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Voice-Derived Acoustic Features and Pain Intensity in Chronic Low Back Pain
Sponsor: nurmuhammet tas
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
Conditions
Interventions
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)