Digital Stethoscopes in the Age of AI and Connected Medicine: Clinical Implications for Practice
For over two centuries, the stethoscope has been a cornerstone of clinical medicine, yet traditional acoustic models are limited by environmental noise, user experience, and the subjective nature of auscultation. Digital stethoscopes, augmented by signal processing, visualization tools, and Artificial Intelligence (AI), represent a transformative evolution in auscultatory practice. These devices convert acoustic signals into digital data, enabling amplification, noise reduction, and objective analysis through phonograms and spectrograms. AI integration enhances diagnostic accuracy by detecting and classifying cardiac and respiratory abnormalities, while connectivity features facilitate telemedicine, remote monitoring, and longitudinal patient care. Clinical studies consistently demonstrate the superiority of digital over acoustic stethoscopes in detecting subtle heart murmurs, lung sounds, and arrhythmias, particularly in complex or noisy settings. Beyond clinical diagnostics, digital stethoscopes serve as educational tools, providing visualized, recordable, and analyzable auscultatory data. As part of the emerging Medicine 3.0 ecosystem, these devices align with predictive, preventive, personalized, participatory, and precision (5P) medicine, offering new opportunities for global health equity, chronic disease management, and medical education. This review synthesizes current evidence on the technology, clinical performance, AI applications, and telemedicine integration of digital stethoscopes, highlighting their potential to redefine auscultation in the 21st century.
Andrès E1,2, El Hassani HA3, Talha S2,4, Lavigne T2,5, Terrade JE1, Jannot X1 and Lorenzo-Villalba N1