E. Hoff, L. Brechtel, G. Barwolff, N. Natho, O. Pfeiffer, S. Jeschke
{"title":"A concept of mathematical methods for the optimization of the post-processing of nuclear resonance spectra of the human skeletal musculature","authors":"E. Hoff, L. Brechtel, G. Barwolff, N. Natho, O. Pfeiffer, S. Jeschke","doi":"10.1109/ISSPIT.2007.4458173","DOIUrl":null,"url":null,"abstract":"By means of 31P nuclear magnetic resonance (NMR) spectroscopy, metabolic conditions and changes in the resting and moving (human) musculature can be measured. Applications range from the examination of myopathies to the analysis of the composition of muscle fibers of competitive athletes. A vast amount of measurements of human skeletal muscles acquired using the 31P-NMR spectroscopy is waiting at hand to be processed. As manual processing of a single spectrum requires about half an hour of work form an exercised human analyzer several man-years of work are needed to do the job. Therefore a concept for the automatic post-processing of data acquired by 31P- NMR spectroscopy is presented.","PeriodicalId":299267,"journal":{"name":"2007 IEEE International Symposium on Signal Processing and Information Technology","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Symposium on Signal Processing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2007.4458173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
By means of 31P nuclear magnetic resonance (NMR) spectroscopy, metabolic conditions and changes in the resting and moving (human) musculature can be measured. Applications range from the examination of myopathies to the analysis of the composition of muscle fibers of competitive athletes. A vast amount of measurements of human skeletal muscles acquired using the 31P-NMR spectroscopy is waiting at hand to be processed. As manual processing of a single spectrum requires about half an hour of work form an exercised human analyzer several man-years of work are needed to do the job. Therefore a concept for the automatic post-processing of data acquired by 31P- NMR spectroscopy is presented.