
The new technology pairs wireless sensing with artificial intelligence to determine when a patient is using an insulin pen or inhaler, and it flags potential errors in the patient’s administration method.
Image: Courtesy of the researchers
Wireless sensing technology could help improve patients’ technique with inhalers and insulin pens
From swallowing pills to injecting insulin, patients frequently administer their own medication. But 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. MIT researchers have developed a system to reduce those numbers for some types of medications.
The new technology pairs wireless sensing with artificial intelligence 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% of patients do not take their insulin as prescribed, and many patients do not use inhalers properly,” says Dina Katabi, the Andrew and Erna Viteri Professor at MIT, whose research group has developed the new solution. The researchers say the system, which can be installed in a home, could alert patients and caregivers to medication errors and potentially reduce unnecessary hospital visits.
The research appears today in the journal Nature Medicine. The study’s lead authors are Mingmin Zhao, a PhD student in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), and Kreshnik Hoti, a former visiting scientist at MIT and current faculty member at the University of Prishtina in Kosovo. Other co-authors include Hao Wang, a former CSAIL postdoc and current faculty member at Rutgers University, and Aniruddh Raghu, a CSAIL PhD student.
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,” says Zhao. “All those little steps are necessary to properly deliver the drug to its active site.” Each step also presents opportunity for errors, especially when there’s no pharmacist present to offer corrective tips. Patients might not even realize when they make a mistake — so Zhao’s team designed an automated system that can.
Their system can be broken down into three broad steps. First, a sensor tracks a patient’s movements within a 10-meter radius, using radio waves that reflect off their body. Next, artificial intelligence scours the reflected signals for signs of a patient self-administering an inhaler or insulin pen. Finally, the system alerts the patient or their health care provider when it detects an error in the patient’s self-administration.
The researchers adapted their sensing method from a wireless technology they’d previously used to monitor people’s sleeping positions. It starts with a wall-mounted device that emits very low-power radio waves. When someone moves, they modulate the signal and reflect it back to the device’s sensor. Each unique movement yields a corresponding pattern of modulated radio waves that the device can decode. “One nice thing about this system is that it doesn’t require the patient to wear any sensors,” says Zhao. “It can even work through occlusions, similar to how you can access your Wi-Fi when you’re in a different room from your router.”
The new sensor sits in the background at home, like a Wi-Fi router, and uses artificial intelligence 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. They trained the network to learn those patterns by performing example movements, some relevant (e.g. using an inhaler) and some not (e.g. eating). Through repetition and reinforcement, the network successfully detected 96 percent of insulin pen administrations and 99 percent of inhaler uses.
Once it mastered the art of detection, the network also proved useful for correction. Every proper medicine administration follows a similar sequence — picking up the insulin pen, priming it, injecting, etc. So, the system can flag anomalies in any particular step. For example, the network can recognize 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,” says Zhao.
The researchers say a key feature of their radio wave-based system is its noninvasiveness. “An alternative way to solve this problem is by installing cameras,” says Zhao. “But using a wireless signal is much less intrusive. It doesn’t show peoples’ appearance.”
He adds that their framework could be adapted to medications beyond inhalers and insulin pens — all it would take is retraining the neural network to recognize the appropriate sequence of movements. Zhao says that “with this type of sensing technology at home, we could detect issues early on, so the person can see a doctor before the problem is exacerbated.”
Original Article: System detects errors when medication is self-administered
More from: MIT Computer Science and Artificial Intelligence Laboratory | Massachusetts Institute of Technology
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
Wireless sensing technology
- Logitech G309 Lightspeed Wireless Gaming Mouse Launched in India: Check Price, Features
The Logitech G309 Lightspeed gaming mouse, priced at ₹8,995, offers dual connectivity, a Hero 25K sensor, and extended battery life.
- Wytec Introduces its "Distributed AI" Gunshot/THC Technology for Schools & Public Safety
William Gray, CEO/President of Wytec International, Inc., (OTCQB:WYTC), a leading developer of threat sensing systems announces today, its latest achievements for its patented, advanced threat and ...
- Scientists develop battery-free technology to power devices using ambient radio waves
A team of scientists from the (NUS) has developed an innovative energy-harvesting module that can convert ambient radiofrequency (RF) signals, such as those from Wi-Fi, Bluetooth, and 5G, into direct ...
- ATIS’ Next G Alliance releases 6G report focused on comms and sensing
NGA aims to advance North American tech leadership over the next decade through private sector-led efforts with an initial focus on 6G ...
- New battery-free technology to power electronic devices using ambient radiofrequency signals
Researchers demonstrated a novel technique to efficiently convert ambient low-power radiofrequency signals into DC power. This 'rectifier' technology can be easily integrated into energy harvesting ...
Go deeper with Google Headlines on:
Wireless sensing technology
[google_news title=”” keyword=”wireless sensing technology” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]
Go deeper with Bing News on:
Wireless sensing technology and artificial intelligence
- Artificial Intelligence and Machine Learning – News and Features
How do they do this, with their limited brain power? Researchers have developed a sensor made from "frozen smoke" that uses artificial intelligence techniques to detect formaldehyde in real-time at ...
- Artificial intelligence
The Cyberspace Administration of China’s action shows its resolve to enforce domestic rules on generative artificial intelligence ... pack with AI AI and wireless technology are taking seamless ...
- Telco AI for network automation and 5G monetization
Telco AI in network management allows CSPs to automate routine tasks like network monitoring, fault detection and performance optimization.
- Artificial Intelligence
The four-wheel robot made by Vayu Robotics eschews expensive LiDAR technology typically used ... Prior to WWDC24, AI meant artificial intelligence to most consumers. In classic Apple-esque fashion ...
- The Remote Sensing Technology Institute (IMF)
The Remote Sensing Technology Institute (IMF ... Imaging with optical sensors Atmospheric spectrometry Data Science and Artificial Intelligence. MF manages the air-based optical sensor suite of the ...
Go deeper with Google Headlines on:
Wireless sensing technology and artificial intelligence
[google_news title=”” keyword=”wireless sensing technology and artificial intelligence” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]