Experimental models and measurements to study cardiovascular physiology

After reading this chapter, you should be able to:

appreciate the influence that the ‘observer effect’, ‘signal-to-noise ratio’, ‘sampling rate’ and ‘dynamic range’ have on experimental measurements (19.1);

understand the need for appropriate ‘positive and negative controls’, ‘randomization’, ‘blinding’ and adequate ‘statistical power’ when it comes to experimental design (19.1);

understand the basic principles behind common experimental models and measurement techniques used to study cardiovascular physiology (19.3–19.7);

appreciate the advantages and limitations of these techniques (19.3–19.7);

see how using a variety of experimental techniques across different spatial domains leads to a better approach to hypothesis-driven science (19.1);

appreciate the use of computational modelling to facilitate the reassembly and understanding of complex systems (19.8).