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Acoustic Analysis of Inhaler Sounds from Community-Dwelling Asthmatic Patients for Automatic Assessment of Adherence

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Audio signal (a) and corresponding spectrogram (b) of DiskusTM inhaler use showing the blister, exhalation and inhalation events.
Audio signal (a) and corresponding spectrogram (b) of Diskus™ inhaler use showing the blister, exhalation and inhalation events.

Inhalers are devices which deliver medication to the airways in the treatment of chronic respiratory diseases. When used correctly inhalers relieve and improve patients’ symptoms. However, adherence to inhaler medication has been demonstrated to be poor, leading to reduced clinical outcomes, wasted medication and higher healthcare costs. There is a clinical need for a system that can accurately monitor inhaler adherence as currently no method exists to evaluate how patients use their inhalers between clinic visits. This study presents a method of automatically evaluating inhaler adherence through acoustic analysis of inhaler sounds. An acoustic monitoring device was employed to record the sounds patients produce while using a DiskusTM dry powder inhaler, in addition to the time and date patients use the inhaler. An algorithm was designed and developed to automatically detect inhaler events from the audio signals and provide feedback regarding patient adherence. The algorithm was evaluated on 407 audio files obtained from 12 community dwelling asthmatic patients. Results of the automatic classification were compared against two expert human raters. For patient data for whom the human raters Cohen’s kappa agreement score was greater than 0.81, results indicated that the algorithm’s accuracy was 83% in determining the correct inhaler technique score compared to the raters. This study has several clinical implications as it demonstrates the feasibility of using acoustics to objectively monitor patient inhaler adherence and provide real-time personalized medical care for a chronic respiratory illness.
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See complete bios of the authors in the full version of this article.
M HolmesM Holmes
Mr. Holmes has been a PhD researcher with the Trinity Centre for Bioengineering in Trinity College Dublin, Ireland since 2011. His research interests lie in the area of biomedical engineering, including acoustic signal processing, developing objective metrics for analysing inhaler therapy and treating respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD).

S D'ArcyS D’Arcy
Dr. D’Arcy is currently a Project Manager in the Trinity Centre for Bioengineering, working primarily on medical device commercialisation and clinical trial management. Her research has included the use of speech as a potential bio marker of early onset of cognitive decline.

R CostelloR Costello
Dr. Costello is currently a Consultant Physician in Respiratory Medicine at Beaumont Hospital, Dublin, Ireland and Associate Professor of Medicine at the Royal College of Surgeons in Ireland. He is involved in both the clinical and research aspects of asthma, rhinitis and sleep medicine.

R ReillyR Reilly
Dr. Reilly is currently President of the European Society of Engineering and Medicine (ESEM). His research focuses on clinical neural engineering based on high density electrophysiological and neuroimaging based analysis of sensory and cognitive processing, analysis of data acquired from implanted devices and also bioacoustics.

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