1 Introduction to Biosignal Processing

Biosignal processing is an interdisciplinary field of research that includes medical in-

formatics, signal processing and life sciences. The main objective of the analysis of

human biosignals is to support medical diagnosis with the help of mathematical meth-

ods. Intelligent evaluation of the signals should provide the medical practitioner with

valuable quantitative information in the diagnosis and effectively support them in

medical decision-making. The topics are wide-ranging: On the one hand, they include

signal processing, methods for monitoring and controlling vital functions in intens-

ive care medicine, for example through the automatic classification of signals, and

on the other hand, the formal description of the relationships between signals and

physiological functions in medical research. Another growing discipline is the mod-

elling of physiological phenomena to gain a deeper understanding of the underlying

pathological mechanisms to subsequently improve the technology in medical device

engineering. Modern simulation techniques often make use of statistical methods like

parameter variation and estimation, as well as the quantification of uncertainties in

the model approach – just to develop increasingly sophisticated data evaluation meth-

ods for diagnostic purposes. In many cases, these methods are the basis for optimal

control and regulation or lead to a complete replacement of physiological functions,

as for example in prosthetics.

The acquisition of biosignals for diagnostic purposes has a long history. Begin-

ning with the recognition of the electrical activity of nerve and muscle cells, which en-

gaged Luigi Galvani in his famous frog’s leg experiment in 1787, a chain of far-reaching

findings on the fundamental mechanisms of electrophysiology followed. As early as

1876, E. J. Marey succeeded in graphically depicting these processes for the first time.

Willem Einthoven received the Nobel Prize in Medicine in 1924 for the development

of the string galvanometer and the physiological interpretation of the electrocardio-

gram. Further development through the use of improved sensing and measuring tech-

nology, such as the tube amplifier, transistors and later integrated circuits as well as

the microprocessor technology, led to a considerable improvement in signal quality

over time.

Nowadays, the main focus of research is on increasingly sophisticated evaluation

algorithms, for example based on large amounts of data¹ and the miniaturisation of

measurement and transmission technology as well as data storage on the internet.

Today, the evaluation of information and signals from the human body is the basis

of almost every medical diagnosis. Electrocardiography (ECG) in particular has de-

veloped into one of the most frequently used medical examination methods – mil-

lions of ECGs are recorded in the world every day. Especially in the field of long-term

1 Evaluation of extremely large data sets with the help of computer algorithms with the aim of making

connections such as trends, correlations or patterns in the behaviour of the data visible.

https://doi.org/10.1515/9783110736298-001