Efficient Implementation of Movement Decoding for Brain Computer Interface Using Fixed-Point Arithmetic

Spring 2013

Student
Alvin Mao
Advisor
Xin Li
Project description

In this project, efficient implementation of movement decoding for brain computer interface (BCI) will be developed by using fixed-point arithmetic. The objective of BCI is to provide a direct control pathway from brain to external devices. It is a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. This project will study the on-chip implementation of movement decoding algorithms for a low-power BCI system. In particular, the student will develop a movement decoding flow by using the HDL Coder tool offered by MATLAB Simulink. The aforementioned decoding flow will be further used to study the trade-off between power consumption and decoding accuracy for the BCI system.

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