Paper

Physiological Information Reliability: Cross-Layer Adaptive Resource Allocation for Cardiovascular Sensing

Cardiovascular sensing systems must preserve clinically useful information despite signal degradation, wireless losses, energy constraints, and edge-computation latency. We introduce Physiological Information Reliability (PIR), a cross-layer framework that represents physiological information value jointly with wireless, energy, and computation states and uses a contextual bandit to adapt sensing and communication de · Authors: Navaneeth Krishnan Kamalakannan, Janakiraman Kamalakannan, Harinisri Velmurugan · Published 2026-08-31 · arXiv:2609.00435

Published
2026-08-31
Authors
3
arXiv
2609.00435
Category
eess.SP

Abstract

arXiv:2609.00435

Navaneeth Krishnan Kamalakannan, Janakiraman Kamalakannan, Harinisri Velmurugan

Cardiovascular sensing systems must preserve clinically useful information despite signal degradation, wireless losses, energy constraints, and edge-computation latency. We introduce Physiological Information Reliability (PIR), a cross-layer framework that represents physiological information value jointly with wireless, energy, and computation states and uses a contextual bandit to adapt sensing and communication decisions. We integrate multimodal ECG/PPG signal-quality estimation with physiological information value and an adaptive network-coding layer under burst-erasure conditions. Across controlled multiseed experiments, PIR-LinUCB demonstrates a promising low-energy operating point while maintaining medical latency constraints and competitive physiological estimation performance relative to fixed and heuristic policies. We analyze the resulting accuracy-energy-latency trade-offs and identify limitations of proxy PIV estimation and simulated communication dynamics. These results provide an initial computational demonstration of physiological-information-aware resource allocation and motivate future clinical and real-channel validation.