Noble (Aptar Pharma) secures US patent for AI sound detection in drug-delivery and diagnostic devices
- A U.S. patent covers an AI-enabled method to detect, analyze and classify sounds from drug delivery and diagnostic devices.
- The system uses time-series acoustic sensing and neural network–based machine learning to recognize device sound signatures.
- It provides objective feedback on whether critical device-use steps were completed correctly, aiding training, usability and human factors evaluation.
- The patent is part of Aptar’s broader AI strategy spanning patient insights, analytical testing, formulation, quality prediction and digital health.
Patent coverage
The issued U.S. patent covers an artificial intelligence–enabled method for detecting, analyzing and classifying sound output from drug delivery and diagnostic devices to determine whether a device has been operated correctly.
Technical approach
The method applies time-series acoustic sensing combined with neural network–based machine learning to recognize device-generated sound signatures. Because it relies on sound rather than visual markers or hardware modifications, it is suited to training programs, usability studies and human factors evaluation.
Applications and context
The technology is intended to determine whether critical device-use steps were completed successfully and to provide objective feedback that supports correct device use. That capability is positioned as increasingly important as therapies shift to home and self-administration. The patent is cited as a milestone within Aptar’s broader exploration of AI across patient and consumer insights, analytical and compatibility testing, formulation and product development, quality prediction, digital health solutions and advanced data analytics.
Source: Aptar
