Xinxin Li, Yihao Du, Chunhua Yang, Wenjing Qi, P. Xie
{"title":"协同肌的合并和肌间一致性预测肌肉协调的复杂性","authors":"Xinxin Li, Yihao Du, Chunhua Yang, Wenjing Qi, P. Xie","doi":"10.1109/ICINFA.2016.7831927","DOIUrl":null,"url":null,"abstract":"Studies have shown that the nervous system through the modular structure simplifies control the movement, however, whether such a modular structure complexity associated with muscle coupling has not been proven well. The purpose of this study was to examine the effect of synergistic muscles and intermuscular coherence predicts muscle coordination complexity. Electormyographic (EMG) activity was recorded from eight upper limb muscles of eight healthy subjects. They performed two different activities with the dominant arm, especially were not known what is the next action, they focus on indicative images. We first determine the number of motion modules was 5 through nonnegative matrix factorization with the account for variability of muscle activation. Next, we calculate the coupling relationship between muscles through approach of coherence, which are the pairs of EMG signals, both synergistic and non-synergistic muscles. We found a strong coupling muscles exist in synergistic muscles; most were observed both beta band and gamma band. Identification coupling muscles of the synergistic may lead to new insight into explored the neural control mechanism.","PeriodicalId":389619,"journal":{"name":"2016 IEEE International Conference on Information and Automation (ICIA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Merging of synergistic muscles and intermuscular coherence predict muscle coordination complexity\",\"authors\":\"Xinxin Li, Yihao Du, Chunhua Yang, Wenjing Qi, P. Xie\",\"doi\":\"10.1109/ICINFA.2016.7831927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Studies have shown that the nervous system through the modular structure simplifies control the movement, however, whether such a modular structure complexity associated with muscle coupling has not been proven well. The purpose of this study was to examine the effect of synergistic muscles and intermuscular coherence predicts muscle coordination complexity. Electormyographic (EMG) activity was recorded from eight upper limb muscles of eight healthy subjects. They performed two different activities with the dominant arm, especially were not known what is the next action, they focus on indicative images. We first determine the number of motion modules was 5 through nonnegative matrix factorization with the account for variability of muscle activation. Next, we calculate the coupling relationship between muscles through approach of coherence, which are the pairs of EMG signals, both synergistic and non-synergistic muscles. We found a strong coupling muscles exist in synergistic muscles; most were observed both beta band and gamma band. Identification coupling muscles of the synergistic may lead to new insight into explored the neural control mechanism.\",\"PeriodicalId\":389619,\"journal\":{\"name\":\"2016 IEEE International Conference on Information and Automation (ICIA)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Information and Automation (ICIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINFA.2016.7831927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Information and Automation (ICIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2016.7831927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Merging of synergistic muscles and intermuscular coherence predict muscle coordination complexity
Studies have shown that the nervous system through the modular structure simplifies control the movement, however, whether such a modular structure complexity associated with muscle coupling has not been proven well. The purpose of this study was to examine the effect of synergistic muscles and intermuscular coherence predicts muscle coordination complexity. Electormyographic (EMG) activity was recorded from eight upper limb muscles of eight healthy subjects. They performed two different activities with the dominant arm, especially were not known what is the next action, they focus on indicative images. We first determine the number of motion modules was 5 through nonnegative matrix factorization with the account for variability of muscle activation. Next, we calculate the coupling relationship between muscles through approach of coherence, which are the pairs of EMG signals, both synergistic and non-synergistic muscles. We found a strong coupling muscles exist in synergistic muscles; most were observed both beta band and gamma band. Identification coupling muscles of the synergistic may lead to new insight into explored the neural control mechanism.