Version 1
: Received: 24 September 2024 / Approved: 24 September 2024 / Online: 24 September 2024 (11:15:42 CEST)
How to cite:
Zheng, J.; Li, Y.; Chen, L.; Wang, F.; Gu, B.; Sun, Q.; Gao, X.; Zhou, F. The Impact of Data Packet Loss on Neural Decoding. Preprints2024, 2024091901. https://doi.org/10.20944/preprints202409.1901.v1
Zheng, J.; Li, Y.; Chen, L.; Wang, F.; Gu, B.; Sun, Q.; Gao, X.; Zhou, F. The Impact of Data Packet Loss on Neural Decoding. Preprints 2024, 2024091901. https://doi.org/10.20944/preprints202409.1901.v1
Zheng, J.; Li, Y.; Chen, L.; Wang, F.; Gu, B.; Sun, Q.; Gao, X.; Zhou, F. The Impact of Data Packet Loss on Neural Decoding. Preprints2024, 2024091901. https://doi.org/10.20944/preprints202409.1901.v1
APA Style
Zheng, J., Li, Y., Chen, L., Wang, F., Gu, B., Sun, Q., Gao, X., & Zhou, F. (2024). The Impact of Data Packet Loss on Neural Decoding. Preprints. https://doi.org/10.20944/preprints202409.1901.v1
Chicago/Turabian Style
Zheng, J., Xiang Gao and Fan Zhou. 2024 "The Impact of Data Packet Loss on Neural Decoding" Preprints. https://doi.org/10.20944/preprints202409.1901.v1
Abstract
Background: In the field of brain-computer interfaces, neural decoding plays a crucial role in translating neural signals into meaningful physical actions. These signals are transmitted to processors for decoding via wired or wireless channels, often encountering data loss, commonly referred to as "packet loss." Despite its importance, the impact of different types and degrees of packet loss on neural decoding has yet to be comprehensively studied. Understanding this impact is critical for advancing neural signal processing and data filtering.
Methods: This paper addresses this gap by constructing four distinct packet loss models, simulating congestion packet loss, distributed packet loss, and burst packet loss scenarios. Using macaque superior arm-movement decoding experiments, we evaluate the effects of these packet loss types on decoding performance.
Results: Our findings reveal that continuous burst packet loss significantly degrades decoding performance at the same packet loss probability, and decoding parameters that are sensitive to data continuity are more heavily impacted by packet loss.
Conclusions: This study provides an analysis of the relationship between packet loss and neural decoding results, offering valuable insights for future strategies aimed at preventing and handling packet loss in neural signal acquisition.
Keywords
Neural Decoding; Packet Loss; Gilbert-Elliott Model
Subject
Engineering, Bioengineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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