Vocal Biomarkers in the Management of Heart Failure: Pathophysiological Basis, Current Evidence, and Future Perspectives

Introduction: Chronic heart failure (HF) represents a major challenge in contemporary healthcare and is associated with a substantial risk of morbidity, mortality, and recurrent hospitalization. Despite advances in pharmacological therapy, a proportion of patients remain at high risk of decompensation following hospital discharge. Current remote monitoring strategies, including daily body weight assessment and self-reported symptoms, often fail to detect fluid retention and pulmonary congestion at an early stage. One of the major challenges in heart failure management is the early detection of clinical deterioration, particularly during the stage when fluid retention and pulmonary congestion begin to develop while overt clinical symptoms remain minimal. Existing monitoring approaches do not always allow for the early identification of underlying pathophysiological changes.

In recent years, advances in digital health and artificial intelligence (AI) technologies have created new opportunities for the remote management of chronic diseases. Among these, vocal biomarkers have attracted increasing interest. Vocal biomarkers are digital indicators derived from acoustic characteristics of the human voice that may reflect underlying physiological changes within the body.

Objective: The aim of this review is to evaluate the pathophysiological basis, current clinical evidence, technological potential, and existing challenges associated with the use of vocal biomarkers in heart failure management.

Methods: A narrative literature review was conducted. The literature search was performed using the PubMed/MEDLINE, Scopus, and Web of Science databases. The following keywords were used: “heart failure,” “vocal biomarkers,” “voice analysis,” “artificial intelligence,” “digital biomarkers,” and “remote monitoring.” Particular emphasis was placed on studies published between 2020 and 2025 that investigated the association between vocal characteristics and the clinical status of patients with heart failure, the risk of hospitalization, and the potential applications of voice-based remote monitoring.

Key Findings: Existing studies suggest that specific acoustic characteristics of the human voice may be associated with physiological changes occurring in patients with heart failure. Parameters commonly evaluated in vocal biomarker analysis include jitter, which reflects short-term variability in vocal fold vibration; shimmer, a measure of periodic variation in voice amplitude; the harmonic-to-noise ratio (HNR); speech rate; phonation duration; and the temporal structure of speech pauses. Artificial intelligence-based algorithms have demonstrated the potential to detect subtle changes in vocal characteristics that may be associated with the early stages of heart failure deterioration.

However, the current evidence remains insufficient for definitive clinical implementation and requires further validation, particularly through large-scale, multicenter studies conducted across diverse patient populations.

Conclusion: Vocal biomarkers represent a promising emerging field in digital cardiology. Although they cannot currently replace standard clinical assessment of heart failure, they may serve as an additional digital tool for remote patient monitoring and early risk stratification. Further research is required to establish their clinical effectiveness, reliability, and feasibility of integration into routine clinical practice.