From Respiratory Instability to Operational Monitoring: A Deterministic Phase-Memory Framework for Chest-Mounted Wearables

Abstract

Chest-mounted inertial sensing offers a low-cost route to continuous respiratory-pattern monitoring, but operational use is constrained by motion artifacts, baseline drift, nonspecific physiological interpretation, and the risk of treating an unvalidated deviation score as a diagnostic or readiness decision. This structured narrative review and methodological framework builds on a published proof-of-concept deterministic phase-memory operator for chest-mounted smartphone inertial measurement unit (IMU) signals. The present manuscript adds a translational validation architecture focused on high-exertion terrestrial training and occupational or first-responder heat-and-PPE tasks. It specifies signal-quality and artifact-rejection gates, a guarded dual-timescale baseline that limits absorption of progressive deterioration, pre-specified verification and validation endpoints, reference instrumentation, and governance requirements for privacy, autonomy, human oversight, and prohibition of unsupported automated command or employment decisions. Phase-memory divergence is retained as an auditable deviation observable rather than a disease classifier. A valid alert requires acceptable signal quality, no artifact-gate condition, threshold exceedance, and temporal persistence; otherwise, the required output is indeterminate/low quality. Real-time human-in-the-loop alerts and post-session trend analysis remain separate outputs. Proposed quantitative criteria are engineering targets for future preregistered studies, not achieved performance claims. The framework therefore defines a falsifiable pathway toward fit-for-purpose evaluation without claiming clinical validation, military qualification, spaceflight readiness, or deployment-level safety. Received: 13 May 2026 | Revised: 27 July 2026 | Accepted: 21 August 2026 Conflicts of Interest The author declares that he has no conflicts of interest to this work. Data Availability Statement No new empirical dataset was generated or analyzed for this framework article. The public repository at https://github.com/dfeen87/Smartphone-Based-Chest-Monitoring contains the reference implementation and reproducibility materials for the previously published respiratory proof-of-concept article, including documented parameters, tests, validation scripts, dependency files, and a one-command reproduction workflow. The repository does not constitute clinical or operational validation of the broader architecture, baseline safeguards, proposed go/no-go targets, or future application contexts described here. Any prospective confirmatory analysis must cite and archive the exact release/commit and configuration manifest used. Author Contribution Statement Marcel Krüger: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration.