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Automated Pulse-Based Diagnosis: Role of TIM Diagnostic Features
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作者 rajani r. joshi 《Journal of Biomedical Science and Engineering》 2014年第10期781-787,共7页
Emanated from the idea of reinvestigating ancient medical system of Ayurveda—Traditional Indian Medicine (TIM), our recent study had shown significant applications of analysis of arterial pulse waveforms for non-inva... Emanated from the idea of reinvestigating ancient medical system of Ayurveda—Traditional Indian Medicine (TIM), our recent study had shown significant applications of analysis of arterial pulse waveforms for non-invasive diagnosis of cardiovascular functions. Here we present results of further investigations analyzing the relation of pulse-characteristics with some clinical and pathological parameters and other features that are of diagnostic importance in Ayurveda. 展开更多
关键词 Pulse-Based DIAGNOSIS Spectral Parameters TIM (Traditional Indian Medicine) DIAGNOSTIC FEATURES Statistical Analysis
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Automatic detection of pulse morphology patterns &cardiac risks
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作者 rajani r. joshi Ganesh B. Nawsupe Smita P. Wangikar 《Journal of Biomedical Science and Engineering》 2012年第6期315-322,共8页
Analysis of arterial pulse waveforms is important for non-invasive diagnosis of cardiovascular functions. Large samples of IPG signal records of radial arterial pulse show presence of eight different types of shapes (... Analysis of arterial pulse waveforms is important for non-invasive diagnosis of cardiovascular functions. Large samples of IPG signal records of radial arterial pulse show presence of eight different types of shapes (morphological patterns) in the pulse waveforms. In this paper we present an efficient computational method for automatic identification of these morphological patterns. Our algorithm uses likelihood ratio of cumulative periodogram of pulse signals and some geometrical criteria. The algorithm is presented with necessary details on signal processing aspects. Results for a large sample of pulse records of adult Indian subjects show high accuracy of our algorithm in detecting pulse-morphology patterns. Variation of pulse-morphology with respect to time is also analyzed using this algorithm. We have identified some characteristic features of pulse-morphology variation in patients of certain cardiac problems, hypertension, and diabetes. These are found relevant and significant in terms of physiological interpretation of the associated shapes of pulse waveforms. Importance of these findings is highlighted along with discussion on overall scope of our study in automatic analysis of heart rate variability and in other applications for non-invasive prognosis/diagnosis. 展开更多
关键词 PULSE Signal SPECTRAL Analysis—Fisher’s Ratio MORPHOLOGY Variation GEOMETRICAL Modeling
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