A Platform-Agnostic Physiological Signal Compression Approach for Resource-Constrained Computational Headwear

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• Paper (IEEE Xplore)

Abstract

This paper presents a novel platform-agnostic architecture for physiological signal compression targeted at resource-constrained computational headwear. The approach enables real-time diagnostic integrity while maintaining efficiency on wearable devices with limited computational resources.

Citation

Radmehr, Amirmohammad. 2024. “A Platform-Agnostic Physiological Signal Compression Approach for Resource-Constrained Computational Headwear.” In 2024 IEEE 20th International Conference on Body Sensor Networks (BSN). IEEE. https://doi.org/10.1109/BSN63547.2024.10780594.

@inproceedings{radmehr2024compression,
  author = {Radmehr, Amirmohammad},
  title = {A Platform-Agnostic Physiological Signal Compression Approach for Resource-Constrained Computational Headwear},
  booktitle = {2024 IEEE 20th International Conference on Body Sensor Networks (BSN)},
  year = {2024},
  doi = {10.1109/BSN63547.2024.10780594}
}