A low-power low-data-rate neural recording system with adaptive spike detection

A design of small, low-power, low-data rate, wireless 32-channel neural recording system for small animal head-stage is presented. A neural pre-amplifier has low-input-referred-noise of 1.95 muVrms and consumes 53.6 muW. To enable digital telemetry with optimized bandwidth under size and power constraint for small-animal headstage, we propose to separately record spikes and local-field potentials. An adaptive spike detector using absolute value algorithm accompanied with 7th-order all-pass delay filter provides accurate on-chip acquisition of spike waveform in duration of 2 ms. A low-power 10-bit and 5-bit resolution A/D converters running at 22 Ksamples/s for active spikes and 200 samples/s for local field potential, respectively, can be integrated with the proposed system. Using adaptive bandwidth control, we achieve reduction of data-rate up to seven times which provides compatibility to 1 Mbps ultra low power Bluetooth technology. Total power consumption of single channel excluding ADCs is 109.58 muW in 3.3 V power supply.

[1]  Iyad Obeid,et al.  A WIRELESS MULTICHANNEL NEURAL RECORDING PLATFORM FOR REAL-TIME BRAIN MACHINE INTERFACES , 2004 .

[2]  Kari Halonen,et al.  A 12-bit Ratio-Independent Algorithmic ADC for a Capacitive Sensor Interface , 2007, 2007 IEEE International Symposium on Circuits and Systems.

[3]  Charles M. Higgins,et al.  Analog VLSI implementation of spatio-temporal frequency tuned visual motion algorithms , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.

[4]  R.R. Harrison,et al.  Validation of adaptive threshold spike detector for neural recording , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  Khalil Najafi,et al.  A wireless FM multi-channel microsystem for biomedical neural recording applications , 2003, Southwest Symposium on Mixed-Signal Design, 2003..

[6]  Xiao Yun,et al.  Low-Power High-Resolution 32-channel Neural Recording System , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  Reid R. Harrison,et al.  A low-power integrated circuit for adaptive detection of action potentials in noisy signals , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[8]  Patrick D. Wolf,et al.  Evaluation of spike-detection algorithms fora brain-machine interface application , 2004, IEEE Transactions on Biomedical Engineering.

[9]  P. Irazoqui-Pastor,et al.  In-vivo EEG recording using a wireless implantable neural transceiver , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..