The SeVA platform is a composite AI device that can be effectively deployed in hospital, nursing homes and home settings. It has the capability to track a patient’s mental and physical state and signal early signs of risks such as delirium, falls or impending illness. It provides emotional support to the patient and their family by indulging in a natural conversation and facilitating their needs. When fully deployed, the product can serve as a platform which allays worry for people and their caregivers and will reduce healthcare costs by identifying the early signs of severe illness.

The fall detection system runs on built-in instability metrics that assess the fall precursors and assist users in correcting posture and regaining balance. Using a stream of data from multiple cameras, our algorithm calculates, in real-time, several posture metrics for identifying potential falls. It then provides individualized posture correction feedback using both audio and a wearable haptic device or can trigger wearable robotics for fall protection.

UArizona researchers have created an AI powered data-driven tool to forecast a personalized due date window for expectant mothers utilizing data from commonly worn personal devices like smart rings at various periods in gestation.