2.2 Connection between Signals and Systems

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physiological system is expressed in the form of signals and the appropriate analysis of

the generated signals consequently leads to diagnostically usable system knowledge.

If one transfers this knowledge to the process of analogue modulation in Figure 2.2,

the information signal sI(t) in the figure thus becomes the partially unknown influence

quantity or the physiological information of a biological system to be decoded and the

carrier signal sT(t) the non-informative part of the biosignal and consequently sU(t)

the measured biosignal. For this reason, the analysis of a biosignal is often done like

a decoding of an encrypted signal with incomplete knowledge of the code used.

2.2 Connection between Signals and Systems

In classical signal processing, the processing and transmission of information gener-

ally takes place in the form of signals, i.e. the information is encoded by a measurable

change in a physical quantity. This quantity can be, for example, the change of an

electrical potential difference on the surface of the human body, as in the electrocar-

diogram, or also the local change of the magnetic field vector of a data bit on a data

carrier, e.g. a hard disk. The methods for processing the information are basically the

same; they usually take on the character of a signal processing system. This can be,

for example, a simple shifting of the signal, or as shown in subsubsection 5.3.4.2, a

digital filtering or the like (cf. Figure 2.6).

x(t)

T

x(t −T)

x(t)

h(t)

x(t) ∗h(t)

Fig. 2.6: Two different digital systems: a time-shifting system that delays the input signal x(t) by T

(left) and a digital convolution filter that convolves the input signal x(t) with the impulse response

h(t) of the system (right).

In biosignal processing, signal-processing systems are used in particular for signal

conditioning, i.e. freeing the signal from interference. However, in the subsequent

analysis of the biosignals for diagnosis finding, it is a matter of identifying important

diagnostic parameters of a signal-generating system. An example of such a signal gen-

erating system is the human heart. This physical system has a fundamentally different

importance compared to the signal-processing systems. These systems generate im-

portant diagnostic information during operation, such as an electrically measurable

ECG signal of heart excitation.

To illustrate this fact, let us take an exemplary look at the system character and

the biosignals generated by the human heart. Consisting of four blood-filled cavities

separated by heart valves and a conduction system of nerve and muscle fibres, the

heart is stimulated by nerve impulses to cyclic contractions of the heart muscle. In

doing so, it generates a multitude of biosignals which describe the state of the system