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NCT07078019

Voice-Derived Acoustic Features and Pain Intensity in Chronic Low Back Pain

Sponsor: nurmuhammet tas

View on ClinicalTrials.gov

Summary

This observational study investigated whether characteristics of a person's voice are associated with pain intensity in adults with chronic low back pain and whether voice recordings can help predict individual pain levels. The study included 110 adults aged 18-70 years with chronic low back pain. Participants were selected to represent the full range of pain intensity scores from 0 to 10, with 10 participants at each level. Each participant reported their current pain intensity using the Numerical Rating Scale (NRS) and completed the Oswestry Disability Index (ODI) questionnaire to assess limitations in daily activities. Participants also read a standardized text aloud while their voice was recorded using a smartphone. The recordings were analyzed to measure acoustic characteristics, including voice pitch, pitch variability, jitter, shimmer, voice quality, speaking duration, and pauses. Researchers examined whether these characteristics were associated with pain intensity and functional disability. Statistical prediction models were also evaluated to determine whether voice characteristics could estimate individual pain scores. No experimental treatment was administered as part of this study. The study aimed to improve understanding of the potential usefulness and limitations of voice analysis as a non-invasive method for assessing pain in people with chronic low back pain.

Official title: Voice-Derived Acoustic Features and Pain Intensity in Chronic Low Back Pain: An Exploratory Prediction Study

Key Details

Gender

All

Age Range

18 Years - 70 Years

Study Type

OBSERVATIONAL

Enrollment

110

Start Date

2025-07-11

Completion Date

2025-09-30

Last Updated

2026-10-28

Healthy Volunteers

No

Interventions

OTHER

Voice Recording Procedure

Participants underwent standardized voice recording using the built-in recording application of a Samsung Galaxy A71 smartphone. Two reading protocols were used: an emotionally neutral text and a consent-related text. Participants read the assigned text aloud using their habitual speaking voice. Recordings were subsequently analyzed using Praat software to extract acoustic features, including fundamental frequency, intensity, jitter, shimmer, harmonics-to-noise ratio, recording duration, and pause-related measures. The recording procedure was non-invasive and did not involve any therapeutic intervention.

Locations (1)

Erzurum City Hospital

Erzurum, Erzurum, Turkey (Türkiye)