Title :
A 128-Channel 6 mW Wireless Neural Recording IC With Spike Feature Extraction and UWB Transmitter
Author :
Chae, Moo Sung ; Yang, Zhi ; Yuce, Mehmet R. ; Hoang, Linh ; Liu, Wentai
Author_Institution :
Electr. Eng. Dept., Univ. of California-Santa Cruz, Santa Cruz, CA, USA
Abstract :
This paper reports a 128-channel neural recording integrated circuit (IC) with on-the-fly spike feature extraction and wireless telemetry. The chip consists of eight 16-channel front-end recording blocks, spike detection and feature extraction digital signal processor (DSP), ultra wideband (UWB) transmitter, and on-chip bias generators. Each recording channel has amplifiers with programmable gain and bandwidth to accommodate different types of biological signals. An analog-to-digital converter (ADC) shared by 16 amplifiers through time-multiplexing results in a balanced trade-off between the power consumption and chip area. A nonlinear energy operator (NEO) based spike detector is implemented for identifying spikes, which are further processed by a digital frequency-shaping filter. The computationally efficient spike detection and feature extraction algorithms attribute to an auspicious DSP implementation on-chip. UWB telemetry is designed to wirelessly transfer raw data from 128 recording channels at a data rate of 90 Mbit/s. The chip is realized in 0.35 mum complementary metal-oxide-semiconductor (CMOS) process with an area of 8.8 times 7.2 mm2 and consumes 6 mW by employing a sequential turn-on architecture that selectively powers off idle analog circuit blocks. The chip has been tested for electrical specifications and verified in an ex vivo biological environment.
Keywords :
CMOS integrated circuits; biomedical telemetry; electrocardiography; electroencephalography; electromyography; feature extraction; integrated circuits; medical signal detection; medical signal processing; neurophysiology; transmitters; ultra wideband communication; UWB telemetry; UWB transmitter; analog-to-digital converter; complementray metal-oxide-semiconductor process; digital signal processor; integrated circuit; nonlinear energy operator; on-chip bias generators; spike detection; spike feature extraction; ultra wideband transmitter; wireless neural recording IC; Digital signal processing (DSP); integrated circuit (IC); low-noise amplifier; neural recording system; ultra-wideband (UWB); Action Potentials; Equipment Design; Equipment Failure Analysis; Nerve Net; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Telemetry;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2009.2021607