Physiological Monitoring of Sound-Based Relaxation Using Binaural Audio and Vibroacoustic Stimulation

Immersive audio and vibroacoustic stimulation have gained increasing attention as non-invasive approaches for modulating human emotional and physiological states. The SonikB3D platform was previously introduced as a multisensory system combining immersive 3D audio, vibroacoustic stimulation, and physiological monitoring. Building upon this prior work, the present study advances the platform through a refined experimental protocol and a data-driven framework for the automatic assessment of relaxation using multimodal biosignals. A controlled pilot study was conducted with 20 participants exposed to 3D sound and vibroacoustic stimulation delivered through a massage table equipped with integrated transducers. Although the SonikB3D platform supports multiple stimulation scenarios, the present study focuses on a single controlled condition combining binaural 3D audio (binaural beats plus music) and vibroacoustic stimulation in order to ensure methodological consistency for multimodal modelling. Physiological responses were continuously recorded using a synchronized setup including electroencephalography (EEG), photoplethysmography (PPG), and electrodermal activity (EDA). Subjective emotional self-assessment questionnaires were collected before and after exposure to provide a multidimensional characterization of participant responses. Results show a statistically significant increase in self-reported relaxation (paired t-test = 3.05, p = 0.01), corresponding to an average 8% improvement in normalized relaxation scores. To support objective assessment, multimodal physiological features associated with autonomic and emotional regulation were extracted and used to develop a two-stage machine learning pipeline. The proposed model, combining a window-level Random Forest classifier with session-level aggregation, achieved an accuracy of 80% and an F1-score of 0.857 in classifying relaxation-related states. These findings provide preliminary evidence that combined 3D audio and vibroacoustic stimulation can produce measurable changes in subjective and physiological indicators of relaxation, while demonstrating the feasibility of automatic relaxation state inference from multimodal biosignals. Although exploratory due to the limited sample size and the absence of unimodal control conditions, this work contributes a data-driven methodology for studying human responses to multisensory sound and vibration metrics.