Wireless sensors could detect errors in self-administered medication

Patients frequently administer their own medication, which can range from swallowing pills and injecting insulin. However, they don’t always get it right.

Improper adherence to doctors’ orders is commonplace, accounting for thousands of deaths and billions of dollars in medical costs annually, experts have said. So to tackle this, researchers at MIT have developed a system to reduce those numbers for some types of medications.

The new technology pairs wireless sensing with artificial intelligence (AI) to determine when a patient is using an insulin pen or inhaler and flags potential errors in the patient’s administration method.

“Some past work reports that up to 70 per cent of patients do not take their insulin as prescribed, and many patients do not use inhalers properly,” said Dina Katabi, the Andrew and Erna Viteri Professor at MIT, whose research group has developed the new solution.

According to the researchers, users can install the system in their homes and it can alert patients and caregivers to medication errors and potentially reduce unnecessary hospital visits.

Some common drugs entail intricate delivery mechanisms. “For example, insulin pens require priming to make sure there are no air bubbles inside. And after injection, you have to hold for 10 seconds,” said Mingmin Zhao, a PhD student in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). “All those little steps are necessary to properly deliver the drug to its active site.”

Each step also presents an opportunity for errors, especially when there’s no pharmacist present to offer corrective tips, the team said. Patients might not even realise when they make a mistake – so the study’s lead, Zhao, and his team designed an automated system that can.

In terms of the process of the system, first, a sensor tracks a patient’s movements within a 10m radius, using radio waves that reflect off their body. AI then scours the reflected signals for signs of a patient self-administering an inhaler or insulin pen. Finally, the system alerts the patient or their healthcare provider when it detects an error in the patient’s self-administration.

The new sensor sits in the background at home, like a Wi-Fi router, and uses AI to interpret the modulated radio waves. The team developed a neural network to key-in on patterns indicating the use of an inhaler or insulin pen.

The team trained the network to learn those patterns by performing example movements, some relevant (for example, using an inhaler) and some not (for example, eating). Through repetition and reinforcement, the network successfully detected 96 per cent of insulin pen administrations and 99 per cent of inhaler uses.

According to the team, once it was successful at detection, the network also proved useful for correction. Every proper medicine administration follows a similar sequence – picking up the insulin pen, priming it, injecting it, etc. So, the system can flag anomalies in any step of the self-administering process.

The team said the network, for example, can recognise if a patient holds down their insulin pen for five seconds instead of the prescribed 10 seconds. The system can then relay that information to the patient or directly to their doctor, so they can fix their technique.

“By breaking it down into these steps, we can not only see how frequently the patient is using their device but also assess their administration technique to see how well they’re doing,” said Zhao.

He added they could adapt their framework to medications beyond inhalers and insulin pens – all it would take is retraining the neural network to recognise the appropriate sequence of movements. Zhao said that “with this type of sensing technology at home, we could detect issues early on, so the person can see a doctor before it exacerbates the problem”.