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DC Field | Value | Language |
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dc.contributor.author | Wong De Balzan, Sara | - |
dc.date.accessioned | 2018-01-11T16:47:06Z | - |
dc.date.available | 2018-01-11T16:47:06Z | - |
dc.date.issued | 2014-10-14 | - |
dc.identifier.isbn | 9781628413625 | - |
dc.identifier.issn | 16057422 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923040527&doi=10.1117%2f12.2073558&partnerID=40&md5=f8c926fd4d2f56c3d69b451f62e7a4ca | - |
dc.identifier.uri | http://dspace.ucuenca.edu.ec/handle/123456789/28999 | - |
dc.description.abstract | Physiological signals are commonly the result of complex interactions between systems and organs, these interactions lead to signals that exhibit a non-stationary behaviour. For cardiac signals, non-stationary heart rate variability (HRV) may produce misinterpretations. A previous work proposed to divide a non-stationary signal into stationary segments by looking for changes in the signal's properties related to changes in the mean of the signal. In this paper, we extract stationary segments from non-stationary synthetic and cardiac signals. For synthetic signals with different signal-to-noise ratio levels, we detect the beginning and end of the stationary segments and the result is compared to the known values of the occurrence of these events. For cardiac signals, RR interval (cardiac cycle length) time series, obtained from electrocardiographic records during stress tests for two populations (diabetic patients with cardiovascular autonomic neuropathy and control subjects), were divided into stationary segments. Results on synthetic signals reveal that the non-stationary sequence is divided into more stationary segments than needed. Additionally, due to HRV reduction and exercise intolerance reported on diabetic cardiovascular autonomic neuropathy patients, non-stationary RR interval sequences from these subjects can be divided into longer stationary segments compared to the control group. | - |
dc.language.iso | en_US | - |
dc.publisher | SPIE | - |
dc.source | Progress in Biomedical Optics and Imaging - Proceedings of SPIE | - |
dc.subject | Diabetic Cardiovascular Autonomic Neuropathy | - |
dc.subject | Heart Rate Variability | - |
dc.subject | Non-Stationary Time Series | - |
dc.subject | Rr Interval | - |
dc.subject | Scale Invariance | - |
dc.subject | Statistical Analysis | - |
dc.subject | Stress Test | - |
dc.subject | Synthetic Data Generation | - |
dc.title | Extracting stationary segments from non-stationary synthetic and cardiac signals | - |
dc.type | Article | - |
dc.description.city | Cartagena de Indias | - |
dc.ucuenca.idautor | 081929618 | - |
dc.identifier.doi | 10.1117/12.2073558 | - |
dc.ucuenca.embargoend | 2022-01-01 0:00 | - |
dc.ucuenca.afiliacion | wong, s., grupo de bioingeniería y biofísica aplicada, universidad simon bolívar, caracas, venezuela, investigador prometeo, universidad de cuenca, ecuador | - |
dc.ucuenca.correspondencia | Altuve, M.; Grupo de Bioingeniería y Biofísica Aplicada, Universidad Simon BolívarVenezuela | - |
dc.ucuenca.volumen | 9287 | - |
dc.ucuenca.indicebibliografico | SCOPUS | - |
dc.ucuenca.numerocitaciones | 2 | - |
dc.ucuenca.nombrerevista | 10th International Symposium on Medical Information Processing and Analysis | - |
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documento.pdf | 168.92 kB | Adobe PDF | View/Open |
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