TY - CPAPER AB - In this paper, we present a new method for neuralspike sorting based on Continuous Time (CT) signal processing.A set of CT based features are proposed and extracted fromCT sampled pulses, and a complete event-driven spike sortingalgorithm that performs classification based on these features isdeveloped. Compared to conventional methods for spike sorting,the hardware implementation of the proposed method does notrequire any synchronisation clock for logic circuits, and thusits power consumption depend solely on the spike activity. Thishas been implemented using a variable quantisation step CTanalogue to digital converter (ADC) with custom digital logicthat is driven by level crossing events. Simulation results usingsynthetic neural data shows a comparable accuracy comparedto template matching (TM) and Principle Components Analysis(PCA) based discrete sampled classification. AU - Liu,Y AU - Pereira,J AU - Constandinou,TG DO - 10.1109/ISCAS.2016.7527296 EP - 541 PB - IEEE PY - 2016/// SP - 538 TI - Clockless Continuous-Time Neural Spike Sorting: Method, Implementation and Evaluation UR - http://dx.doi.org/10.1109/ISCAS.2016.7527296 UR - http://hdl.handle.net/10044/1/30125 ER -