Information Engineering Department, University of Pisa, 56126 Pisa, Italy.
Maxillofacial Surgery Unit, Department of Biomedical and Neuromotor Sciences and S. Orsola-Malpighi Hospital, Alma Mater Studiorum University of Bologna, 40138 Bologna, Italy.
Sensors (Basel). 2020 Mar 13;20(6):1612. doi: 10.3390/s20061612.
Augmented reality (AR) Head-Mounted Displays (HMDs) are emerging as the most efficient output medium to support manual tasks performed under direct vision. Despite that, technological and human-factor limitations still hinder their routine use for aiding high-precision manual tasks in the peripersonal space. To overcome such limitations, in this work, we show the results of a user study aimed to validate qualitatively and quantitatively a recently developed AR platform specifically conceived for guiding complex 3D trajectory tracing tasks. The AR platform comprises a new-concept AR video see-through (VST) HMD and a dedicated software framework for the effective deployment of the AR application. In the experiments, the subjects were asked to perform 3D trajectory tracing tasks on 3D-printed replica of planar structures or more elaborated bony anatomies. The accuracy of the trajectories traced by the subjects was evaluated by using templates designed ad hoc to match the surface of the phantoms. The quantitative results suggest that the AR platform could be used to guide high-precision tasks: on average more than 94% of the traced trajectories stayed within an error margin lower than 1 mm. The results confirm that the proposed AR platform will boost the profitable adoption of AR HMDs to guide high precision manual tasks in the peripersonal space.
增强现实 (AR) 头戴式显示器 (HMD) 作为支持直接视觉下执行的手动任务的最有效输出媒介正在出现。尽管如此,技术和人为因素的限制仍然阻碍了它们在辅助近体空间高精度手动任务中的常规使用。为了克服这些限制,在这项工作中,我们展示了一项用户研究的结果,该研究旨在定性和定量地验证一种专门为指导复杂 3D 轨迹跟踪任务而开发的新型 AR 平台。该 AR 平台包括一种新概念的 AR 视频透视 (VST) HMD 和一个专用软件框架,用于有效部署 AR 应用程序。在实验中,要求受试者在平面结构或更精细的骨骼解剖结构的 3D 打印复制品上执行 3D 轨迹跟踪任务。使用专门设计的模板来匹配模型的表面,评估受试者跟踪的轨迹的准确性。定量结果表明,该 AR 平台可用于指导高精度任务:平均而言,超过 94%的跟踪轨迹保持在误差小于 1 毫米的范围内。研究结果证实,所提出的 AR 平台将促进对 AR HMD 的有利采用,以指导近体空间中的高精度手动任务。
Sensors (Basel). 2020-3-13
Ann Biomed Eng. 2021-9
IEEE Trans Vis Comput Graph. 2022-7
IEEE J Biomed Health Inform. 2022-2
Comput Assist Surg (Abingdon). 2017-12
IEEE Trans Biomed Eng. 2019-5-6
IEEE Trans Vis Comput Graph. 2024-7
Int J Comput Assist Radiol Surg. 2024-10
IEEE Trans Vis Comput Graph. 2024-7
Int J Comput Assist Radiol Surg. 2020-11
Front Bioeng Biotechnol. 2023-11-22
Int J Environ Res Public Health. 2022-5-23
Int J Environ Res Public Health. 2022-1-18
Bioengineering (Basel). 2021-9-25
Int J Environ Res Public Health. 2021-9-22
IEEE J Biomed Health Inform. 2020-7
IEEE Trans Biomed Eng. 2019-5-6
IEEE Trans Vis Comput Graph. 2018-5-3
Sensors (Basel). 2018-6-2
J Healthc Eng. 2017-8-21
IEEE Trans Vis Comput Graph. 2018-9
Comput Assist Surg (Abingdon). 2017-12
IEEE Trans Med Imaging. 2014-10-2