Machine-learning algorithm can predict a hot flash before a person perceives it

When combined with Embr Labs' patented wearable device, Embr Wave, immediate cooling is delivered to mitigate or fully alleviate the event. This first-of-its-kind predictive algorithm is the result of machine learning being applied to the largest data set of digital biomarkers forever collected, which was generated by researchers at UMass Amherst's Center for Human Health and Performance.

Unlike previous attempts to combat hot flashes, this is a non-pharmaceutical approach. The current generation of the Embr Wave is worn on the inside of the wearer's wrist and heats or cools at the touch of a button to elicit a brain and body response that can help with resolving hot flashes, improving sleep and relieving stress. The new predictive sensor technology will be commercialized in an upcoming generation of Embr Wave.

Instead, Busa describes the new system as a"reactive digital drug" for hot flash symptoms."The solution is not quite so simple as hot plus cold equals neutral," he explains."In this case, we leverage early physiological changes that precede a person's perception of an oncoming hot flash and provide early relief that aims to automatically deploy an intervention tailored to minimize the disturbance of the hot flash symptoms.

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