Analysis of Lifting and B-Spline DWT Implementations for Implantable Neuroprosthetics

The large amount of data generated by neuroprosthetic devices requires a high communication bandwidth for extra-cranial transmission, critically limiting the number and utility of wireless implantable applications. Discrete wavelet transform (DWT) can provide exceptionally efficient data compression for neural records. Two energy efficient hardware implementations for one dimensional, multi-level, multi-channel DWT have been compared to identify the optimal approach for real time processing within an implanted device. This paper defines area-power minimized hardware implementation of the lifting and B-spline DWT schemes and analyzes their performance tradeoffs for implantable neuroprosthetics. The lifting scheme is shown to be increasingly superior for a larger number of input channels.