Ellipsis and Ceras Partner on Voice Biomarker Technology
Ellipsis Health, a provider of artificial intelligence-generated voice biomarker technology, and Ceras Health, a provider of digital health solutions, have partnered to integrate Ellipsis Health's technology into Ceras' clinical monitoring and health data analytics platform, enabling real-time severity scores for anxiety and depression to improve care and triage patients in need.
"This new partnership will advance the state of mental health care, enabling Ellipsis Health to put its cutting-edge voice technology to work identifying people in need and then connecting them into integrated behavioral health services," said Mainul Mondal, founder and CEO of Ellipsis Health, in a statement. "We are proud to partner with Ceras Health, an organization that shares our commitment to using innovative technology to ensure that those in need have access to the right care at the right time, with the potential to transform how mental health care is identified, monitored, and delivered."
By harnessing the unique power of the human voice as a biomarker for mental well-being, along with machine learning and AI, Ellipsis Health identifies, measures, and monitors the severity of stress, anxiety, and depression at scale. Its technology analyzes short voice samples to create an objective and scalable clinical decision support tool.
"This unique partnership with Ellipsis Health aligns with Ceras Health's commitment to providing impactful care for our patients with chronic diseases and innovating how we deliver this care," said Udaya Devineni, CEO of Ceras, in a statement. "The ability to access mental healthcare has never been more important given these unprecedented times, especially for those patients who are also managing chronic diseases, and we are excited about the potential of providing patients with easy and direct access to mental health support."
The Menlo College pilot will use Ellipsis Health's technology to generate an assessment of anxiety and depression symptoms by analyzing student speech.