Nowadays, technological advancement of micro-electro-mechanical systems (MEMS) has enabled neural electrode for brain-machine interfaces (BMI) to be sophisticated. The size of the electrode pad has become smaller and the number of recording channels has increased that it can detect high-resolution signals in a wide-scale neuronal area simultaneously. On the other hand, recent wireless recording systems used for getting neural signal still have low data throughput that it can be used at restricted applications to record just small amounts of neuronal data, which drops the merits of the electrode. These wireless recording systems must overcome the disadvantage to achieve better experimental environment and fully implantable applications for freely moving living things.
Table Of Contents
I. Introduction 1 1.1 Background 1 1.2 Motivation 4 II. Methods 5 2.1 ECoG electrode array 5 2.2 Wireless recording system 8 2.3 Graphical user interface 11 2.4 Tactile stimulation system 13 2.5 In-vivo procedures 15 III. Results 18 3.1 Characterization of electrodes 18 3.2 Characterization of wireless recording system 20 3.2.1 Wireless connection 20 3.2.2 Operating performance 20 3.2.3 Current consumption 21 3.3 In-vivo validation 27 3.3.1 Recording test 27 3.3.2 Time and frequency analysis of SEPs 29 3.3.3 Time-frequency dynamics 34 IV. Conclusion 43 References 44