Reveal Clinical Insights with Embedded AI

Augmented Observation

Utilize powerful computer vision technology that analyzes live video streams of patients and their environment. Detect movement and changes that could lead to adverse events such as falls or self-harm and observe visitor activity and staff visits.

Seamlessly monitor for patient safety factors, including:

• Patient fall and elopement warning signs
• Patient self-harm
• Patient position in bed
• Head of bed, bed height, and rail position

Drive operational efficiency by using computer vision resources to remotely track and optimize staff coverage, bed turnover, and medical equipment deployment.

Vitals Trending

Leverage radar-based sensors to provide continuous, contactless monitoring of key patient vital signs like heart and respiratory rates, as well as patient movement to trend changes over time. Care teams are notified about changes in patient conditions that might signal deterioration or indicate the patient is waking from sedation or sleep. Embedded machine learning models deliver patient-specific smart clinical alerts to reduce alarm fatigue for clinicians so they can better focus on patient care.

• Continuously monitor vitals to trend patient health factors over time
• Quickly identify patient deterioration to accelerate clinical intervention
• Receive smart clinical notifications based on individual patient factors and baselines