Biosensors and Sensor Systems

This chapter is concerned with the design and operation of devices for the measurement of chemical concentrations in living systems. Whilst the meaning of chemical sensors has been somewhat broadened in recent years, a useful definition from a recent authoritative review (McDonagh et al, Chem Rev 108:400–422, 2008) is: “chemical sensors are miniaturised analytical devices that can deliver real time and online information on the presence of specific compounds or ions in complex samples”. Historically, a useful distinction was made between chemical sensors and biosensors in that a biosensor used a biologically derived element (enzyme, antibody, cell, tissue sample etc.) as part of the transduction process. This useful distinction has now been lost; biosensor is now often applied to any sensor measuring a chemical concentration in a biological system. Jiri Janata makes a further distinction between sensors and sensor systems, sensors being capable of continuous monitoring and sensor systems providing measurements in discrete steps. Turner, in a recent tutorial review (Turner APF, Chem Soc Rev 42:31284-3196, 2013) identifies two broad categories of device described under the heading ‘biosensor’: sophisticated and high-throughput lab-based instrumentation for rapid and accurate analysis of complex biological interactions and components, and portable easy-to-use devices for non-expert use, out of the lab, in the home or in a field environment, ‘point-of-care’ devices. This chapter will describe both chemical and biosensor (in the historical sense) approaches to the identification and quantification of chemical species in living systems and describe both sensors and sensor systems as described above. It will also outline recent developments, notably new materials with great potential for sensor applications. The underlying principles of the most widely used sensor types are described to enable their proper operation, design of control instrumentation, optimisation of sensor design and correct interpretation of the resulting data. Exemplar applications are given to illustrate these principles.