Cloud-based Pulse Analysis System with Clinical Data Examination
Date Issued
2014
Date
2014
Author(s)
Chen, Wei
Abstract
The proposed pulse analysis system provides a platform for researchers to analyze, share, and store their pulse data. A novice and easy time-domain algorithm is applied to the pulse signals for periodic function examination. Monitoring and modeling our body as a system with pulse using digital pulse signals is one of the linkages that we can find between Traditional Chinese Medicine (TCM) and modern Information Communication Technology (ICT). With the labeling of diseases or some modern Bio-markers, we are able to link TCM, ICT, and the latest medical science together. The proposed method is capable of calculating the instability of the pulse wave of subjects. After finding the starting point of each period in a periodic wave, we use set theory as the constraint to detect stable periodic wave. With normal heart rate checking and the variability of each period checking, our algorithm can detect whether the input signal is normal, stable and periodic. A coefficient that represents the instability is calculated by the average standard deviation of each period in the waveform. The proposed system helps the automation for pulse examination to select a proper segment for harmonic analysis. The system is capable of using Fast Fourier Transform (FFT), harmonics, Ensemble Empirical Mode Decomposition (EEMD) as feature extraction, and using two-sample t-test as statistics and classification. An example of hospice patient death prediction shows that near-death patients within 7 days can be significantly separated from the others by the Standard Deviations (SD) of harmonics with the proposed pulse analysis system. With the periodic function examination method, non-survival sepsis patients in Continuous Mandatory Ventilation (CMV) mode or Continuous Positive Airway Pressure (CPAP) mode can be significantly separated.
Subjects
中醫
生醫資訊
資料處理
Type
thesis
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