Background: Heart signals represent an important way to evaluate cardiovascular function and often what is desired is to quantify the level of some signal of interest against the louder backdrop of the beating of the heart itself. An example of this type of application is the quantification of cavitation in mechanical heart valve patients.
Methods: An algorithm is presented for the quantification of high-frequency, non-deterministic events such as cavitation from recorded signals. A closed-form mathematical analysis of the algorithm investigates its capabilities. The algorithm is implemented on real heart signals to investigate usability and implementation issues. Improvements are suggested to the base algorithm including aligning heart sounds, and the implementation of the Short-Time Fourier Transform to study the time evolution of the energy in the signal.
This is a normal rhythm, and is not of diagnostic significance unless the rate, which ranges from 60 to 100 beats per minute, is not appropriate for the clinical setting.
This rhythm differs from normal sinus rhythm only in that the rate is above 100 beats per minute. The differential diagnosis is extensive. Common causes are anxiety; physiological stress such as hemorrhage, dehydration, sepsis, and fever; and hyperthyroidism. Correction of the underlying cause, if necessary, is recommended.
Biosignal is a summarizing term for all kinds of signals that can be (continually) measured and monitored from biological beings. The term biosignal is often used to mean bio-electrical signal but in fact, biosignal refers to both electrical and non-electrical signals.
Electrical biosignals (“bio-electrical” signals) are usually taken to be (changes in) electrical currents produced by the sum of electrical potential differences across a specialized tissue, organ or cell system like the nervous system. Thus, among the best-known bio-electrical signals are :
