The field of audiomics, which focuses on analyzing voice patterns to assess health conditions, has gained significant traction in recent years. A vocal biomarker test, a key component of audiomics, leverages artificial intelligence (AI) and advanced signal processing techniques to evaluate various vocal attributes such as pitch, tone, and rhythm. By identifying subtle changes in these features, researchers can detect physiological and psychological conditions, particularly those related to respiratory health. The relevance of this technology has surged since the COVID-19 pandemic, as respiratory diseases have become a major public health concern. [1,2]

The integration of AI into vocal biomarker analysis has refined diagnostic accuracy, enabling the identification of a broad spectrum of diseases. While the concept of using voice for medical assessment is not new, machine learning advancements have significantly improved the precision of diagnosis. This technology now facilitates the early detection and monitoring of conditions such as laryngeal pathologies, respiratory disorders, neurological impairments, psychological conditions, and even certain types of cancers affecting the head and neck. Experts from diverse medical fields, including neurology, speech-language pathology, internal medicine, otolaryngology, and pulmonology, contribute their specialized knowledge to enhance research and clinical applications in this domain. Their interdisciplinary insights help refine AI models and expand the potential of vocal biomarkers in medical diagnostics. [2,3]

One of the most compelling advantages of vocal biomarkers is their non-invasive nature. Unlike traditional diagnostic tools, which may require imaging, blood tests, or other invasive procedures, voice analysis can be conducted effortlessly using widely accessible devices such as smartphones and computers. This makes it a cost-effective, scalable, and user-friendly approach, paving the way for broader adoption in medical practice. As digital health technologies continue to evolve, vocal biomarkers are poised to play a transformative role in telemedicine, remote patient monitoring, and early disease detection. [2,3]

Recognizing the potential of this innovation, PinkTree in association with Koye Endeavours and Sonde Inc is getting the vocal biomarker test to India. This collaboration signifies an important step toward integrating AI-driven voice analysis into mainstream healthcare, offering a promising future for non-invasive diagnostics and digital medicine. [1]

References :-

1. https://www.sondehealth.com/sonde-healths-respiratory-responsive-vocal-biomarker-tool-differentiates
2. Bensoussan Y, Elemento O, Rameau A. Voice as an AI Biomarker of Health—Introducing Audiomics. JAMA Otolaryngology–Head & Neck Surgery. 2024 Apr 1;150(4):283-4.

Despotovic V, Elbeji A, Fuenfgeld K, Pizzimenti M, Ayadi H, Nazarov PV, Fagherazzi G. Digital voice-based biomarker for monitoring respiratory quality of life: findings from the colive voice study. Biomedical Signal Processing and Control. 2024 Oct 1;96:106555