Accurate Medical Vial Identification Through Mixed Reality: A HoloLens 2 Implementation.

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Electronics Pub Date : 2024-11-02 Epub Date: 2024-11-11 DOI:10.3390/electronics13224420
Bahar Uddin Mahmud, Guan Yue Hong, Afsana Sharmin, Zachary D Asher, John D Hoyle
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引用次数: 0

Abstract

The accurate identification of medicine vials is crucial for emergency medical services, especially for vials that resemble one another but have different labels, volumes, and concentrations. This study introduces a method to detect vials in real-time using mixed reality technology through Microsoft HoloLens 2. The system is also equipped with an SQL server to manage barcode and vial information. We conducted a comparative analysis of the barcode detection capabilities of the HoloLens 2 camera and an external scanner. The HoloLens 2 effectively identified larger barcodes when they were 20-25 cm away in normal lighting conditions. However, it faced difficulties in detecting smaller barcodes that were consistently detected by the external scanner. The frame rate investigation revealed performance fluctuations: an average of 10.54 frames per second (fps) under standard lighting conditions, decreasing to 10.10 fps in low light and further reducing to 10.05 fps when faced with high barcode density. Resolution tests demonstrated that a screen resolution of 1920 × 1080 yielded the best level of accuracy, with a precision rate of 98%. On the other hand, a resolution of 1280 × 720 achieved a good balance between accuracy 93% and speed. The HoloLens 2 demonstrates satisfactory performance under ideal circumstances; however, enhancements in detecting algorithms and camera resolution are required to accommodate diverse surroundings. This approach seeks to help paramedics make quick and accurate decisions during critical situations and tackle common obstacles such as reliance on networks and human mistakes. Our new approach of a hybrid method that integrates an external Bluetooth scanner with the MR device gives optimal results compared to the scanner-only approach.

通过混合现实准确识别医用小瓶:HoloLens 2实现。
准确识别药瓶对于紧急医疗服务至关重要,特别是对于那些彼此相似但标签、体积和浓度不同的药瓶。本研究介绍了一种利用微软HoloLens 2混合现实技术实时检测小瓶的方法。该系统还配备了一个SQL服务器来管理条形码和瓶信息。我们对HoloLens 2相机和外部扫描仪的条形码检测能力进行了比较分析。在正常照明条件下,HoloLens 2在20-25厘米外有效识别较大的条形码。然而,它在检测被外部扫描仪持续检测到的较小条形码时面临困难。帧率调查揭示了性能波动:在标准照明条件下平均每秒10.54帧(fps),在低光条件下下降到10.10帧/秒,在面对高条形码密度时进一步下降到10.05帧/秒。分辨率测试表明,1920 × 1080的屏幕分辨率产生了最佳的精度水平,准确率为98%。另一方面,1280 × 720的分辨率在93%的精度和速度之间取得了很好的平衡。HoloLens 2在理想情况下表现出令人满意的性能;然而,检测算法和相机分辨率的改进需要适应不同的环境。这种方法旨在帮助护理人员在危急情况下做出快速准确的决定,并解决依赖网络和人为错误等常见障碍。我们的新方法是一种混合方法,将外部蓝牙扫描仪与MR设备集成在一起,与仅使用扫描仪的方法相比,可以获得最佳结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Electronics
Electronics Computer Science-Computer Networks and Communications
CiteScore
1.10
自引率
10.30%
发文量
3515
审稿时长
16.71 days
期刊介绍: Electronics (ISSN 2079-9292; CODEN: ELECGJ) is an international, open access journal on the science of electronics and its applications published quarterly online by MDPI.
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