Purpose: To evaluate manual and automatic registration times as well as accuracy with augmented reality during alignment of a holographic 3-dimensional (3D) model onto the real-world environment. Method: 18 participants in various stages of clinical training across two academic centers registered a 3D CT phantom model onto a CT grid using the HoloLens 2 augmented reality headset 3 consecutive times. Registration times and accuracy were compared among different registration methods (hand gesture, Xbox controller, and automatic registration), levels of clinical experience, and consecutive attempts. Registration times were also compared with prior HoloLens 1 data. Results: Mean aggregate manual registration times were 27.7, 24.3, and 72.8 seconds for one-handed gesture, two-handed gesture, and Xbox controller, respectively; mean automatic registration time was 5.3s (ANOVA p<0.0001). No significant difference in registration times was found among attendings, residents and fellows, and medical students (p>0.05). Significant improvements in registration times were detected across consecutive attempts using hand gestures (p<0.01). Compared with previously reported HoloLens 1 experience, hand gesture registration times were 81.7% faster (p<0.05). Registration accuracies were not significantly different across manual registration methods, measuring at 5.9, 9.5, and 8.6 mm with one-handed gesture, two-handed gesture, and Xbox controller, respectively (p>0.05). Conclusions: Manual registration times decreased significantly with updated hand gesture maneuvers on HoloLens 2 versus HoloLens 1, approaching the registration times of automatic registration and outperforming Xbox controller mediated registration. These results will encourage wider clinical integration of HoloLens 2 in procedural medical care.
翻译:目的:评估手动和自动登记时间以及准确度,在将全息三维(3D)模式与现实环境接轨期间,将全息三维(3D)模式与真实世界环境接轨,以扩大实际情况。方法:两个学术中心不同阶段临床培训的18名参与者分别用HoloLens 2 连续三次在CT网格上登记了3DCT假象模型(ANOVA p < 0.001),对不同的登记方法(手势、Xbox控制器和自动登记)、临床经验水平和连续尝试进行比较。与以前报告的HoloLens 1 数据相比,登记时间也有很大改进。结果:平均手工登记时间为27.7、24.3和72.8秒,单手手手手手手手手手手手手动作、手势手势手势和Xbox控制器分别登记了3DCTCT CT CT 3 (NOVA p < 000) 平均登记时间为5.3、居民和研究员之间登记时间差异登记时间(P>0.05) 手势的登记时间和手势上手势的登记时间将大大改进的登记时间比前手势(P)。