A dedicated bit-serial hardware neuron for massively-parallel neural networks in fast epilepsy diagnosis

Kueh, Si Mon and Kazmierski, Tomasz (2017) A dedicated bit-serial hardware neuron for massively-parallel neural networks in fast epilepsy diagnosis. IEEE-NIH 2017 Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies, NIH Natcher Conference Centre, Bethesda, United States. 06 - 08 Nov 2017. pp. 105-108 . (doi:10.1109/HIC.2017.8227595).

Abstract

This paper outlines the feasibility of detecting epilepsy though low-cost and low-energy dedicated hardware with bit-serial processing. The concept of a novel bit-serial data processing unit (DPU) is presented which implements the functionality of a complete neuron. The proposed approach has been tested using various network configurations and compared with related work. The proposed DPU uses only 24 Adaptive Logic Modules on an Altera Cyclone V FPGA. An array of these DPUs are controlled by a simple finite state machine. The proposed DPU allows the construction of complex hardware ANNs that can be implemented in portable equipment that suits the needs of a single epileptic patient in his or her daily activities to detect impending seizure events.

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