Multiscale Cochlear Biomechanical Modelling and the Environmental Auditory Risk Index (Eari) as Quantitative Forensic Markers of Environmental Noise Exposure

Background Environmental noise is a recurrent element in forensic disputes involving occupational exposure, neighbourhood conflicts and environmental crime. Although epidemiological data link noise to auditory dysfunction, current forensic practice rarely incorporates biomechanical indicators of cochlear overload, relying instead on sound-level records and subjective reports. Objective To investigate, via multiscale in silico cochlear modelling, whether typical environmental noise levels produce mechanical and neural alterations that can be translated into a quantitative forensic risk index. Methods Three complementary cochlear models were implemented in MATLAB: (i) a one-dimensional transmission-line model of basilar-membrane (BM) mechanics; (ii) a three-dimensional finite-difference time-domain fluid–structure interaction model; and (iii) a neuromorphic perceptual pipeline including ERB filterbanks, inner hair cell transduction and stochastic auditory-nerve spiking. Harmonic sweeps and speech-like stimuli were simulated under a quiet control (30 dB SPL) and an environmental noise condition (85 dB SPL). Results Across models, the noisy condition produced marked biomechanical and neurophysiological changes, including increased peak BM displacement along the cochlear partition, a flattened tonotopic gradient, and reduced spectral selectivity. Cochleograms' heatmaps exhibited an elevated noise floor and smeared activation bands, and spike rasters became denser and more irregular, particularly between 1 and 6 kHz. These outputs were normalised and combined into an Environmental Auditory Risk Index (EARI) that classified the 85 dB exposure as high auditory risk compared with the 30 dB control. Conclusion Multiscale cochlear modelling provides a reproducible, physiologically grounded framework for forensic environmental acoustics. By converting sound-level evidence into simulated inner-ear responses, the EARI offers an objective, mechanistic biomarker that informs expert testimony, complements audiometric data, and strengthens preventive policies for occupational and community noise control.