A 64-channel neural signal processor/ compressor based on Haar wavelet transform

Abstract

A signal processor/compressor dedicated to implantable neural recording microsystems is presented. Signal compression is performed based on Haar wavelet. It is shown in this paper that, compared to other mathematical transforms already used for this purpose, compression of neural signals using this type of wavelet transform can be of almost the same quality, while demanding less circuit complexity and smaller silicon area. Designed in a 0.13-μm standard CMOS process, the 64-channel 8-bit signal processor reported in this paper occupies 113 μm x 110 μm of silicon area. It operates under a 1.8-V supply voltage at a master clock frequency of 3.2 MHz.

A 128‐channel discrete cosine transform‐based neural signal processor for implantable neural recording microsystems

“…where x i and x i are the reconstructed and the original action potentials, respectively, x i (p À p) is peak to peak of action potential, and N is the number of samples [13,16]. The compression capability of the DCT was investigated by performing simulation on a neural signal intra-cortically recorded from auditory cortex of a guinea pig [8].…”

“…In order to increase the number of recording channels, and at the same time considering the bandwidth limitation of a wireless link, researchers have devoted their efforts to reduce or compress the recorded data on the basis of discrimination between action potentials (which are believed to carry the main information) and background noise (which is usually of less importance). These attempts can be categorized in time-domain [7][8][9][10][11] and transformation-domain methods [12][13][14][15][16][17][18]. In [7] and [8], only the occurrence of action potentials is transmitted exteriorly.…”

“…Discrete wavelet transform is a transform with high compression ability, however, due to a high computation complexity not considered as suitable for high density neural recording systems. In [16], a 64-channel neural signal processor (NSP)/compressor based on Haar wavelet was reported. The Walsh-Hadamard transform as a suitable transform for neural data compression was proposed in [17], and a 64-channel implementation of this algorithm was reported.…”

“…The Walsh-Hadamard transform as a suitable transform for neural data compression was proposed in [17], and a 64-channel implementation of this algorithm was reported. Both [16] and [17] proposed algorithms with simple hardware implementations (by using only addition/subtraction operations), but they did not address the issue of sending the compressed neural data. This paper reports the design and development of a 128-channel NSP, which is based on the discrete cosine transform (DCT).…”

Implantable Biomedical Devices

“…A 64-channel neural data compressor based on Walsh-Hadamard Transform is presented in [29] with a compression factor of 72. But a more efficient 64-channel neural data compressor based on Discrete Haar-Wavelet Transform is presented in [30] with a compression factor of 112, in which has been claimed that has a more simpler circuit in comparison with the work in [29]. Anyway, data compressor approach is a power-and-area-hungry one.…”