Journal
ELECTRONICS
Volume 10, Issue 24, Pages -Publisher
MDPI
DOI: 10.3390/electronics10243068
Keywords
neuroscience; brain machine interface; digital signal processing; spike detection; low power; VLSI
Ask authors/readers for more resources
The study introduces a spike detector utilizing the ASO operator and noise estimation, achieving a good balance between performance and energy consumption, making it suitable for implantable BMIs.
High-density microelectrode arrays allow the neuroscientist to study a wider neurons population, however, this causes an increase of communication bandwidth. Given the limited resources available for an implantable silicon interface, an on-fly data reduction is mandatory to stay within the power/area constraints. This can be accomplished by implementing a spike detector aiming at sending only the useful information about spikes. We show that the novel non-linear energy operator called ASO in combination with a simple but robust noise estimate, achieves a good trade-off between performance and consumption. The features of the investigated technique make it a good candidate for implantable BMIs. Our proposal is tested both on synthetic and real datasets providing a good sensibility at low SNR. We also provide a 1024-channels VLSI implementation using a Random-Access Memory composed by latches to reduce as much as possible the power consumptions. The final architecture occupies an area of 2.3 mm(2), dissipating 3.6 mu W per channels. The comparison with the state of art shows that our proposal finds a place among other methods presented in literature, certifying its suitability for BMIs.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available