Smartwatch-Based Detection of Ventricular Dysrhythmias: A Systematic Review of Literature.

BACKGROUND

The rise of smartwatches introduces a novel technology for detecting dysrhythmias. However, the diagnosis of ventricular dysrhythmias (VDs) usually requires automatic recording modes. There is a scarcity of literature on smartwatch-based VDs detection.

OBJECTIVES

We conducted a literature review to synthesize current evidence on the clinical profiles of smartwatch-detected VDs and to highlight their detectability in real-world settings.

METHODS

PubMed, Embase, Scopus, and the Cochrane Library were searched from inception to May 2025 for studies reporting smartwatch-based detection of VDs, with availability of participant-level data. Two investigators independently extracted study data and quality.

RESULTS

A total of 20 patients from 18 articles were included, with a mean age of 48 years; 35% were over 60 years of age, and 35% had a documented history of structural heart disease. Primary complaints were palpitations (70%) and syncope (20%). Sustained monomorphic ventricular tachycardia was the most common dysrhythmia (60%), followed by polymorphic ventricular tachycardia (25%). Vasospastic angina and idiopathic ventricular tachycardia were the leading diagnoses. Interventions included coronary angiography (25%), electrophysiology studies (35%), catheter ablation (35%), and implantable cardioverter defibrillators (45%). The rest received medical therapy.

CONCLUSIONS

Smartwatches may provide valuable outpatient data that support timely diagnosis and appropriate therapy across diverse clinical scenarios. As exemplified in this review, the detectability of VDs through smartwatches in real-world settings is feasible. Emergency department interrogation of smartwatch data may provide valuable information.