Oral motion classification of the elderly for prevention and rehabilitation of dysphagia
Several people, particularly the elderly population, have difficulties in swallowing; therefore, to address this issue, we built an oral motion classification system based on the muscle activity pattern of the suprahyoid muscles and tested it on 12 elderly people (seven males and five females) witho...
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The Japan Society of Mechanical Engineers
2020
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oai:doaj.org-article:8c5494d0197d47ffb615c38d914242b32021-11-29T05:52:02ZOral motion classification of the elderly for prevention and rehabilitation of dysphagia2187-974510.1299/mej.19-00076https://doaj.org/article/8c5494d0197d47ffb615c38d914242b32020-01-01T00:00:00Zhttps://www.jstage.jst.go.jp/article/mej/7/1/7_19-00076/_pdf/-char/enhttps://doaj.org/toc/2187-9745Several people, particularly the elderly population, have difficulties in swallowing; therefore, to address this issue, we built an oral motion classification system based on the muscle activity pattern of the suprahyoid muscles and tested it on 12 elderly people (seven males and five females) without a history of dysphagia and five healthy young men. Surface electromyography (sEMG) signals of the suprahyoid muscles were measured using a 22-channel electrode that was designed as a thin flexible boomerang-shaped patch attached to the underside of the jaw. Six oral motions involving various tongue, jaw opening, and swallowing exercises were classified from the root mean square (RMS) features and cepstrum coefficients (CC) features of sEMG signals using a support vector machine (SVM) classifier. Results showed that the six oral motions for elderly patients were classified with an accuracy of 95.2% and 95.4% for young patients. There was no statistically significant difference in the mean classification accuracy between the two groups. We also found that the six oral motions can be classified with an accuracy of 95.2% regardless of sex, subcutaneous fat thickness on the underside of the jaw, or the level of oral function. Therefore, it appears that the system proposed here can be an effective tool for accurately measuring oral motions and it can be employed to develop an effective game-based training protocol for the elderly whose swallowing capabilities require maintenance and improvement.Makoto SASAKIShumpei ITOKatsuhiro KAMATAMasahiro YOSHIKAWAIsamu SHIBAMOTOAtsushi NAKAYAMAThe Japan Society of Mechanical Engineersarticleelectromyographyoral movementmotion classificationdysphagia rehabilitationMechanical engineering and machineryTJ1-1570ENMechanical Engineering Journal, Vol 7, Iss 1, Pp 19-00076-19-00076 (2020) |
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DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
electromyography oral movement motion classification dysphagia rehabilitation Mechanical engineering and machinery TJ1-1570 |
| spellingShingle |
electromyography oral movement motion classification dysphagia rehabilitation Mechanical engineering and machinery TJ1-1570 Makoto SASAKI Shumpei ITO Katsuhiro KAMATA Masahiro YOSHIKAWA Isamu SHIBAMOTO Atsushi NAKAYAMA Oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| description |
Several people, particularly the elderly population, have difficulties in swallowing; therefore, to address this issue, we built an oral motion classification system based on the muscle activity pattern of the suprahyoid muscles and tested it on 12 elderly people (seven males and five females) without a history of dysphagia and five healthy young men. Surface electromyography (sEMG) signals of the suprahyoid muscles were measured using a 22-channel electrode that was designed as a thin flexible boomerang-shaped patch attached to the underside of the jaw. Six oral motions involving various tongue, jaw opening, and swallowing exercises were classified from the root mean square (RMS) features and cepstrum coefficients (CC) features of sEMG signals using a support vector machine (SVM) classifier. Results showed that the six oral motions for elderly patients were classified with an accuracy of 95.2% and 95.4% for young patients. There was no statistically significant difference in the mean classification accuracy between the two groups. We also found that the six oral motions can be classified with an accuracy of 95.2% regardless of sex, subcutaneous fat thickness on the underside of the jaw, or the level of oral function. Therefore, it appears that the system proposed here can be an effective tool for accurately measuring oral motions and it can be employed to develop an effective game-based training protocol for the elderly whose swallowing capabilities require maintenance and improvement. |
| format |
article |
| author |
Makoto SASAKI Shumpei ITO Katsuhiro KAMATA Masahiro YOSHIKAWA Isamu SHIBAMOTO Atsushi NAKAYAMA |
| author_facet |
Makoto SASAKI Shumpei ITO Katsuhiro KAMATA Masahiro YOSHIKAWA Isamu SHIBAMOTO Atsushi NAKAYAMA |
| author_sort |
Makoto SASAKI |
| title |
Oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| title_short |
Oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| title_full |
Oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| title_fullStr |
Oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| title_full_unstemmed |
Oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| title_sort |
oral motion classification of the elderly for prevention and rehabilitation of dysphagia |
| publisher |
The Japan Society of Mechanical Engineers |
| publishDate |
2020 |
| url |
https://doaj.org/article/8c5494d0197d47ffb615c38d914242b3 |
| work_keys_str_mv |
AT makotosasaki oralmotionclassificationoftheelderlyforpreventionandrehabilitationofdysphagia AT shumpeiito oralmotionclassificationoftheelderlyforpreventionandrehabilitationofdysphagia AT katsuhirokamata oralmotionclassificationoftheelderlyforpreventionandrehabilitationofdysphagia AT masahiroyoshikawa oralmotionclassificationoftheelderlyforpreventionandrehabilitationofdysphagia AT isamushibamoto oralmotionclassificationoftheelderlyforpreventionandrehabilitationofdysphagia AT atsushinakayama oralmotionclassificationoftheelderlyforpreventionandrehabilitationofdysphagia |
| _version_ |
1718407598956347392 |