In an effort to tackle the opioid epidemic, researchers from the University of Massachusetts Amherst, Syracuse University and SUNY Upstate Medical University have come together to create a wireless sensor designed to help prevent opioid relapses and overdoses. The National Institute on Drug Abuse has reported that in 2019, approximately 50,000 people in the US passed away due to opioid-linked overdoses. Moreover, federal data suggests that between 21 and 29 percent of those prescribed opioids for chronic pain misuse them.
The research team, led by Tauhidur Rahman, PhD, an assistant professor in the College of Information and Computer Sciences at UMass Amherst and co-director of the MOSAIC Lab, is developing a sensor to combat the issue of opioid cravings. It will use machine learning to detect psychophysiological signs in real time, determining whether or not they are related to opioid cravings. Cravings are one of the main causes of relapses and overdoses, and the sensor will provide users with mindfulness-based interventions to help them cope. The interventions will be tailored to the user’s behaviors and clinician input.
The sensor has already been proven to be successful in identifying opioid use through physiological signals. In a recently published study in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, researchers assessed data from 36 people who had been admitted to the hospital for an acute pain condition and received opioid analgesics. Each study participant was given a wireless wrist sensor, which monitored their heart rate, skin temperature, accelerometry, electrodermal activity, and interbeat interval for 2,070 hours, or 86 days. During this time, the machine-learning sensor was able to detect 339 opioid administrations and predict the exact moment of administration based on physical characteristics and physiological trends. This system could be used to monitor opioid use and prevent opioid use disorders. As Bhanu Teja Gullapalli, lead author of the study and PhD student in Rahman’s lab, said in a news release, “The doctor can ask the patient to wear the smartwatch and the system will track how frequently the patient is using the drug, how the patient’s physiology is changing and determine if the patient is developing a dependence on opioids.”