ABSTRACT
The remarkable increase in computational power and, more recently, advances in the architecture and size of field-programmable logic devices have made it possible to build devices inspired by mechanisms found in nature. Artificial neural networks and evolutionary algorithms are many examples of bio-inspired techniques that have been successfully developed and incorporated in commercial systems. This chapter discusses the fundamentals of bio-inspired sensors and gives some examples of their applications. The paradigm of the life-inspired systems originates from the observations with the aim that the microelectronic-based systems should have characteristics resembling the characteristics of individual life organisms or organized populations. In human health, bio-inspired sensors are common in areas such as cochlear implants to restore hearing, retinas to cure blindness, glucose monitoring and control for diabetes, and vestibular feedback to restore balance. Bio-inspired sensors commonly come as microchips, and they largely generate analog signals. As in the case of all analog sensors, the signal processing requires analog-to-digital and digital-to-analog conversions.
