CarePredict Wearable Tracks Seniors’ Behavior, Wellness
CarePredict has announced the launch of the third generation of their smart wearable – CarePredict Tempo™ Series 3. The Tempo uses an array of sensors, indoor location data, machine learning, and sophisticated gesture recognition algorithms to learn an individual’s activity and behavior patterns and predict the probability of health declines well in advance.
The earliest signs of health decline in seniors appear as subtle changes in daily activity and behavior patterns. There is an over-reliance on human observation when it comes to detecting these changes. Tempo augments human observation with machine sensing and learning by continuously observing and alerting on the changes in activities of daily living (ADLs) like eating, cooking, walking, sleeping, showering, and toileting.
“Almost all wearables in the market today detect just steps, sleep or some physiological measurements,” said Satish Movva, CEO and Founder, CarePredict. “But when it comes to senior care, changes in activity and behavior patterns are the new vital signs as they foreshadow declines in health and are more important than just physiological measurements. CarePredict’s Tempo wearables enable professional and family caregivers to shift from the old paradigm of Detect and Treat based on physiological measurements to the new world of “Predict and Prevent” based on changes in activity and behavior patterns.”
The latest generation of Tempo has sophisticated sensors including a highly advanced motion sensor for gesture recognition and a combined heart rate and pulse oximetry sensor using best in class technology. Like its predecessor, Tempo Series 3 uses CarePredict’s proprietary two-way voice technology that allows seniors to communicate with their caregivers, near and far, directly through their wrist-worn wearable. Along with CarePredict’s Context beacons, it provides room-level location accuracy and location-based insights and is integrated with RFID for electronic door access.