S. Cerutti, A. Bianchi, B. Bontempi, G. Comi, P. Gianoglio, D. Liberati, P. Micossi, M. Sora
{"title":"Quantitative analysis of heart rate variability signal in diabetic subjects","authors":"S. Cerutti, A. Bianchi, B. Bontempi, G. Comi, P. Gianoglio, D. Liberati, P. Micossi, M. Sora","doi":"10.1109/IEMBS.1988.94449","DOIUrl":null,"url":null,"abstract":"An automatic procedure is presented for processing heart rate variability (HRV, taken from the ECG) and respiration of diabetic subjects with or without neuropathy. Spectral analysis is carried out using autospectra, cross-spectra, and coherence parametric methods (based on autoregressive modeling). Spectral parameters, and in particular the power associated with low-frequency and high-frequency bands, as well as the contribution of the HRV spectrum coherent with respiration, seem to discriminate satisfactorily between diabetic subjects with and without neuropathy. These results were obtained from the control population when resting/standing and when respiration was controlled. This fact reflects the impact of neural control systems on heart rate and respiration.<<ETX>>","PeriodicalId":227170,"journal":{"name":"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1988.94449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
An automatic procedure is presented for processing heart rate variability (HRV, taken from the ECG) and respiration of diabetic subjects with or without neuropathy. Spectral analysis is carried out using autospectra, cross-spectra, and coherence parametric methods (based on autoregressive modeling). Spectral parameters, and in particular the power associated with low-frequency and high-frequency bands, as well as the contribution of the HRV spectrum coherent with respiration, seem to discriminate satisfactorily between diabetic subjects with and without neuropathy. These results were obtained from the control population when resting/standing and when respiration was controlled. This fact reflects the impact of neural control systems on heart rate and respiration.<>