RE’AYA: A Kuwaiti AI-Driven Robotic Diagnostic Nurse

Abstract

This study presents RE’AYA, an AI-enabled robotic diagnostic system developed to assist with triage operations in healthcare settings. The system was designed in response to workforce constraints affecting frontline services, particularly in high-volume environments such as emergency departments. RE’AYA integrates facial recognition, physiological sensing, and real-time data processing to perform preliminary assessments, including the measurement of body temperature, blood pressure, heart rate, oxygen saturation, blood glucose level, weight, and height. It also collects patient identification and symptom data to support triage prioritization. The system was evaluated in a controlled environment using simulated patient interactions. Results showed a reduction in average triage waiting time by more than 50 percent compared to manual triage processing, with sensor outputs remaining within clinically acceptable accuracy thresholds. Facial recognition performance was robust across varied lighting and occlusion conditions. Usability testing indicated high satisfaction among both patient participants and healthcare professionals. These findings suggest that RE’AYA may contribute to improving triage efficiency and supporting clinical staff in resource-constrained environments. Further validation is required in real-world settings to assess long-term performance, ethical implications, and system scalability.

Ähnliche Arbeiten