基于小波检测的人体运动活动肌肉协同分解分析

Anton Popov, S. Yakovenko
{"title":"基于小波检测的人体运动活动肌肉协同分解分析","authors":"Anton Popov, S. Yakovenko","doi":"10.1109/SPS.2015.7168260","DOIUrl":null,"url":null,"abstract":"Any movement is generated by synergistic actions of muscle groups. The analytical description of how muscles are combined into synergies to produce their coordination actions remains to be established. Here, we have introduced the wavelet-based analysis to identify common information among major leg muscles during a locomotor tasks with and without asymmetric adaptation.","PeriodicalId":193902,"journal":{"name":"2015 Signal Processing Symposium (SPSympo)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Muscle synergy decomposition analysis using wavelet detection in human locomotor activity\",\"authors\":\"Anton Popov, S. Yakovenko\",\"doi\":\"10.1109/SPS.2015.7168260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Any movement is generated by synergistic actions of muscle groups. The analytical description of how muscles are combined into synergies to produce their coordination actions remains to be established. Here, we have introduced the wavelet-based analysis to identify common information among major leg muscles during a locomotor tasks with and without asymmetric adaptation.\",\"PeriodicalId\":193902,\"journal\":{\"name\":\"2015 Signal Processing Symposium (SPSympo)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Signal Processing Symposium (SPSympo)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPS.2015.7168260\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing Symposium (SPSympo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPS.2015.7168260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

任何运动都是由肌肉群的协同作用产生的。关于肌肉如何结合成协同作用以产生协调动作的分析描述仍有待建立。在这里,我们引入了基于小波的分析来识别在有和没有不对称适应的运动任务中主要腿部肌肉之间的共同信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Muscle synergy decomposition analysis using wavelet detection in human locomotor activity
Any movement is generated by synergistic actions of muscle groups. The analytical description of how muscles are combined into synergies to produce their coordination actions remains to be established. Here, we have introduced the wavelet-based analysis to identify common information among major leg muscles during a locomotor tasks with and without asymmetric adaptation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A scalable computing platform for digital pulse compression and digital beamforming Doppler Radar tomography of rotated object in noisy environment based on time-frequency transformation Direct signal suppression schemes for passive radar Voltage tunable bandpass filter IEEE 802.15.4 compliant in-building wireless sensor network
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1