Zhang Peiming, Wang Zihe, Wang Tao, Liu Tielong, Wang Jing, Gao Yimeng, Li Weiqi
School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Department of Electrical Engineering, Shandong Vocational College of Industry, Zibo, 256414, People's Republic of China.
Med Devices (Auckl). 2025 Aug 22;18:427-445. doi: 10.2147/MDER.S541187. eCollection 2025.
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.
增强现实头戴式设备（AR HMD）在医疗保健领域的应用越来越广泛。鉴于医疗环境对安全性和有效性的严格要求，在部署前对关键性能属性进行主动定量测试对于风险评估至关重要。一个系统的性能评估框架不仅对于支持临床应用至关重要，而且对于获得监管批准也必不可少。本综述系统地总结了医疗保健领域中AR HMD的硬件、软件和可用性评估方法，分析了当前的研究和实验设计，并指出了因设备异质性、与现实世界临床场景的有限耦合以及主观偏差而产生的挑战。为了解决这些问题，我们提出了五条设计原则，以指导客观实用的评估方法的开发：（1）基于核心功能识别关键组件；（2）按功能贡献对测试进行优先级排序；（3）复制真实的临床和人类视觉条件；（4）使主观感知客观化；（5）联合测试功能相关组件。
