Thomas Pendel, Karl Kesper, Heinrich F. Becker
1 Department for Internal Medicine, University Hospital of Philipps-University, Marburg, Germany
Biosignal monitoring and recording is the extension of medical investigations taking into consideration the development over time. The usual practice for medical tests is the investigation at one particular time point when the physician sees the patient. Besides the clinical interview the physician checks the pulse, measures blood pressure, takes a blood sample and sometimes urinary sample, and perhaps also measures body temperature and sweating. This collected information is used to develop a diagnosis or if it is not sufficient, to request more investigations. The additional investigations are in many cases functional tests or image-producing examinations. Such examinations can be radiology or ultrasound investigations or endoscopic or angiographic investigations. Functional investigations being requested can be electrocardiography, lung function test or a physical stress test. All these investigations are really point measures even if they involve image generation or a functional test over a short period of time. These point measures are used to generate a medical diagnosis. Based on the diagnosis the physician tries to predict changes over time (e.g. development of a disease or a treatment outcome). In order to verify these predicted changes often a second or a third investigation follows after a couple of days or weeks, again being point measures in essence. This type of measurement is always restricted to a few time points (Figure 13-1).
By its nature it cannot give any conclusion about the dynamic behavior of physiological systems. Functional tests are the only and still limited approach to dynamic behavior. To extend the investigations of physiological variables in the time domain is the primary aim of biosignal acquisition or in other terms time series analysis in medicine. By this approach a better understanding of physiological control systems can be achieved. Predictions can be improved by considering the dynamic behavior of physiological regulation.
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