Peiming Zhang,1 Zihe Wang,1 Tao Wang,2 Tielong Liu,3 Jing Wang,3 Yimeng Gao,1 Weiqi Li1 

1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People’s Republic of China; 2Department of Electrical Engineering, Shandong Vocational College of Industry, Zibo, 256414, People’s Republic of China; 3Department of Orthopedics, Changzheng Hospital, Naval Medical University, Shanghai, 200003, People’s Republic of China

Correspondence: Peiming Zhang, University of Shanghai for Science and Technology, No. 516, Jungong Road, Yangpu District, Shanghai, People’s Republic of China, Email zpmking@163.com

Abstract: Augmented reality head-mounted devices (AR HMDs) are increasingly deployed in healthcare. Given the stringent safety and efficacy requirements of medical settings, proactive quantitative testing of key performance attributes prior to deployment is critical for risk assessment. A systematic performance evaluation framework is essential not only to support clinical adoption but also to secure regulatory approval. This review systematically summarizes hardware, software, and usability assessment methods for AR HMDs in healthcare, analyzes current research and experimental designs, and identifies challenges arising from device heterogeneity, limited coupling with real-world clinical scenarios, and subjective bias. To address these issues, we propose five design principles to guide the development of objective and practical evaluation methods: (1) identify key components based on core functions; (2) prioritize testing by functional contribution; (3) replicate authentic clinical and human-visual conditions; (4) objectify subjective perception; (5) test functionally linked components jointly.

Keywords: augmented reality, head-mounted display, performance evaluation, usability assessment, visual perception