JMIR Publications

ABSTRACT

In this paper we describe the development and validation of an opioid overdose detection radar (ODR) specifically designed for use in public restroom stalls. The ODR system utilized a high frequency pulsed coherent radar sensor and Raspberry Pi, combining advanced technology with a compact and cost-effective setup to monitor respiration and detect opioid overdoses. The development of the radar included several constraints and challenges to be able to detect opioid overdose within this setting: The ODR has to measure respiration rate on a fully clothed, slumped over individual with weak breathing, it must fit within a bathroom stall, it must be accurate, and it must respect privacy and anonymity. To determine the optimal position for the ODR within the confined space of a restroom stall, iterative testing was conducted, considering the radar's bounded capture area and the limitations imposed by the stall's dimensions and layout. By adjusting the orientation of the ODR, researchers were able to identify the most effective placement. To emulate real-world conditions, experiments used a mock bathroom stall setup that adhered to building code regulations. This setup created a controlled environment while maintaining the authenticity of a public restroom stall. By simulating different body positions commonly associated with opioid overdoses, the ODR's ability to accurately track respiration in various scenarios was assessed. To validate the accuracy of the ODR, testing was performed using a respiration belt as a reference. The radar measurements were compared to those obtained from the belt. The results demonstrated favorable agreement between the radar and belt measurements, with a mean error in cycle duration of 0.0072s with a standard deviation of 0.54s. This indicates that the ODR reliably captures respiration patterns associated with normal breathing. During simulated overdose scenarios, the ODR successfully tracked respiration with a mean period difference of 0.0091±0.62s compared to the reference data. This suggests that the ODR has the potential to detect significant deviations in respiration patterns that may indicate an opioid overdose event. Overall, this study shows the promising potential of the ODR in detecting opioid overdoses in public restroom stalls. The development of an accurate and reliable radar-based system, combined with its successful performance in controlled experiments, indicates that the ODR can play a crucial role in enhancing safety and emergency response measures in public restrooms. However, further validation is necessary, particularly on unhealthy opioid-influenced respiratory patterns, to ensure the ODR's effectiveness in real-world overdose situations.