Title :
Distributed Intracortical Neural Interfacing: Network protocol design
Author :
Zabihian, Alireza ; Sodagar, Amir M. ; Sawan, Mohamad
Author_Institution :
EE Dept., Polystim Neurotechnologies Lab., Montreal, QC, Canada
Abstract :
New high-performance neural interfacing approaches are demanded for today´s Brain-Machine Interfaces (BMIs). In this paper, we present the architecture of a wireless network of implantable microsystems (Brain-ASNET: Brain Area Sensor NETwork). As well, we introduce an energy-efficient ad-hoc network protocol for the desired network, along with a method to overcome issue of variable packet length caused by bit stuffing process in HDLC standard protocol. To implement the idea, architecture and design of a System-on-a-Chip (SoC) is also presented. The SoC can be configured to be used either as a sensor node chip or the network coordinator´s RF front-end and network controller. The SoC is designed and laid-out in an IBM 0.13μm CMOS process. The post-layout simulation results show energy efficiency of the designed ad-hoc network protocol and low power dissipation of the SoC. The whole chip, including all functional and peripheral integrated components, consumes 138μW and 412μW, at 1.2V, configured in a synchronized network as a sensor node and the coordinator, respectively.
Keywords :
CMOS integrated circuits; ad hoc networks; brain-computer interfaces; neurophysiology; system-on-chip; wireless sensor networks; CMOS process; HDLC standard protocol; SoC; brain area sensor network; brain-ASNET; brain-machine interfaces; distributed intracortical neural interfacing approaches; energy-efficient ad-hoc network protocol; functional integrated components; high-performance neural interfacing approaches; implantable microsystems; network controller; network coordinator RF front-end; peripheral integrated components; post-layout simulation; power dissipation; sensor node chip; system-on-a-chip; wireless network; Ad hoc networks; Energy efficiency; Master-slave; Synchronization; System-on-chip; Wireless sensor networks;
Conference_Titel :
Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
Conference_Location :
Montpellier
DOI :
10.1109/NER.2015.7146604