Sovrinti continues to improve predictive care performance through new Johns Hopkins study
WACO, TX, UNITED STATES, July 2024 — Waco based Sovrinti Inc. has been awarded a follow-on research grant for the development of Artificial Intelligence (AI) techniques that predict adverse health events in senior populations using Sovrinti’s in-home sensing data. The award was made by the Johns Hopkins AI & Technology Collaboratory for Aging Research (JH AITC), one of three research centers within the Artificial Intelligence and Technology Collaboratory (AITC) for Aging Research funded by the National Institute on Aging, part of the National Institutes of Health. This Sovrinti project is part of an ongoing research program at Johns Hopkins “Utilizing Technology and AI approaches to Facilitate Independence and Resilience in Older Adults”. This particular program will continue to advance the Sovrinti predictive models by optimizing performance and minimizing required home sensors while still demonstrating the ability to predict acute incidents for older adults up to two weeks before an occurrence.
The Sovrinti system uses a patented set of home sensors to identify Activities of Daily Living (ADLs) and look for changes from individual routines. Subtle changes in behavior patterns are mapped to cognitive and physiological relevant criteria allowing early identification of rising risk for acute events. Without any additional effort from the older adult or caregiver, the Sovrinti system uses the power of smart home devices and data analytics to identify specific areas requiring care team attention before a health situation becomes acute and costly.
“We have already validated the ability of the system to improve on existing care standards and predict acute health events. The goal of this new project is to demonstrate an optimal solution which helps us continue to reduce cost and complexity while maintaining predictive accuracy. By continuing to improve on the efficiency of our system, we will be able to ensure broad access for older adults and their families. For those of us that have dealt with constantly reacting to parents changing health needs, we look forward to helping families get ahead of issues before they become acute. ” says John Fitch, Sovrinti Principal and CEO. “We continue to enjoy working with Johns Hopkins on both the technical and business development side of this project as they provide a world class support in moving this technology into the mainstream of senior care health management.”
Previous efforts have demonstrated the ability of the Sovrinti system to provide continuous ADL monitoring and assessment as well as predict acute health events with greater than 90% accuracy up to two weeks in advance. Details of these studies as well as in depth case studies of specific events are available on the sovrinti.com website.
Funds to support this AITC study were provided by the Johns Hopkins University AITC under award number P30AG073104. Research described in this announcement was supported by National Institute on Aging grants P30AG073104 and R44AG065118B. The content is solely the responsibility of the authors and does not necessarily represent the views of the National Institutes of Health.
For more information visit https://www.sovrinti.com or https://www.a2collective.ai/.