This study explored whether changes in a person's voice could help identify opioid use in patients with opioid use disorder (OUD). Current methods for determining whether a patient is intoxicated or in withdrawal often rely on self-reporting and clinical judgment, which can be subjective and inconsistent. Drug tests are logistically challenging to administer and can be costly with repeated use.
The project investigated whether physiological changes associated with opioid use could be detected through speech analysis technology. Researchers evaluated whether machine learning methods could identify voice patterns associated with opioid intoxication or withdrawal.
The primary goal of the study was to assess the accuracy of voice-based biomarkers in identifying opioid use. The study also explored relationships between opioid use and specific speech characteristics.