Title: From ECG to multimodal biosignals: BVidAL multimodal biosignal analyzer for ECG, EEG, EMG, PPG, PCG, respiration and hemodynamic signal analysis
Abstract:
Modern clinical assessment increasingly depends on the coordinated interpretation of heterogeneous physiological signals rather than the analysis of a single waveform in isolation. This work presents the BVidAL Multimodal Biosignal Analyzer within the BVidAL Clinical Software Suite, a Software as a Medical Device (SaMD) implementation based on the Novel Bansal Biology Theory and B-Bio Framework, with particular emphasis on the B-Multimodal Medical Imaging & BioSignal Framework. The software provides a unified environment for the acquisition, processing, visualization, comparative evaluation, longitudinal assessment, multimodal integration, and simulation of clinically relevant physiological signals. The broader B-Bio architecture is intended to coordinate heterogeneous biological and clinical information within a common computational environment.
The demonstrated biosignal environment incorporates electrocardiography (ECG), electroencephalography (EEG), electromyography (EMG), photoplethysmography (PPG), phonocardiography (PCG), respiratory signals, oxygen saturation, blood-pressure and hemodynamic measurements, and related physiological time-series data. Processing workflows include signal-quality assessment, filtering, artifact suppression, normalization, synchronization, waveform segmentation, event detection, morphology analysis, temporal and frequency-domain characterization, trend analysis, cross-signal coupling, and longitudinal comparison.
Using these heterogeneous multimodal biosignal and clinical datasets, patient-specific and representative digital-twin models are constructed to demonstrate drug-related simulations. Drug testing, efficacy assessment, therapeutic monitoring, and treatment-response simulations are performed on the resulting digital twins from both the clinical-physician perspective and the pharmaceutical-scientist perspective, enabling comparative examination of physiological and treatment-related responses within the software environment.
An important methodological and demonstration limitation must, however, be explicitly stated. Where a complete longitudinal dataset from a single patient is unavailable and as the patient suffering from more than one ailments is unknown and unavailable, data derived from multiple patients—effectively forming a cohort—are combined to construct a representative composite single-patient digital twin solely for demonstrating the capabilities of the SaMD and the Bansal Framework. Such composite representations are intended strictly for methodological research, simulation, validation, and software-demonstration purposes. They do not represent an actual individual patient record, must not be interpreted as one, and do not imply the availability of complete longitudinal observations from a single patient.
