An Iterative Spike Compression Method Based on Wavelet Transform and Heuristic Algorithm

Due to the constraints of bandwidth and power in implantable brain-computer interface, large amount of neural data cannot be easily transferred over a wireless link. Wavelet-based compression before transmission is a popular technique for reducing the data rate. But it struggles to achieve a well-ba...

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Veröffentlicht in:Biomedical Circuits and Systems Conference S. 1 - 5
Hauptverfasser: Ding, Yukun, Liu, Yirui, Liu, Xiao
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 24.10.2024
Schlagworte:
Brain-computer interfaces
Circuits and systems
CMOS process
Complexity theory
discrete wavelet transform
Discrete wavelet transforms
heuristic algorithm
Heuristic algorithms
implantable brain machine interface
Iterative algorithms
spike compression
System-on-chip
Wavelet coefficients
Wireless communication
ISSN:2766-4465
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Zusammenfassung:Due to the constraints of bandwidth and power in implantable brain-computer interface, large amount of neural data cannot be easily transferred over a wireless link. Wavelet-based compression before transmission is a popular technique for reducing the data rate. But it struggles to achieve a well-balanced trade-off between compression ratio and reconstruction error. In this article, we propose an iterative spike compression method based on discrete wavelet transform and heuristic algorithm. It can automatically search for the optimal combination of wavelet coefficients, trading longer processing time for higher compression ratio and lower reconstruction error. It has been validated in simulation that the proposed algorithm achieves a compression ratio of 9.25 on detected spike data with a reconstruction error of 3.63%. The proposed processor has been validated in the Cadence Virtuoso Environment using X-FAB's 180nm CMOS process. It occupies a chip area of 2.56 \mathrm{~mm}^{2} and consumes 385 \mu \mathrm{~W} power.
ISSN:2766-4465
DOI:10.1109/BioCAS61083.2024.10798407