International Journal on Science and Technology

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AI-Based Novel Myobioscan device for Real-Time and Early Detection of Cardiovascular Implications

Author(s) Ravichandra Mulpuri
Country India
Abstract The Myobioscan system is a novel, AI-powered wearable platform developed for non-invasive, real-time monitoring of cardiovascular health. This pilot study evaluated its performance in 80 participants, including healthy individuals and those with diagnosed conditions such as atrial fibrillation, myocardial ischemia, and early-stage heart failure. Myobioscan integrates multi-channel ECG acquisition with sweat-based biochemical sensing for key cardiac biomarkers, including troponin-I, NT-proBNP, lactate, cortisol, pH, and electrolytes. A hybrid machine learning model combining convolutional neural networks (CNN), long short-term memory (LSTM), and XGBoost classifiers was employed to detect and classify cardiovascular anomalies. The device demonstrated strong diagnostic performance, achieving AUC-ROC values between 0.90 and 0.94 across conditions, with real-time alerting yielding a positive predictive value (PPV) of 94.1%. Subclinical abnormalities were detected in 4 asymptomatic individuals and confirmed through clinical follow-up. Sweat biomarker levels significantly differed between healthy and stressed participants, showing strong correlation with laboratory standards (e.g., Pearson’s r = 0.83 for troponin-I). User feedback revealed high satisfaction in terms of comfort (4.5/5), clarity of app feedback (4.7/5), and trust in results (4.3/5), with over 90% expressing interest in long-term use. These findings suggest that Myobioscan offers a comprehensive, patient-friendly solution for early detection and continuous monitoring of cardiovascular risk. With further validation, it holds strong potential to become a cornerstone in preventive cardiology and remote health management.
Keywords Myobioscan, AI-driven, Cardiovascular diseases, Biomarker
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 16, Issue 2, April-June 2025
Published On 2025-06-30
DOI https://doi.org/10.71097/IJSAT.v16.i2.6564
Short DOI https://doi.org/g9r8gp
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