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Area-Power Efficient VLSI Implementation of Multichannel DWT for Data Compression in Implantable Neuroprosthetics

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4 Author(s)
Kamboh, A.M. ; Michigan State Univ., East Lansing ; Raetz, M. ; Oweiss, K.G. ; Mason, A.

Time-frequency domain signal processing of neural recordings, from high-density microelectrode arrays implanted in the cortex, is highly desired to ease the bandwidth bottleneck associated with data transfer to extra-cranial processing units. Because of its energy compactness features, discrete wavelet transform (DWT) has been shown to provide efficient data compression for neural records without compromising the information content. This paper describes an area-power minimized hardware implementation of the lifting scheme for multilevel, multichannel DWT with quantized filter coefficients and integer computation. Performance tradeoffs and key design decisions for implantable neuroprosthetics are presented. A 32-channel 4-level version of the circuit has been custom designed in 0.18-mum CMOS and occupies only 0.22 mm2 area and consumes 76 muW of power, making it highly suitable for implantable neural interface applications requiring wireless data transfer.

Published in:

Biomedical Circuits and Systems, IEEE Transactions on  (Volume:1 ,  Issue: 2 )