Design of Configurable Digital Spike Filtering Circuits in 130 nm CMOS Process In this paper, configurable digital spike filtering circuits are explored for removing unwanted noise pulses from the signals. The width of the spike to be suppressed from the signal is configurable. The circuits identify and remove both positive and negative spike pulses accurately. The presented circuits are implemented in 130 nm CMOS process. The asynchronous circuits are implemented in fully custom and fully synthesizable techniques which occupy an area of 252 xc3x97 323 xc2xb5mxc2xb2 and 127 xc3x97 127 xc2xb5mxc2xb2 and consumes 419 nW and 226 nW of power respectively from 1.2 V supply. The presented synchronous spike filtering circuit is fully synthesizable and it needs only 348 gate counts for its implementation with an area of 68 xc3x97 68 xc2xb5mxc2xb2. It draws only 83 nA current form supply for its full operation. The circuits are measured extensively and experimental results verify the accuracy of the proposed spike filtering circuits.

A 10 MSampleSec Digital Neural Spike Detection for a 1024 Pixels Multi Transistor Array Sensor This paper presents an FPGA implementation of a DSP performing real time spike detection on the electrical activity of an in vitro neuronal culture of rat hippocampi. The DSP enhances the Signaltonoise ratio (SNR) of samples recorded by a 1024 pixels Multi Transistor Array (MTA) at 9375 SamplesSec per pixel of  sim 6 boldsymbolmumathbfm  pitch. The implementation integrates in the same system a Time Division Multiplexing (TDM) filter and a spatiotemporal correlation algorithm, to increase the SNR up to identify spikes as low as  215 boldsymbolmumathbfV_0mathbfPEAK . The digital filter is a 2nd order high pass Infinite input response (IIR) Chebyshev filter. The spatiotemporal correlation exploits the MTA smaller pixels size and the high samplerate to compute an equivalent pixel from a group of 7 pixels and 3 consecutive frames for a total of 21 samples and it is supported by a multichannel noise power estimation. Finally, this paper shows the results achieved on the performed experiments and compares the system with others experiments using different sensors and algorithms.