Over 68,000 opioid-overdose related deaths occurred within the United States in 2020 alone, indicating a need to develop technologies to help curb this growing epidemic. The ability to detect respiratory rate (RR) depression in real-time has the potential to decrease adverse outcomes by alerting emergency medical services or willing bystanders to an overdose event. The aim of this investigation was to design, build, and test a novel photoplethysmography (PPG)-based measurement device capable of monitoring RR and identifying respiratory depression.

We developed a novel murine model for opioid-induced respiratory depression (OIRD) to demonstrate the PPG device's capabilities. We induced respiratory depression in mice using both isoflurane and opioid-overdose and initiated recovery events with injections of naloxone while monitoring respiration via PPG and a laboratory reference system.

The device accurately identified all anesthesia-induced respiratory depression (n = 5) and OIRD events (n = 3). Our PPG-based monitor showed significant correlation with a reference respiratory measurement system ( ). The bias measured across the isoflurane trials was 0.6 breaths per minute (BrPM), while the bias measured across the oxycodone trials was −1.0 BrPM, with mean absolute errors of 1.5 and 3.6 BrPM, respectively, indicating that our device was able to accurately measure RR in a murine model.

These preliminary experiments suggest that our device could detect OIRD and could potentially be adaptable to humans with modifications to firmware and more extensive validation in human subjects. Our present study is a proof-of-concept for detecting OIRD and alerting bystanders and health professionals in real-time.