Detection of Chronic Musculoskeletal Pain Using Voice Characteristics
Physical pain, particularly musculoskeletal pain, negatively impacts the activities of daily life and quality of life of elderly people. Because pain is a subjective sensation and there are no standard assessment procedures to detect pain, we attempted to quantitatively determine the actual state of...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Journal of Translational Engineering in Health and Medicine |
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| Online Access: | https://ieeexplore.ieee.org/document/10937750/ |
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| author | Masakazu Higuchi Toshiko Iidaka Chiaki Horii Gaku Tanegashima Hiroyuki Oka Hiroshi Hashizume Hiroshi Yamada Munehito Yoshida Sakae Tanaka Noriko Yoshimura Mitsuteru Nakamura Shinichi Tokuno |
| author_facet | Masakazu Higuchi Toshiko Iidaka Chiaki Horii Gaku Tanegashima Hiroyuki Oka Hiroshi Hashizume Hiroshi Yamada Munehito Yoshida Sakae Tanaka Noriko Yoshimura Mitsuteru Nakamura Shinichi Tokuno |
| author_sort | Masakazu Higuchi |
| collection | DOAJ |
| description | Physical pain, particularly musculoskeletal pain, negatively impacts the activities of daily life and quality of life of elderly people. Because pain is a subjective sensation and there are no standard assessment procedures to detect pain, we attempted to quantitatively determine the actual state of chronic pain caused by musculoskeletal organs and related factors based on questionnaires. First, we studied techniques for diagnosing diseases by monitoring the involuntary characteristics of the voice. Then, we applied the technique based on voice characteristics and proposed a voice index to detect chronic musculoskeletal pain. The voice index was derived based on the assumption that physiological changes due to chronic musculoskeletal pain also affect the vocal cords. Subjects in this study were adults, 65 years of age or older, with chronic pain in the musculoskeletal system (lumbar and/or knees). A large-scale population-based cohort study was conducted in 2019. Voice characteristics were extracted from the recorded voices of the subjects, and the characteristics with similar properties were organized into several principal components using principal component analysis. The principal components were further combined using logistic regression analysis to propose a voice index that discriminates between normal subjects and subjects suffering from chronic musculoskeletal pain. A discrimination accuracy of approximately 80% was obtained using the dataset corresponding to the participants with knee pain only, and a discrimination accuracy of approximately 70% was obtained during cross-validation of the same dataset. The proposed voice index may serve as a novel tool for detecting chronic musculoskeletal pain. Clinical impact: The voice-based pain detection holds clinical significance owing to its noninvasive nature, ease of administration, and potential to efficiently assess large populations within a short time frame. |
| format | Article |
| id | doaj-art-8fdc2c349a48427abfcd128fe292c88d |
| institution | OA Journals |
| issn | 2168-2372 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Translational Engineering in Health and Medicine |
| spelling | doaj-art-8fdc2c349a48427abfcd128fe292c88d2025-08-20T02:08:57ZengIEEEIEEE Journal of Translational Engineering in Health and Medicine2168-23722025-01-011313614810.1109/JTEHM.2025.355389210937750Detection of Chronic Musculoskeletal Pain Using Voice CharacteristicsMasakazu Higuchi0https://orcid.org/0000-0003-0329-1141Toshiko Iidaka1https://orcid.org/0009-0007-4662-4248Chiaki Horii2Gaku Tanegashima3Hiroyuki Oka4https://orcid.org/0000-0001-5674-4875Hiroshi Hashizume5https://orcid.org/0000-0002-9064-0284Hiroshi Yamada6https://orcid.org/0000-0002-7694-883XMunehito Yoshida7Sakae Tanaka8https://orcid.org/0000-0001-9210-9414Noriko Yoshimura9https://orcid.org/0000-0001-9206-4658Mitsuteru Nakamura10https://orcid.org/0000-0002-5851-5424Shinichi Tokuno11https://orcid.org/0000-0002-2691-6979Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, JapanDepartment of Preventive Medicine for Locomotive Organ Disorders, 22nd Century Medical and Research Center, The University of