This report presents a verification analysis of biological coherence using openly available wearable biosignal datasets. The study evaluates temporal alignment and synchronization patterns across heart-rate variability (HRV), respiration, photoplethysmography (PPG), electrodermal activity (EDA), and accelerometry (ACC). Multiple coherence measurements are introduced, including the κₜ temporal alignment metric, phase-locking relationships, surrogate-based null models, and multi-signal synchrony indices. The goal is to assess whether coherence can be treated as a measurable, falsifiable phenomenon within biological time-series data. This work provides a full replication protocol, detailed preprocessing steps, statistical thresholds, and criteria for independent verification by laboratories, signal-research teams, and academic institutions. Developed without access to specialized lab equipment, this framework relies entirely on open data, transparent analyses, and reproducible methods. This manuscript is part of the emerging discipline of Coherence Physics, which explores how biological systems synchronize, stabilize, and communicate through measurable patterns of coherence.