Abstract
Conference Title: 2015 IEEE International Symposium on Circuits and Systems (ISCAS) Conference Start Date: 2015, May 24 Conference End Date: 2015, May 27 Conference Location: Lisbon, Portugal Real time spike detection is the first critical step to develop spike-sorting for integrated brain circuits interface applications. Nonlinear Energy Operator (NEO) and absolute thresholding have been widely used as the spike detection algorithms where NEO has a better performance measured by the probability of detection and false alarm. This paper proposes a hybrid spike detection algorithm incorporating both spike detection algorithms to reduce the power and to keep the detection rate the same as that of NEO. In the proposed algorithm, the absolute thresholding is performed first to detect a potential spike. Once a potential spike is detected, NEO is executed to check whether the detected spike by absolute thresholding is valid. Since NEO is conditionally conducted, this reduces the overall power consumption. The simulation shows that the proposed hybrid method improves the power consumption by 54.48% compared to NEO in 65 nm CMOS technology.