Human-machine collaboration using artificial intelligence to enhance the safety of donning and doffing personal protective equipment (PPE)

Abstract

Objectives: To compare the accuracy of monitoring personal protective equipment (PPE) donning and doffing process between an artificial intelligent (AI) machine collaborated with remote human buddy support system and an onsite buddy, and to determine the degree of AI autonomy at the current development stage.

Design and setting: We conducted a pilot simulation study with 30 procedural scenarios (15 donning and 15 doffing, performed by one individual) incorporating random errors in 55 steps. In total, 195 steps were assessed.

Methods: The human-AI machine system and the onsite buddy assessed the procedures independently. The human-AI machine system performed the assessment via a tablet device, which was positioned to allow full-body visualization of the donning and doffing person.

Results: The overall accuracy of PPE monitoring using the human-AI machine system was 100% and the overall accuracy of the onsite buddy was 99%. There was a very good agreement between the 2 methods (κ coefficient, 0.97). The current version of the AI technology was able to perform autonomously, without the remote human buddy's rectification in 173 (89%) of 195 steps. It identified 67.3% of all the errors independently.

Conclusions: This study provides preliminary evidence suggesting that a human-AI machine system may be able to serve as a substitute or enhancement to an onsite buddy performing the PPE monitoring task. It provides practical assistance using a combination of a computer mirror, visual prompts, and verbal commands. However, further studies are required to examine its clinical efficacy with a diverse range of individuals performing the donning and doffing procedures.