Multimodal Wearable System for Continuous Physiological and Metabolic Monitoring Using Integrated Acoustic, Impedance, and Volatile Organic Compound Sensing with Machine Learning Pattern Classification for Disease Detection, Prediction, and Therapeutic Intervention

A method for detecting disease states through volatile organic compound pattern classification comprising:

• (a) continuously sampling skin-emitted volatile organic compounds using a metal-oxide semiconductor sensor array having a plurality of sensor elements with differential chemical sensitivity;
• (b) generating multi-dimensional sensor response patterns through temperature modulation of the metal-oxide semiconductor sensor array;
• (c) extracting features from the multi-dimensional sensor response patterns, wherein the features include steady-state responses, transient dynamics, and spectral characteristics;
• (d) classifying the extracted features using a trained machine learning model to identify disease-associated volatile organic compound patterns;
• (e) concurrently measuring autonomic biomarkers including a Vascular Resonance Shift Index (VRSI) and a Mechanical-Electrical Coherence Index (MECI) using bone-conduction acoustic sensing and bio-impedance spectroscopy;
• (f) fusing the classified disease-associated volatile organic compound patterns with the autonomic biomarkers to compute one or more disease-specific health indices;
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• (g) generating an alert when at least one of the one or more disease-specific health indices exceeds a predetermined threshold.

A multi-species physiological monitoring system for continuous assessment of a non-human subject, comprising:

• (a) a bone-conduction transducer configured to emit frequency-swept acoustic energy through biological tissue or plant tissue of the non-human subject spanning frequencies from 32 Hz to 1 MHz and to receive reflected mechanical responses;
• (b) a tetrapolar bio-impedance module comprising four electrodes configured to measure complex tissue impedance magnitude and phase at a body surface or stem surface of the non-human subject;
• (c) a metal-oxide semiconductor (MOX) volatile organic compound (VOC) sensor array positioned to continuously detect and classify volatile organic compound patterns emitted from a skin, integument, or plant surface of the non-human subject;
• (d) a processor configured to compute species-calibrated or plant-calibrated autonomic or physiological biomarkers from the acoustic, impedance, and VOC measurements and to perform machine learning classification of VOC patterns to identify disease-associated, stress-associated, or physiological-stress-associated signatures;
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• (e) a wearable or attachable housing configured for secure attachment to the non-human subject during normal activity, maintaining continuous sensor contact with target tissue.