Journal of Scientific Engineering Advances

Abstract

Background: Smartphone-based auscultation connects acoustic sensing, embedded electronics, digital signal processing, machine learning, and telemedicine. However, a phone microphone, a Bluetooth-linked electronic stethoscope, ECG-enabled sensors, and inertial approaches represent different engineering systems and should not be treated as interchangeable. Objective: This narrative review examines their technical architectures, validation requirements, clinical evidence, and translational limitations from a biomedical engineering perspective. Approach: We critically discuss selected technical studies, diagnostic evaluations, randomized implementation trials, regulatory documentation, and experience from the Strasbourg digital auscultation programme; no systematic search or quantitative meta-analysis was undertaken. Synthesis: Reliable acquisition requires attention to sensor coupling, frequency response, sampling, ambient noise, signal-quality assessment, and device-specific processing. Machine-learning performance depends on annotation quality, patient-level data separation, external validation, calibration, and resistance to distribution shift. Dedicated digital-stethoscope systems have stronger clinical validation than unassisted phone microphones. In the TRICORDER cluster-randomized trial, promising device-level capabilities did not yield a significant population-level increase in heart-failure diagnoses, underscoring the importance of implementation engineering. Conclusions: Smartphone auscultation should be designed and evaluated as an end-to-end, safety-critical biomedical system rather than as an isolated classification algorithm. Reproducible acoustic standards, prospective multicentre validation, interoperable workflows, human oversight, and patient-relevant outcomes are priorities for future research.