Pulse Analysis System with a Novice Periodic Function Examination Method on Sepsis Survival Prediction

This project proposes a pulse analysis system for doctors to diagnose their patients using their pulse signals. A novice and easy time-domain algorithm is applied to pulse signal for periodic function examination. Monitoring and modeling our body as a system with digitalized pulse signals is one of the linkages that we can find among Traditional Chinese Medicine (TCM), hemodynamics and modern Information Communication Technology (ICT). With the labeling of diseases or some modern Bio-markers, we are able to link pulse analysis, 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 (SD) of each period in the waveform. The proposed system helps the automation of pulse examination to select a proper segment for harmonic analysis. 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.