The Spatial Well-Being Index (SWBI): A Neurobiologically Grounded Tool for Indoor Environmental Quality Assessment

The built environment shapes human neuroendocrine regulation through identifiable pathways, yet few assessment tools jointly integrate multiple neural mechanisms, biologically calibrated response functions, and evidence-derived weights in one operational framework. This paper presents the Spatial Well-Being Index (SWBI), a fourteen-criterion composite tool for assessing indoor environmental quality across luminous, acoustic, biophilic, and spatial domains. Each criterion maps a physical measurement to a normalised biological response via sigmoid or Gaussian functions, aggregated through a weighted geometric product so that distributed moderate deficits compound rather than average out. A deficit indicator ranks cost-aware intervention priorities. Application is demonstrated on an open-plan office in a North African coastal city, which scored 32.4 (Critical), produced by accumulation of distributed deficits rather than a single dominant stressor. SWBI is presented as a falsifiable, biologically informed proxy requiring future biomarker validation, not a predictor; its contribution is to translate dispersed environmental-neuroscience evidence into a transparent, reproducible structure.A bilingual (French/English) browser-based prototype implementing the SWBI scoring logic — including on-device camera-based estimation of illuminance and vegetation cover for a subset of criteria — is available at https://elaborate-mochi-04a635.netlify.app for field demonstration. The prototype is offered as a working illustration of the framework's computational feasibility, not as a validated measurement instrument; known measurement limitations (e.g. vegetation detection under strong sunlight, and the empirical anchoring of certain response-function thresholds) are documented transparently in the manuscript's Limitations section.Note: SWBI is a renamed and substantially revised evolution of an earlier framework by the same author (previously titled IHM), reflecting a change in scope, terminology, and formulation; it should be treated as a distinct work.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-02
DOI
https://doi.org/10.5281/zenodo.21139451
Primary Topic
Building Energy and Comfort Optimization
Type
preprint
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The Spatial Well-Being Index (SWBI): A Neurobiologically Grounded Tool for Indoor Environmental Quality Assessment

Tahar Boukhalfa
Zenodo (CERN European Organization for Nuclear Research)
Building Energy and Comfort Optimization
preprint

The Spatial Well-Being Index (SWBI): A Neurobiologically Grounded Tool for Indoor Environmental Quality Assessment

Tahar Boukhalfa
preprint en

Abstract

The built environment shapes human neuroendocrine regulation through identifiable pathways, yet few assessment tools jointly integrate multiple neural mechanisms, biologically calibrated response functions, and evidence-derived weights in one operational framework. This paper presents the Spatial Well-Being Index (SWBI), a fourteen-criterion composite tool for assessing indoor environmental quality across luminous, acoustic, biophilic, and spatial domains. Each criterion maps a physical measurement to a normalised biological response via sigmoid or Gaussian functions, aggregated through a weighted geometric product so that distributed moderate deficits compound rather than average out. A deficit indicator ranks cost-aware intervention priorities. Application is demonstrated on an open-plan office in a North African coastal city, which scored 32.4 (Critical), produced by accumulation of distributed deficits rather than a single dominant stressor. SWBI is presented as a falsifiable, biologically informed proxy requiring future biomarker validation, not a predictor; its contribution is to translate dispersed environmental-neuroscience evidence into a transparent, reproducible structure.A bilingual (French/English) browser-based prototype implementing the SWBI scoring logic — including on-device camera-based estimation of illuminance and vegetation cover for a subset of criteria — is available at https://elaborate-mochi-04a635.netlify.app for field demonstration. The prototype is offered as a working illustration of the framework's computational feasibility, not as a validated measurement instrument; known measurement limitations (e.g. vegetation detection under strong sunlight, and the empirical anchoring of certain response-function thresholds) are documented transparently in the manuscript's Limitations section.Note: SWBI is a renamed and substantially revised evolution of an earlier framework by the same author (previously titled IHM), reflecting a change in scope, terminology, and formulation; it should be treated as a distinct work.

Zenodo (CERN European Organization for Nuclear Research)
University Hospital of Oran (DZ)
Life below water
Building Energy and Comfort Optimization
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The Spatial Well-Being Index (SWBI): A Neurobiologically Grounded Tool for Indoor Environmental Quality Assessment — Tahar Boukhalfa · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS