Arterial stiffness using radial arterial waveforms measured at the wrist as an indicator of diabetic control in the elderly.

IEEE Trans. Biomed. Engineering(2011)

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摘要
Although current technique of photoplethysmography (PPG) is a popular noninvasive method of waveform contour analysis in assessing arterial stiffness, data obtained are frequently affected by various environmental and physiological factors. We proposed an easily operable air pressure sensing system (APSS) for radial arterial signal capturing. Totally, 108 subjects (young, the aged with or without diabetes) were recruited from July 2009 to May 2010. Arterial waveform signals from the wrist were obtained and analyzed using Hilbert-Huang transformation (HHT). Through ensemble empirical mode decomposition (EEMD), the signals were decomposed into eight intrinsic mode functions (IMF1-8) of which IMF5 was found to be the desired signal with a discernible diastolic peak. The results showed significant differences in reflection index (RI) and stiffness index (SI) from the young subjects and those from the aged participants with or without diabetes. Significant differences in RI and SI were also noted between subjects with well-controlled diabetes and those without. Good reproducibility and correlation were demonstrated. In conclusion, the present study proposed the application of radial arterial signal capturing subsystem and HHT in acquiring more reliable data on RI and SI compared with the conventional PPG method.
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关键词
arterial stiffness,biomechanics,photoplethysmography,diseases,stiffness index (si),ensemble empirical mode decomposition,noninvasive method,waveform analysis,hilbert–huang transformation (hht),geriatrics,intrinsic mode functions,blood vessels,ensemble empirical mode decomposition (eemd),reflection index,air pressure sensing system,medical signal processing,hilbert-huang transformation,discernible diastolic peak,waveform contour analysis,radial arterial signal capturing,wrist,air pressure sensing system (apss),reflection index (ri),radial arterial waveforms,elderly,diabetic control,hilbert transforms,hilbert huang transform,indexation,white noise,diabetes,silicon,empirical mode decomposition,time frequency analysis
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