International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI‑Powered Wireless Stethoscope for Early Prediction of Cardiac and Pulmonary Diseases

Author(s) Mr. Amit Kumar Singh
Country India
Abstract Cardio‑pulmonary diseases such as arrhythmia, chronic obstructive pulmonary disease (COPD), pneumonia, tuberculosis (TB), asthma, and lung cancer remain leading causes of global morbidity and mortality, particularly in low‑resource and primary care settings where access to advanced diagnostic tools is limited. Conventional auscultation using acoustic stethoscopes is subjective, experience‑dependent, and often insufficient for early disease detection. This paper presents an AI‑powered wireless stethoscope designed for early prediction and screening of major heart and lung diseases using digital auscultation signals. The proposed system integrates high‑fidelity acoustic sensors, edge processing, wireless connectivity, and cloud‑based artificial intelligence models to analyze heart and lung sounds in real time. Advanced signal processing and deep learning techniques are employed to extract pathological patterns associated with arrhythmia, COPD, pneumonia, TB, asthma, and lung cancer. The system functions as a clinical decision‑support tool, providing risk scores and explainable insights to clinicians while preserving traditional workflow. Experimental validation demonstrates the feasibility of accurate, low‑cost, and scalable early screening, making the system suitable for deployment in hospitals, primary health centers, and remote care environments.
Keywords AI Stethoscope, Digital Auscultation, Cardio‑Pulmonary Diseases, Arrhythmia Detection, Lung Sound Analysis, Wireless Medical Devices
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-17
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.63712
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E-ISSN 2582-2160
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