DiverNet -一个用于实时潜水员可视化的惯性传感器网络

G. Goodfellow, J. Neasham, Ivor Rendulic, D. Nad, N. Mišković
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引用次数: 8

摘要

本文介绍了DiverNet系统,该系统可以实时重建潜水员的姿势,并使用虚拟三维模型将其可视化。DiverNet是一个由17个安装在潜水员身体上的惯性传感器组成的网络,可以计算每个身体部位的方向。根据获得的数据,潜水员的姿势可以可视化。除此之外,DiverNet还可以集成额外的传感器来测量呼吸频率等生理参数。这是首次在水下使用这种技术。获得的数据将用于通过实时监控潜水员来提高潜水员的安全性,以及开发工具来了解潜水员的行为并自动识别可能出现的问题迹象。本文重点介绍了所开发系统的技术描述,以及用于数据分析和可视化的软件。
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DiverNet — A network of inertial sensors for real time diver visualization
This paper describes the DiverNet system that allows real time reconstruction of diver's posture and its visualization using a virtual 3D model. DiverNet is a network consisting of 17 inertial sensors mounted on diver's body, enabling calculation of orientation of each body part. Based on the obtained data, diver posture can be visualized. In addition to that, DiverNet allows integration of additional sensors for measuring physiological parameters such as breathing rate. This is the first time such technology is used in the underwater. Obtained data will be used to increase diver safety by monitoring the diver in real time, as well as developing tools for understanding diver behaviour and automatically recognizing possible signs of trouble. The paper focuses on technical description of the developed system, as well as the software used for data analysis and visualization.
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