Using Muscle Synergy to Evaluate the Neck Muscular Activities during Normal Swallowing
Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely...
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| Published in: | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Vol. 2018; pp. 2454 - 2457 |
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| Main Authors: | , , , , , , , , , , , |
| Format: | Conference Proceeding Journal Article |
| Language: | English |
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IEEE
01.07.2018
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| ISSN: | 1557-170X, 2694-0604, 1558-4615, 2694-0604 |
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| Abstract | Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely investigated. In this study, we studied the muscle synergy associated with swallowing saliva based on high-density (HD) surface electromyography (sEMG) signals acquired from four healthy subjects. The non-negative matrix factorization algorithm was applied to reconstruct the muscle activation patterns, and the values of variance accounted for (VAF) coefficients were computed to determine the number of muscle synergies. The results showed that the VAF values raised with the increase in the number of synergies on both the left and right sides of the neck. And the variation tendency of the VAF values was almost similar between the left and right area with a significant correlation (r=0.9902±0.0046, p<;0.05). Furthermore, it was observed that an average of 5 muscle synergies was the minimum number required to sufficiently reconstruct the spatial characteristics of the synergism between both sides of the neck. These results suggest that the muscle synergy approach could serve as a promising candidate to evaluate the muscular co-contractions during swallowing, and it might be a useful method for dysphagia monitoring and diagnoses. |
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| AbstractList | Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely investigated. In this study, we studied the muscle synergy associated with swallowing saliva based on high-density (HD) surface electromyography (sEMG) signals acquired from four healthy subjects. The non-negative matrix factorization algorithm was applied to reconstruct the muscle activation patterns, and the values of variance accounted for (VAF) coefficients were computed to determine the number of muscle synergies. The results showed that the VAF values raised with the increase in the number of synergies on both the left and right sides of the neck. And the variation tendency of the VAF values was almost similar between the left and right area with a significant correlation ($\text{r}=0.9902 \pm 0.0046$, $\mathrm {p}<0.05)$. Furthermore, it was observed that an average of 5 muscle synergies was the minimum number required to sufficiently reconstruct the spatial characteristics of the synergism between both sides of the neck. These results suggest that the muscle synergy approach could serve as a promising candidate to evaluate the muscular co-contractions during swallowing, and it might be a useful method for dysphagia monitoring and diagnoses.Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely investigated. In this study, we studied the muscle synergy associated with swallowing saliva based on high-density (HD) surface electromyography (sEMG) signals acquired from four healthy subjects. The non-negative matrix factorization algorithm was applied to reconstruct the muscle activation patterns, and the values of variance accounted for (VAF) coefficients were computed to determine the number of muscle synergies. The results showed that the VAF values raised with the increase in the number of synergies on both the left and right sides of the neck. And the variation tendency of the VAF values was almost similar between the left and right area with a significant correlation ($\text{r}=0.9902 \pm 0.0046$, $\mathrm {p}<0.05)$. Furthermore, it was observed that an average of 5 muscle synergies was the minimum number required to sufficiently reconstruct the spatial characteristics of the synergism between both sides of the neck. These results suggest that the muscle synergy approach could serve as a promising candidate to evaluate the muscular co-contractions during swallowing, and it might be a useful method for dysphagia monitoring and diagnoses. Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely investigated. In this study, we studied the muscle synergy associated with swallowing saliva based on high-density (HD) surface electromyography (sEMG) signals acquired from four healthy subjects. The non-negative matrix factorization algorithm was applied to reconstruct the muscle activation patterns, and the values of variance accounted for (VAF) coefficients were computed to determine the number of muscle synergies. The results showed that the VAF values raised with the increase in the number of synergies on both the left and right sides of the neck. And the variation tendency of the VAF values was almost similar between the left and right area with a significant correlation (r=0.9902±0.0046, p<;0.05). Furthermore, it was observed that an average of 5 muscle synergies was the minimum number required to sufficiently reconstruct the spatial characteristics of the synergism between both sides of the neck. These results suggest that the muscle synergy approach could serve as a promising candidate to evaluate the muscular co-contractions during swallowing, and it might be a useful method for dysphagia monitoring and diagnoses. Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely investigated. In this study, we studied the muscle synergy associated with swallowing saliva based on high-density (HD) surface electromyography (sEMG) signals acquired from four healthy subjects. The non-negative matrix factorization algorithm was applied to reconstruct the muscle activation patterns, and the values of variance accounted for (VAF) coefficients were computed to determine the number of muscle synergies. The results showed that the VAF values raised with the increase in the number of synergies on both the left and right sides of the neck. And the variation tendency of the VAF values was almost similar between the left and right area with a significant correlation ($\text{r}=0.9902 \pm 0.0046$, $\mathrm {p}<0.05)$. Furthermore, it was observed that an average of 5 muscle synergies was the minimum number required to sufficiently reconstruct the spatial characteristics of the synergism between both sides of the neck. These results suggest that the muscle synergy approach could serve as a promising candidate to evaluate the muscular co-contractions during swallowing, and it might be a useful method for dysphagia monitoring and diagnoses. |
| Author | Zijian Yang Tong, Michael Chifai Samuel, Oluwarotimi Williams Shixiong Chen Peng Li Leung, Karman Kaying Peng Fang Mingxing Zhu Wanhua Lin Jingqian Tan Guanglin Li Zhen Huang |
| Author_xml | – sequence: 1 surname: Mingxing Zhu fullname: Mingxing Zhu organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China – sequence: 2 givenname: Oluwarotimi Williams surname: Samuel fullname: Samuel, Oluwarotimi Williams organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China – sequence: 3 surname: Zijian Yang fullname: Zijian Yang organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China – sequence: 4 surname: Wanhua Lin fullname: Wanhua Lin organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China – sequence: 5 surname: Zhen Huang fullname: Zhen Huang organization: Dept. of Rehabilitation Med., Guangzhou Panyu Central Hosp., Guangzhou, China – sequence: 6 surname: Peng Fang fullname: Peng Fang organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China – sequence: 7 surname: Jingqian Tan fullname: Jingqian Tan organization: Third Affiliated Hosp. of Sun Yat-Sen Univ., Guangzhou, China – sequence: 8 surname: Peng Li fullname: Peng Li organization: Third Affiliated Hosp. of Sun Yat-Sen Univ., Guangzhou, China – sequence: 9 givenname: Michael Chifai surname: Tong fullname: Tong, Michael Chifai organization: Dept. of Otorhinolaryngology, Head & Neck Surg., Chinese Univ. of Hong Kong, Hong Kong, China – sequence: 10 givenname: Karman Kaying surname: Leung fullname: Leung, Karman Kaying organization: Dept. of Otorhinolaryngology, Head & Neck Surg., Chinese Univ. of Hong Kong, Hong Kong, China – sequence: 11 surname: Shixiong Chen fullname: Shixiong Chen email: sx.chen@siat.ac.cn organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China – sequence: 12 surname: Guanglin Li fullname: Guanglin Li organization: Lab. of Human-Machine Intell.-Synergy Syst., Shenzhen Inst. of Adv. Technol., Shenzhen, China |
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| SubjectTerms | Correlation Correlation coefficient Electrodes Electromyography Legged locomotion Muscles Neck |
| Title | Using Muscle Synergy to Evaluate the Neck Muscular Activities during Normal Swallowing |
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