Researchers have developed an innovative approach to managing menopausal hot flashes using artificial intelligence (AI) combined with wearable technology. Hot flashes, experienced by approximately 75% of menopausal women, are sudden increases in body temperature that can significantly impact daily life.
The team, led by Dr. Michael Busa from the University of Massachusetts Amherst, created a machine learning algorithm capable of predicting hot flashes by monitoring physiological signals such as skin temperature, body temperature, sweating, activity level, and heart rate. This algorithm is integrated with Embr Wave, a wearable device developed by Embr Labs, which emits cooling or warming sensations on the wrist to provide whole-body relief. Priced at $299, the Embr Wave device offers a non-hormonal option for managing hot flashes.
When the algorithm detects early signs of an impending hot flash, it prompts the Embr Wave device to activate cooling within less than a second, potentially stopping the hot flash or alleviating its intensity. This proactive approach offers a promising alternative to traditional hormone therapies, which some women may wish to avoid due to personal preference or medical reasons.
Dr. Karen Adams, an OB/GYN and director of the Menopause and Healthy Aging Program at Stanford University, commented on the significance of non-hormonal treatments for hot flashes. She noted that while hormone therapy is effective, it may not be suitable for all women, making alternative options like this AI-driven wearable particularly valuable.
This development represents a significant advancement in menopausal care, combining AI and wearable technology to offer a personalized and non-hormonal solution to hot flashes.
