gpbiometrics: An R Package for Reproducible Analysis and Reporting of Gazepoint Biometrics Exports

Abstract

Multimodal Gazepoint Biometrics exports may combine eye-tracking, pupil, electrodermal, cardiovascular, engagement dial, TTL/event, and AOI information, but they are rarely analysis-ready. gpbiometrics provides a Gazepoint-aware R workflow v7.2.0 for importing heterogeneous files and folders, detecting schemas, determining time bases and active channels, auditing data quality, preparing signals, aligning events and AOIs, creating model-ready summaries, generating report-ready outputs, and handing data to specialist external toolchains. Its principal contribution is therefore not a new physiological estimator but an auditable vendor-aware layer between Gazepoint exports and established biosignal and statistical software. In the manuscript demonstration, the common synthetic audit executed 63 functions without error or duplication; the advanced audit reached 89 optional functions, of which 84 completed on the generic CSV demonstration, 4 required richer input objects, and 1 XDF/LSL helper was appropriately not exercised. The experimental cluster-permutation module is restricted to paired two-condition, one-dimensional participant-level time courses and is illustrated with a controlled known-effect simulation; unsupported advanced variants fail explicitly. Synthetic data are used to assess software execution and workflow structure, not physiological or behavioural validity. The revised manuscript also distinguishes core processing, lightweight approximations, external bridges, and guardrails and documents reproducibility and privacy-safe real-data smoke testing. gpbiometrics does not translate signal-derived outputs into direct claims about emotion, stress, cognition, preference, health status, diagnosis, mechanism, or exact temporal onset.