Instant Preliminary Cardiac Analysis from Smartphone Auscultation: A Real-World Canine Heart Sound Dataset and Evaluation

TL;DR

This work introduces a real-world canine heart sound dataset collected via smartphone microphones and evaluates SoNUS 3.2.x for preliminary cardiac analysis. The system employs a multi-stage fallback with a quality-scoring gate to robustly extract heart-rate information under variable recording conditions, plus a fast 30–40 s variant for rapid analyses and a 60 s primary model for higher fidelity results. Quantitative results show heart-rate accuracy around 88.9–94.0% across models, with quality gating improving percentile performance and restricting user-facing outputs to reliable predictions; murmur detection could not be comprehensively assessed on real-world data due to noise and placement variability. The study demonstrates the feasibility of at-home, smartphone-based cardiac triage in veterinary care and lays groundwork for telehealth applications, longitudinal monitoring, and future cross-species data expansion.

Abstract

This study presents a real-world canine heart sound dataset and evaluates SoNUS version 3.2.x, a machine learning algorithm for preliminary cardiac analysis using smartphone microphone recordings. More than one hundred recordings were collected from dogs across four continents, with thirty eight recordings annotated by board certified veterinary cardiologists for quantitative evaluation. SoNUS version 3.2.x employs a multi-stage fallback architecture with quality-aware filtering to ensure reliable output under variable recording conditions. The primary sixty second model achieved mean and median heart rate accuracies of ninety one point six three percent and ninety four point nine five percent, while a fast model optimized for thirty to forty second recordings achieved mean and median accuracies of eighty eight point eight six percent and ninety two point nine eight percent. These results demonstrate the feasibility of extracting clinically relevant cardiac information from opportunistic smartphone recordings, supporting scalable preliminary assessment and telehealth applications in veterinary cardiology.

Figures (1)

• Figure 1: High-level overview of the SoNUS 3.2.x processing pipeline