AR-AI assisted ophthalmic nursing: Preliminary usability study in clinical settings

Area of Science:

• Ophthalmic Nursing
• Health Informatics
• Artificial Intelligence

Background:

• Ophthalmic ward nursing is demanding, prompting research into AI-assisted solutions.
• Existing systems may not fully meet the needs of busy ophthalmic nurses.

Purpose of the Study:

• To develop and evaluate an intelligent assistant system for ophthalmic ward nurses using augmented reality (AR) and artificial intelligence (AI).
• To assess the usability and acceptability of the AR-based intelligent assistance system (AR-IAS) in clinical settings.

Main Methods:

• Developed an AR-based intelligent assistance system (AR-IAS) integrating deep learning, acoustic recognition, voice interaction, and image recognition.
• Incorporated patient face recognition, automatic information matching, and nursing work management functionalities.
• Evaluated usability via the System Usability Scale (SUS) comparing AR-IAS against a personal digital assistant (PDA) system.

Main Results:

• The AR-IAS achieved an overall usability score of 75.83/100.
• Comparative analysis showed AR-IAS scored higher in learnability (22.50/30) and efficiency (29.67/40) than the PDA system.
• Satisfaction scores were comparable, with AR-IAS at 23.67/30 and PDA at 23.17/30.

Conclusions:

• The AR-IAS demonstrates good overall usability and clinical acceptability among ophthalmic nurses.
• The system is suitable for ophthalmic nursing tasks and holds potential for clinical adoption and further research.
• AR and AI technologies offer a promising avenue for enhancing nursing efficiency and patient care in specialized wards.