The use of digital signal processors (DSPs) in real-time processing of multi-parametric bioelectronic signals

In many cases of bioanalytical measurement, calculation of large amounts of data, analysis of complex signal waveforms or signal speed can overwhelm the performance of microcontrollers, analog electronic circuits or even PCs. One method to obtain results in real time is to apply a digital signal processor (DSP) for the analysis or processing of measurement data. In this paper we show how DSP-supported multiplying and accumulating (MAC) operations, such as time/frequency transformation, pattern recognition by correlation, convolution or filter algorithms, can optimize the processing of bioanalytical data. Discrete integral calculations are applied to the acquisition of impedance values as part of multi-parametric sensor chips, to pH monitoring using light-addressable potentiometric sensors (LAPS) and to the analysis of rapidly changing signal shapes, such as action potentials of cultured neuronal networks, as examples of DSP capability.