Feature evaluation of accelerometry signals for cough detection.

Cough is a common symptom of multiple respiratory diseases, such as asthma and chronic obstructive pulmonary disorder. Various research works targeted cough detection as a means for continuous monitoring of these respiratory health conditions. This has been mainly achieved using sophisticated machine learning or deep learning algorithms fed with audio recordings.

Performance Evaluation of Embedded Image Classification Models Using Edge Impulse for Application on Medical Images.

This work explores the possibility of applying edge machine learning technology in the context of portable medical image diagnostic systems. This was done by evaluating the performance of two machine learning (ML) algorithms, that are widely used on medical images, embedding them into a resource-constraint Nordic nrf52840 microcontroller. The first model was based on transfer learning of the MobileNetVI architecture.