News Release 28-Aug-2024
Klick Labs’ latest findings highlight potential for voice-based blood sugar monitoring; discovery follows scientists’ pioneering work using vocal biomarkers and AI to detect Type 2 diabetes
Peer-Reviewed Publication
Klick Applied Sciences
NEW YORK/TORONTO – August 28, 2024 – As part of its ongoing exploration of vocal biomarkers and the role they can play in enhancing health outcomes, Klick Labs published a new study in Scientific Reports today – confirming the link between blood glucose levels and voice pitch and opening the door to future advancements in non-invasive glucose monitoring for people living with Type 2 diabetes.
In “Linear Effects of Glucose Levels on Voice Fundamental Frequency in Type 2 diabetes and Individuals with Normoglycemia,” researchers investigated how blood glucose levels influence the frequency of the voice in 505 participants across three glycemic statuses – non-diabetic, prediabetic, and Type-2 diabetic. Participants were fitted with continuous glucose monitors (CGMs) and recorded their voices multiple times daily for two weeks. The analysis revealed a linear relationship where an increase in CGM glucose levels corresponded to an increase in the fundamental frequency in the voice.
“By establishing a significant positive association between glucose levels and fundamental frequency, our study provides compelling justification for more research on using voice to predict and monitor glucose levels,” said Jaycee Kaufman, lead author and scientist at Klick Labs. “Whereas current glucose monitoring methods are often invasive and inconvenient, voice-based glucose monitoring could be as easy as talking into a smartphone, which could change the game for the estimated 463 million people around the world living with Type 2 diabetes.”
Klick Labs’ latest research marks another step forward in its ongoing commitment to revolutionizing the detection and management of diabetes using voice tech and machine learning. Their October 2023 study in Mayo Clinic Proceedings: Digital Health demonstrated that voice and AI can screen for Type 2 diabetes with high accuracy. Previously, their “Screening for Impaired Glucose Homeostasis: A Novel Metric of Glycemic Control” research also appeared in Mayo Clinic Proceedings: Digital Health (May 2023), and their “Homeostasis as a proportional–integral control system” study was published in Nature Digital Medicine (May 2020).
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 [email protected] or 416-214-4977.
Journal
Scientific Reports
DOI
10.1038/s41598-024-69620-z
Method of Research
Data/statistical analysis
Subject of Research
People
Article Title
Linear Effects of Glucose Levels on Voice Fundamental Frequency in Type 2 diabetes and Individuals with Normoglycemia
Article Publication Date
28-Aug-2024
COI Statement
Jaycee Kaufman, Jouhyun Jeon, Jessica Oreskovic and Yan Fossat are employees of Klick Inc., the source of funding for the project. Jouhyun Jeon and Yan Fossat are listed as inventors on patents corresponding to the prediction of glucose from voice (Systems and methods for generating models for determining blood glucose levels using voice, WO2022109714A1, and Systems, devices and methods for blood glucose monitoring using voice, WO2022109713A1).
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