Voice to Diabetes tool leverages vocal biomarker data to diagnose Type 2 diabetes based on the analysis of a person's voice. This innovation harnesses AI and machine learning techniques to detect subtle vocal changes that are imperceptible to the human ear. By incorporating features like pitch and intensity changes, the tool successfully distinguishes between individuals with and without Type 2 diabetes.

Ethic approval for the study was granted by Saanvi Ethical Research LLP on March 31 2021 and from Jasleen Hospital Ethics Committee on May 07, 2021

The clinical study was registered with the CTRI as Number /2021/08/035957

India is home to the second-largest number of diabetes patients in the world. Despite the staggering number of diabetes cases, more than half remain undiagnosed due to various factors including distance, cost, and lack of resources. India’s vast geographical expanse and uneven distribution of healthcare facilities make accessing diagnostic tests challenging for millions, especially in rural areas. The cost of healthcare, including blood tests, can be prohibitive for many Indians, leading to delayed or neglected health concerns. However, over a billion people living in India have mobile phones. With Voice to Diabetes, the widespread use of mobile phones across socioeconomic strata can now be leveraged to address healthcare disparities and save lives.

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The target audiences are healthcare professionals and patients.

India ranks second globally in diabetes cases, with over half remaining undiagnosed due to barriers like distance, cost, and lack of resources. Leveraging the widespread use of mobile phones among over a billion Indian citizens, Voice to Diabetes addresses healthcare disparities and gender equality concerns. This innovative AI tool screens for Type 2 diabetes through voice analysis, offering a non-invasive alternative to traditional blood tests. The study, featured in a Mayo Clinic journal, involved 267 Indian participants. Using a smartphone app, participants recorded voice clips over two weeks, leading to the identification of 14 key acoustic characteristics. For women, pitch changes were vital, while for men, variations in voice strength mattered. Achieving up to 89% accuracy for women and 86% for men, this approach promises a cost-effective and accessible diabetes screening solution, potentially transforming healthcare access in India.

India ranks second globally in diabetes cases, with over half remaining undiagnosed due to barriers like distance, cost, and lack of resources. Leveraging the widespread use of mobile phones among over a billion Indians, Voice to Diabetes addresses healthcare disparities and gender equality concerns. This innovative AI tool screens for Type 2 diabetes through voice analysis, offering a non-invasive alternative to traditional blood tests.

India ranks second globally in diabetes cases, with over half remaining undiagnosed due to barriers like distance, cost, and lack of resources. Leveraging the widespread use of mobile phones among over a billion Indian citizens, Voice to Diabetes addresses healthcare disparities and gender equality concerns. This innovative AI tool screens for Type 2 diabetes through voice analysis, offering a non-invasive alternative to traditional blood tests. The study, featured in a Mayo Clinic journal, involved 267 Indian participants. Using a smartphone app, participants recorded voice clips over two weeks, leading to the identification of 14 key acoustic characteristics. For women, pitch changes were vital, while for men, variations in voice strength mattered. Achieving up to 89% accuracy for women and 86% for men, this approach promises a cost-effective and accessible diabetes screening solution, potentially transforming healthcare access in India.

The Voice to Diabetes system is a mobile phone app designed to identify Type 2 diabetes by just speaking into the phone. It is very simple to use. It displays a sentence on screen for the user to read out loud. The sentence is “Hello how are you, what is my glucose level right now?” The app then runs an analysis of the acoustic properties of the voice sample using a predictive model that was pre-trained on thousands of voice recordings to detect features that are associated with diabetes. The system doesn't comprehend what people say or what accent they have; it listens to lower-level features, such as minute amplitude or frequency modulation of the fundamental frequency of the voice. This analysis takes a few seconds. Once completed, the system shows a risk score of this person having Type 2 diabetes.

With almost one in two, or 240 million adults living with diabetes worldwide unaware they have the condition, and the potential to save $32.75 billion globally, Voice to Diabetes is already changing the diagnostic landscape as we know it. And with hospital partnerships around the world, and 7 different studies currently underway to extend these results in other disease states, the applications coming soon are endless.

Voice to Diabetes generated over 4 billion earned press impressions, including more than 200 broadcast segments. It was covered in more than 65 countries worldwide, including the U.S. Canada, the UK, Japan, China, Germany, France, and Brazil. The week the news hit, the website saw a 50% spike in traffic.