Tokyo, Tokyo, JapanDepartment of Orthopaedic Surgery, Sensory and Motor System Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Orthopaedic Surgery, Sensory and Motor System Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Medical Research and Management for Musculoskeletal Pain, 22nd Century Medical and Research Center, The University of Tokyo, Tokyo, JapanDepartment of Orthopedic Surgery, Wakayama Medical University School of Medicine, Wakayama, JapanDepartment of Orthopedic Surgery, Wakayama Medical University School of Medicine, Wakayama, JapanDepartment of Orthopedic Surgery, Wakayama Medical University School of Medicine, Wakayama, JapanDepartment of Orthopaedic Surgery, Sensory and Motor System Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, JapanDepartment of Preventive Medicine for Locomotive Organ Disorders, 22nd Century Medical and Research Center, The University of Tokyo, Tokyo, JapanGraduate School of Health Innovation, Kanagawa University of Human Services, Kawasaki, JapanDepartment of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, JapanPhysical pain, particularly musculoskeletal pain, negatively impacts the activities of daily life and quality of life of elderly people. Because pain is a subjective sensation and there are no standard assessment procedures to detect pain, we attempted to quantitatively determine the actual state of chronic pain caused by musculoskeletal organs and related factors based on questionnaires. First, we studied techniques for diagnosing diseases by monitoring the involuntary characteristics of the voice. Then, we applied the technique based on voice characteristics and proposed a voice index to detect chronic musculoskeletal pain. The voice index was derived based on the assumption that physiological changes due to chronic musculoskeletal pain also affect the vocal cords. Subjects in this study were adults, 65 years of age or older, with chronic pain in the musculoskeletal system (lumbar and/or knees). A large-scale population-based cohort study was conducted in 2019. Voice characteristics were extracted from the recorded voices of the subjects, and the characteristics with similar properties were organized into several principal components using principal component analysis. The principal components were further combined using logistic regression analysis to propose a voice index that discriminates between normal subjects and subjects suffering from chronic musculoskeletal pain. A discrimination accuracy of approximately 80% was obtained using the dataset corresponding to the participants with knee pain only, and a discrimination accuracy of approximately 70% was obtained during cross-validation of the same dataset. The proposed voice index may serve as a novel tool for detecting chronic musculoskeletal pain. Clinical impact: The voice-based pain detection holds clinical significance owing to its noninvasive nature, ease of administration, and potential to efficiently assess large populations within a short time frame.https://ieeexplore.ieee.org/document/10937750/Chronic musculoskeletal painlogistic regression analysisvoice characteristics |
| spellingShingle | Masakazu Higuchi Toshiko Iidaka Chiaki Horii Gaku Tanegashima Hiroyuki Oka Hiroshi Hashizume Hiroshi Yamada Munehito Yoshida Sakae Tanaka Noriko Yoshimura Mitsuteru Nakamura Shinichi Tokuno Detection of Chronic Musculoskeletal Pain Using Voice Characteristics IEEE Journal of Translational Engineering in Health and Medicine Chronic musculoskeletal pain logistic regression analysis voice characteristics |
| title | Detection of Chronic Musculoskeletal Pain Using Voice Characteristics |
| title_full | Detection of Chronic Musculoskeletal Pain Using Voice Characteristics |
| title_fullStr | Detection of Chronic Musculoskeletal Pain Using Voice Characteristics |
| title_full_unstemmed | Detection of Chronic Musculoskeletal Pain Using Voice Characteristics |
| title_short | Detection of Chronic Musculoskeletal Pain Using Voice Characteristics |
| title_sort | detection of chronic musculoskeletal pain using voice characteristics |
| topic | Chronic musculoskeletal pain logistic regression analysis voice characteristics |
| url | https://ieeexplore.ieee.org/document/10937750/ |
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