Stock.adobe.com Movano Health announced that it has added deep learning to its AI-powered heart rate monitoring algorithm. 1 This has reportedly increased the accuracy of the algorithm, which is used in wearable devices. In a new study, the results showed that the improved algorithm produced consistent results in a variety of activities.
In a press release, Movano Health’s CTO Michael Leabman said, “Utilizing deep learning is significantly better than standard techniques as it is the optimal solution for removing the effects of motion, eliminating the noise and motion artifacts in the optical signal. We believe that this is a first of its kind implementation and an innovation that has the potential to enhance the reliability of wearable health monitors, providing users with more accurate and consistent heart rate measurements."
The improved algorithm was tested using the Evie Ring. The study showed that it was more accurately able to filter out motion artifacts and enhance the signal-to-noise- ratio.
Movano Health is a key player in the health monitoring sector. Earlier this month, MIT announced that it had selected Movano to be its partner for a study of the lasting impacts of long COVID and chronic Lyme disease. 2 For the study, the Evie Ring was once again selected to monitor patient stats.
In a press release, Movano Health CEO John Mastrototaro said, “This collaboration signals a vote of confidence from one of the world’s preeminent research institutions in Movano’s ability to provide continuous, reliable, and convenient access to a large data set, ushering in a new era of personalized patient care and scientific discovery. Our ring solution, designed to meet stringent HIPAA and cybersecurity standards, offers an innovative alternative to existing health monitoring devices–a game-changing solution that is long overdue."
In the same press release, MIT’s Center for Gynepathology Research’s associate scientific director Dr. Michal Caspi Tal said, “We’re excited to incorporate the Evie Ring into our clinical study to evaluate the progression of long COVID and chronic Lyme disease and paint a fuller picture of why some people bounce back from a mild infection while others go on to endure prolonged suffering. The breadth […]
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