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Related Experiment Video

Updated: Sep 15, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

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Published on: July 22, 2025

Detection of Chronic Musculoskeletal Pain Using Voice Characteristics.

Masakazu Higuchi¹, Toshiko Iidaka², Chiaki Horii³

¹Department of BioengineeringGraduate School of EngineeringThe University of Tokyo Tokyo 113-8656 Japan.

IEEE Journal of Translational Engineering in Health and Medicine

|July 14, 2025

Summary

Researchers developed a voice index to detect chronic musculoskeletal pain in older adults. This noninvasive method analyzes voice characteristics, offering a new tool for pain assessment and improving quality of life.

Keywords:

Chronic musculoskeletal pain logistic regression analysis voice characteristics

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Area of Science:

Gerontology
Biomedical Engineering
Pain Medicine

Background:

Musculoskeletal pain significantly diminishes daily activities and quality of life in the elderly.
Current pain assessment is subjective and lacks standardized objective procedures.
Physiological changes associated with chronic pain may influence vocal cord function.

Purpose of the Study:

To quantitatively assess chronic musculoskeletal pain in older adults.
To develop and validate a voice-based index for detecting chronic musculoskeletal pain.
To explore the relationship between voice characteristics and musculoskeletal pain.

Main Methods:

A large-scale, population-based cohort study involving adults aged 65+ with chronic lumbar or knee pain.
Extraction and analysis of voice characteristics using principal component analysis.
Logistic regression analysis to develop a voice index for pain discrimination.

Main Results:

A novel voice index was proposed to differentiate between individuals with and without chronic musculoskeletal pain.
Discrimination accuracy of approximately 80% was achieved for knee pain detection.
Cross-validation yielded a discrimination accuracy of approximately 70% for knee pain.

Conclusions:

The proposed voice index demonstrates potential as a novel, noninvasive tool for detecting chronic musculoskeletal pain.
Voice-based pain detection offers clinical significance through its ease of use and scalability.
This method could facilitate efficient, large-scale screening of pain in older populations.