Jingting Shi, Yanyan Liu, Hongli Yan, Yueming Gao, Ž. L. Vasić, M. Cifrek
{"title":"基于电阻抗肌图的腰背部肌肉状态检测","authors":"Jingting Shi, Yanyan Liu, Hongli Yan, Yueming Gao, Ž. L. Vasić, M. Cifrek","doi":"10.1109/IMBioC52515.2022.9790108","DOIUrl":null,"url":null,"abstract":"In the prevention and rehabilitation stage of low back diseases, it is necessary to detect the state of muscles to avoid excessive fatigue and injury caused by continuous exertion of lumbar muscles. In this paper, an in vivo experimental platform for measuring low back muscle impedance was established in order to detect the different force states of muscle and study the corresponding relationship between muscle force state and muscle impedance. In the experiment, Biering-Sorensen (BS) test was used to make the low back muscle contract continuously, and different weights (5 kg, 2.5 kg, 0 kg) were used to distinguish the force state of muscle. The impedance analyzer was used to measure the muscle impedance parameters under different load in the subject's low back muscle for studying the electrical impedance characteristics of different low back muscle states. The results showed that the relative resistance $R^{\\prime}$ of EIM was a downward trend with time and the 5 kg load had the fastest decline; The relative reactance $X_{c}^{\\prime}$ of EIM was an upward trend with time, the 5 kg load also had the fastest rise. The slope $k$ of the fitting curve of $R^{\\prime}$ and $X_{c}^{\\prime}\\text{were}-5.8\\times 10^{-4}$ and $8.76 \\times 10^{-4}$ respectively. Therefore, EIM can effectively detect the state of low back muscles.","PeriodicalId":305829,"journal":{"name":"2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detection of low back muscle state based on electrical impedance myography\",\"authors\":\"Jingting Shi, Yanyan Liu, Hongli Yan, Yueming Gao, Ž. L. Vasić, M. Cifrek\",\"doi\":\"10.1109/IMBioC52515.2022.9790108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the prevention and rehabilitation stage of low back diseases, it is necessary to detect the state of muscles to avoid excessive fatigue and injury caused by continuous exertion of lumbar muscles. In this paper, an in vivo experimental platform for measuring low back muscle impedance was established in order to detect the different force states of muscle and study the corresponding relationship between muscle force state and muscle impedance. In the experiment, Biering-Sorensen (BS) test was used to make the low back muscle contract continuously, and different weights (5 kg, 2.5 kg, 0 kg) were used to distinguish the force state of muscle. The impedance analyzer was used to measure the muscle impedance parameters under different load in the subject's low back muscle for studying the electrical impedance characteristics of different low back muscle states. The results showed that the relative resistance $R^{\\\\prime}$ of EIM was a downward trend with time and the 5 kg load had the fastest decline; The relative reactance $X_{c}^{\\\\prime}$ of EIM was an upward trend with time, the 5 kg load also had the fastest rise. The slope $k$ of the fitting curve of $R^{\\\\prime}$ and $X_{c}^{\\\\prime}\\\\text{were}-5.8\\\\times 10^{-4}$ and $8.76 \\\\times 10^{-4}$ respectively. Therefore, EIM can effectively detect the state of low back muscles.\",\"PeriodicalId\":305829,\"journal\":{\"name\":\"2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMBioC52515.2022.9790108\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE MTT-S International Microwave Biomedical Conference (IMBioC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMBioC52515.2022.9790108","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of low back muscle state based on electrical impedance myography
In the prevention and rehabilitation stage of low back diseases, it is necessary to detect the state of muscles to avoid excessive fatigue and injury caused by continuous exertion of lumbar muscles. In this paper, an in vivo experimental platform for measuring low back muscle impedance was established in order to detect the different force states of muscle and study the corresponding relationship between muscle force state and muscle impedance. In the experiment, Biering-Sorensen (BS) test was used to make the low back muscle contract continuously, and different weights (5 kg, 2.5 kg, 0 kg) were used to distinguish the force state of muscle. The impedance analyzer was used to measure the muscle impedance parameters under different load in the subject's low back muscle for studying the electrical impedance characteristics of different low back muscle states. The results showed that the relative resistance $R^{\prime}$ of EIM was a downward trend with time and the 5 kg load had the fastest decline; The relative reactance $X_{c}^{\prime}$ of EIM was an upward trend with time, the 5 kg load also had the fastest rise. The slope $k$ of the fitting curve of $R^{\prime}$ and $X_{c}^{\prime}\text{were}-5.8\times 10^{-4}$ and $8.76 \times 10^{-4}$ respectively. Therefore, EIM can effectively detect the state of low back muscles.