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利用Shimmer传感器和微软Kinect传感器开发运动识别应用程序。

Developing movement recognition application with the use of Shimmer sensor and Microsoft Kinect sensor.

作者信息

Guzsvinecz Tibor, Szucs Veronika, Sik Lányi Cecília

出版信息

Stud Health Technol Inform. 2015;217:767-72.

Abstract

Nowadays the development of virtual reality-based application is one of the most dynamically growing areas. These applications have a wide user base, more and more devices which are providing several kinds of user interactions and are available on the market. In the applications where the not-handheld devices are not necessary, the potential is that these can be used in educational, entertainment and rehabilitation applications. The purpose of this paper is to examine the precision and the efficiency of the not-handheld devices with user interaction in the virtual reality-based applications. The first task of the developed application is to support the rehabilitation process of stroke patients in their homes. A newly developed application will be introduced in this paper, which uses the two popular devices, the Shimmer sensor and the Microsoft Kinect sensor. To identify and to validate the actions of the user these sensors are working together in parallel mode. For the problem solving, the application is available to record an educational pattern, and then the software compares this pattern to the action of the user. The goal of the current research is to examine the extent of the difference in the recognition of the gestures, how precisely the two sensors are identifying the predefined actions. This could affect the rehabilitation process of the stroke patients and influence the efficiency of the rehabilitation. This application was developed in C# programming language and uses the original Shimmer connecting application as a base. During the working of this application it is possible to teach five-five different movements with the use of the Shimmer and the Microsoft Kinect sensors. The application can recognize these actions at any later time. This application uses a file-based database and the runtime memory of the application to store the saved data in order to reach the actions easier. The conclusion is that much more precise data were collected from the Microsoft Kinect sensor than the Shimmer sensors.

摘要

如今,基于虚拟现实的应用开发是发展最为迅猛的领域之一。这些应用拥有广泛的用户群体,市场上越来越多的设备能够提供多种用户交互方式。在无需手持设备的应用场景中,其潜力在于可用于教育、娱乐和康复应用。本文旨在研究虚拟现实应用中无需手持设备的用户交互的精度和效率。所开发应用的首要任务是支持中风患者在家中的康复过程。本文将介绍一款新开发的应用,它使用了两种流行的设备,即Shimmer传感器和微软Kinect传感器。为识别和验证用户的动作,这些传感器以并行模式协同工作。为解决问题,该应用可记录一种教育模式,然后软件将此模式与用户的动作进行比较。当前研究的目标是考察手势识别的差异程度,以及这两种传感器识别预定义动作的精确程度。这可能会影响中风患者的康复过程并影响康复效率。此应用是用C#编程语言开发的,并以原始的Shimmer连接应用为基础。在该应用运行期间,使用Shimmer和微软Kinect传感器可以教授五五不同的动作。该应用可在之后的任何时间识别这些动作。此应用使用基于文件的数据库和应用的运行时内存来存储保存的数据,以便更轻松地实现这些动作。结论是,从微软Kinect传感器收集到的数据比Shimmer传感器的数据精确得多。

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