Development of a Sound-Based Smart Inhaler With a Mechanical Acoustic Filter for Medication Identification

Improper inhaler use has been a persistent issue lacking clear and standardized guidelines for accurate assessment. This research aims to address this problem by developing an innovative sound-sensing device that provides immediate feedback to patients and medical professionals, ensuring correct medication usage. The study introduces a novel approach to minimizing noise interference by structurally filtering sound through an acoustic simulation system before it reaches the microphone. This method results in a peak flow error of less than 1 L/min and an inhalation duration error of less than 0.5 s. In a clinical trial involving 40 participants, the technology demonstrated over 91% accuracy in medication identification. The development of this highly accurate and standardized system has the potential to significantly improve current clinical practices for inhaler education, setting a new benchmark for correct medication usage.