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Voice Technology to Identify Opioid Use

NCT07603778 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 41

Last updated 2026-05-22

No results posted yet for this study

Summary

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.

Conditions

  • Opioid Use

Interventions

OTHER

Not applicable- observational study

Not Applicable - Observational Study

Sponsors & Collaborators

  • Volpicelli Center

    collaborator UNKNOWN

  • National Institute on Drug Abuse (NIDA)

    collaborator NIH

  • Tenvos Inc.

    lead INDUSTRY

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-12-10
Primary Completion
2025-06-30
Completion
2026-01-30

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07603778 on ClinicalTrials.gov