NEW YORK/TORONTO – September 10, 2024 – Researchers at Klick Labs unveiled a cutting-edge, non-invasive technique that can predict chronic high blood pressure (hypertension) with a high degree of accuracy using just a person's voice. Just published in the peer-reviewed journal IEEE Access, the findings hold tremendous potential for advancing early detection of chronic high blood pressure and showcase yet another novel way to harness vocal biomarkers for better health outcomes.
The study’s 245 participants were asked to record their voices up to six times daily for two weeks by speaking into a proprietary mobile app, developed by the Klick scientists, which detected high blood pressure with accuracies up to 84 percent for females and 77 percent for males. The app uses machine learning to analyze hundreds of vocal biomarkers that are indiscernible to the human ear, including the variability in pitch (fundamental frequency), the patterns in speech energy distribution (Mel-frequency cepstral coefficients), and the sharpness of sound changes (spectral contrast).
“By leveraging various classifiers and establishing gender-based predictive models, we discovered a more accessible way to detect hypertension, which we hope will lead to earlier intervention for this widespread global health issue. Hypertension can lead to a number of complications, from heart attacks and kidney problems to dementia,” said Yan Fossat, senior vice president of Klick Labs and principal investigator of the study.
More Accessible Screening for the “Silent Killer”
The World Health Organization (WHO) refers to hypertension as the ‘‘silent killer,’’ as well as a global public health concern that affects over 25 percent of the global population. Half are unaware of their condition, and more than 75 percent of those diagnosed live in low- or middle-income countries.
Conventional methods of measuring blood pressure (and, accordingly, identifying hypertension) include using an arm cuff (sphygmomanometry) or an automatic blood pressure measurement device. However, these methods may require technical expertise, specialized equipment, and may not be readily accessible to people in underserved areas.
This study marks Klick Labs' first venture into using voice technology to identify conditions beyond diabetes, as the company expands its research to assess its AI algorithms’ effectiveness in detecting and managing a broader range of health conditions. Klick Labs has been collaborating with hospitals, academic institutions, and public health authorities worldwide since its research revealed that voice analysis combined with AI can accurately screen for Type 2 diabetes in Mayo Clinic Proceedings: Digital Health in October 2023). Last week, Scientific Reports published another Klick Labs' study confirming the link between blood glucose levels and voice pitch.
"Voice technology has the potential to exponentially transform healthcare, making it more accessible and affordable, especially for large, underserved populations,” said Jaycee Kaufman, Klick Labs research scientist and co-author of the study. "Our ongoing research increasingly demonstrates the significant promise of vocal biomarkers in detecting hypertension, diabetes, and a growing list of other health conditions.”
About Klick Applied Sciences (including Klick Labs)
Klick Applied Sciences’ diverse team of data scientists, engineers, and biological scientists conducts scientific research and develops AI/ML and software solutions as part of the company’s work to support commercial efforts using its proven business, scientific, medical, and technological expertise. In 2023, it announced groundbreaking research, published in Mayo Clinic Proceedings: Digital Health, around the AI model it created to detect Type 2 diabetes using 10 seconds of voice. Klick Applied Sciences is part of the Klick Group of companies, which also includes Klick Health (including Klick Katalyst and btwelve), Klick Media Group, Klick Consulting, Klick Ventures, and Sensei Labs. Established in 1997, Klick has offices in New York, Philadelphia, Toronto, London, São Paulo, and Singapore. Klick has consistently been ranked a Best Managed Company, Great Place to Work, Best Workplace for Women, Best Workplace for Inclusion, Best Workplace for Professional Services, and Most Admired Corporate Culture.
For more information, or a copy of the abstract, please contact Klick PR at pr@klick.com or 416-214-4977.
Journal
IEEE Access
Method of Research
Computational simulation/modeling
Subject of Research
People
Article Title
Machine Learning-enabled Hypertension Screening through Acoustical Speech Analysis: Model Development and Validation
Article Publication Date
4-Sep-2024
COI Statement
Behrad Taghibeyglou is a part-time employee, and Jaycee M. Kaufman and Yan Fossat are full-time employees of the source of funding for the study, Klick Inc.