled medication across dierent inhalation ow rates [19, 26]. Our goal is to measure the inhalation prole required to determine the inhalation eਖ਼ciency to improve patient adherence when using conventional inhalers with no extra hardware.

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