Name
Abstract | ||
|---|---|---|
This paper presents an analysis of the effectiveness of delta compression (DC) with additional entropy encoding, referred to as modified delta compression (MDC), as real-time compression scheme for neural spikes. Neural data compression which does not result in major distortion of the data is an attractive option to lower the transmitter power consumption. Since a lossy compression will result in a potentially undesirable loss of information the above mentioned compression scheme is analyzed regarding its ability to preserve the spike sorting relevant information content of the neural signals. Our analysis shows that MDC with thresholding is suitable for the compression of low-noise synthetic neural spike signals, but that its performance significantly degrades in the presence of higher noise levels or with recorded neural signals. In our simulations, the lossless MDC scheme achieves a mean compression rate of 2 without signal distortion. An example circuit realization for the compression of 100 channels synthesized in a 180 nm CMOS technology occupies a chip area of 0.72 mm2 and consumes 0.97 mW of power. Based on these results, it was found that the MDC scheme is capable of lowering the overall power consumption when the utilized wireless transmitters consume more than 121 pJ/bit which applies to most state of the art transmitter implementations. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/NEWCAS.2014.6934076 | NEWCAS |
Keywords | Field | DocType |
bioelectric potentials,brain-computer interfaces,data compression,encoding,medical signal processing,neurophysiology,transmitters,cmos technology,channel compression,chip area,circuit realization,data distortion,entropy encoding,information content,information loss,lossless mdc scheme,lossy compression,low-noise synthetic neural spike signal compression,mean compression rate,modified delta compression,neural data compression,noise levels,overall power consumption,power 0.97 mw,real-time compression scheme,real-time data compression,spike sorting,thresholding,transmitter implementations,transmitter power consumption,utilized wireless transmitters,sorting,principal component analysis,dictionaries,brain computer interfaces,entropy | Data compression ratio,Entropy encoding,Spike sorting,Lossy compression,Computer science,Electronic engineering,Data compression,Image compression,Delta encoding,Lossless compression | Conference |
ISSN | Citations | PageRank |
2472-467X | 1 | 0.41 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ulrich Bihr | 1 | 31 | 6.06 |
| Hongcheng Xu | 2 | 86 | 9.85 |
| christoph bulach | 3 | 1 | 0.41 |
| Matthias Lorenz | 4 | 20 | 4.65 |
| Jens Anders | 5 | 60 | 24.75 |
| Maurits Ortmanns | 6 | 501 | 114.46 |