University of Massachusetts Medical School Faculty Publications

Title

Wearable Biosensors to Detect Physiologic Change During Opioid Use

UMMS Affiliation

Department of Emergency Medicine, Division of Medical Toxicology; Department of Neurology; Department of Quantitative Health Sciences

Date

9-1-2016

Document Type

Article

Disciplines

Emergency Medicine | Medical Toxicology

Abstract

INTRODUCTION: Opioid analgesic use is a major cause of morbidity and mortality in the US, yet effective treatment programs have a limited ability to detect relapse. The utility of current drug detection methods is often restricted due to their retrospective and subjective nature. Wearable biosensors have the potential to improve detection of relapse by providing objective, real time physiologic data on opioid use that can be used by treating clinicians to augment behavioral interventions.

METHODS: Thirty emergency department (ED) patients who were prescribed intravenous opioid medication for acute pain were recruited to wear a wristband biosensor. The biosensor measured electrodermal activity, skin temperature and locomotion data, which was recorded before and after intravenous opioid administration. Hilbert transform analyses combined with paired t-tests were used to compare the biosensor data A) within subjects, before and after administration of opioids; B) between subjects, based on hand dominance, gender, and opioid use history.

RESULTS: Within subjects, a significant decrease in locomotion and increase in skin temperature were consistently detected by the biosensors after opioid administration. A significant change in electrodermal activity was not consistently detected. Between subjects, biometric changes varied with level of opioid use history (heavy vs. nonheavy users), but did not vary with gender or type of opioid. Specifically, heavy users demonstrated a greater decrease in short amplitude movements (i.e. fidgeting movements) compared to non-heavy users.

CONCLUSION: A wearable biosensor showed a consistent physiologic pattern after ED opioid administration and differences between patterns of heavy and non-heavy opioid users were noted. Potential applications of biosensors to drug addiction treatment and pain management should be studied further.

Rights and Permissions

Citation: J Med Toxicol. 2016 Sep;12(3):255-62. doi: 10.1007/s13181-016-0557-5. Epub 2016 Jun 22. Link to article on publisher's site

Related Resources

Link to Article in PubMed

Keywords

Biometrics, Biosensors, Opioids, Signal Processing, Wearables

PubMed ID

27334894