Part of the book: Biomedical Engineering
Part of the book: Advances in Bioengineering
We analyse the heartbeat interval time series in this chapter. Our time series analysis concepts and techniques have been reported previously, for example, in the Intech Book chapter. Here, we would like to introduce how it works by presenting typical examples. The techniques can distinguish between healthy, sick and stressful hearts. All data were obtained by us from natural heartbeat data. Therefore, we have notes behind data, especially about behavioural psychological observations. Results of analysis are the following: healthy hearts exhibit a healthy scaling exponent (SI), which is near 1.0, stressful hearts exhibit a lower SI, such as 0.7, dying heart’s SI approaches to 0.5, and so forth.
Part of the book: Time Series Analysis and Applications
Modified detrended fluctuation analysis (mDFA) is a novel method to check abnormality of heartbeat which is developed recently by the author. mDFA can characterize any oscillation such as heartbeat by the scaling exponent (scaling index, SI). Healthy heartbeat shows SI = 1. Dying heart’s SI sifts toward 0.5. Ischemic sick heart experimentally showed an SI way over 1.0 approaching 1.5. Random vibration, such as FM-radio noise and idling car-engine, shows SI = 0.5. Quietly running motor generates an SI almost equal to zero. Using mDFA, it is possible to check potential risk based on SI values. This chapter shows empirical results quantifying various signals from heartbeat to material vibration.
Part of the book: Noise and Vibration Control