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Conceptual framework enhances emotional architecture in AI, suggesting new methodologies for emotion recognition.
published a conceptual framework for biosignal-based emotional architecture in AI (AE — Artificial Emotion) and received feedback that the formalism was missing.I have now written the technical version. Key contributions:• Emotional State Vector formally defined as element of complete metric space (R²⁰, d_ESV)• Sparx Index defined as HF band coherence Γ ∈ [0,1] — proved bounded via Cauchy-Schwarz• Emotional Fourier Transform as bounded linear operator on L² — isometry via Plancherel• Four-module signal processing pipeline with transfer functions• Three falsifiable propositions with pre-specified statistical tests• 20 citations — Porges, McCraty, Dumas, Thayer, Task Force 1996DOI: 10.5281/zenodo.18917446Genuinely looking for: errors in the mathematics, better feature sets than d=20, prior work I have missed, or anyone working in adjacent areas (affective computing, HRV, EEG hyperscanning).
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Prabhat Negi (2026) studied this question.
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