Evidence map›Paper›PMID 40873666›Full record

ReviewMedical devices (Auckland, N.Z.)2025

Evaluating Augmented Reality Head-Mounted Devices in Healthcare: A Review of Hardware, Software, and Usability Approaches.

Peiming Zhang, Zihe Wang, Tao Wang, Tielong Liu, Jing Wang, Yimeng Gao, Weiqi Li

Abstract readReview
In one paragraph

Review in Medical devices (Auckland, N.Z.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Peiming ZhangSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Zihe WangSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Tao WangDepartment of Electrical Engineering, Shandong Vocational College of Industry, Zibo, 256414, People's Republic of China.
Tielong LiuDepartment of Orthopedics, Changzheng Hospital, Naval Medical University, Shanghai, 200003, People's Republic of China.
Jing WangDepartment of Orthopedics, Changzheng Hospital, Naval Medical University, Shanghai, 200003, People's Republic of China.
Yimeng GaoSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Weiqi LiSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

augmented realityhead-mounted displayperformance evaluationusability assessmentvisual perception

Identifiers

PMID40873666
PMCPMC12380000

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.