Embedded machine learning in asthma inhalers changes lives

My son has had asthma since he was three years old. Ben is now 10, and during that time, it’s been fascinating to experience the challenges associated with asthma technique and medication from a parent’s perspective.  

For example: it’s advised that you take your inhaler at morning or at night – but with children, they are tired or groggy at these times and don’t always inhale the medication properly. We have questions such as, “Did my wife already give him some dosage?” Or, “What effect did the cough have just after taking the medication?” It’s often difficult to tell whether one prescription results in better compliance and respiratory outcomes than another.

The humble mechanical inhaler is a marvelous device that can treat the condition. But as both a parent and an engineer, you can’t help thinking how much better it could be.

Working in Arm, it’s all too obvious to see the level of low-power miniaturization being deployed in all sorts of IoT applications, from smart homes to smart textiles. It’s also interesting to look around my son’s bedroom and see the smart toys that have electronics embedded into them.

So, with this technology all around us, improving our everyday lives – could technology be used to help my son’s asthma?