Da Gama Alana Elza Fontes, Chaves Thiago Menezes, Figueiredo Lucas Silva, Baltar Adriana, Meng Ma, Navab Nassir, Teichrieb Veronica, Fallavollita Pascal
Informatics Center, Federal University of Pernambuco, Recife, Brazil; Faculty of Informatics, Technical University of Munich, Germany.
Informatics Center, Federal University of Pernambuco, Recife, Brazil.
Comput Methods Programs Biomed. 2016 Oct;135:105-14. doi: 10.1016/j.cmpb.2016.07.014. Epub 2016 Jul 9.
Interactive systems for rehabilitation have been widely investigated for motivational purposes. However, more attention should be given to the manner in which user movements are recognized and categorized. This paper aims to evaluate the efficacy of using a clinically-related gesture recognition tool, based on the international biomechanical standards (ISB) for the reporting of human joint motion, for the development of an interactive augmented reality (AR) rehabilitation system -mirrARbilitation.
This work presents an AR rehabilitation system based on ISB standards, which enables the system to interact and to be configured according to therapeutic needs. The Kinect(TM) skeleton tracking technology was exploited and a new movement recognition method was developed to recognize and classify biomechanical movements. Further, our mirrARbilitation system provides exercise instructions while simultaneously motivating the patient. The system was evaluated on a cohort of 33 patients, physiotherapists, and software developers when performing shoulder abduction therapy exercises. Tests were performed in three moments: (i) users performed the exercise until they feel tired without the help of the system, (ii) the same however using the mirrARbilitation for motivation and guidance, and (iii) users performed the exercise again without the system. Users performing the movement without the help of the system worked as baseline reference.
We demonstrated that the percentage of correct exercises, measured by the movement analysis method we developed, improved from 69.02% to 93.73% when users interacted with the mirrARbilitation. The number of exercise repetitions also improved from 34.06 to 66.09 signifying that our system increased motivation of the users. The system also prevented the users from performing the exercises in a completely wrong manner. Finally, with the help of our system the users' worst result was performing 73.68% of the rehabilitation movements correctly. Besides the engagement, these results suggest that the use of biomechanical standards to recognize movements is valuable in guiding users during rehabilitation exercises.
The proposed system proved to be efficient by improving the user engagement and exercise performance outcomes. The results also suggest that the use of biomechanical standards to recognize movements is valuable in guiding users during rehabilitation exercises.
为了激发积极性,人们对交互式康复系统进行了广泛研究。然而,对于用户动作的识别和分类方式应给予更多关注。本文旨在评估一种基于国际生物力学标准(ISB)报告人体关节运动的临床相关手势识别工具,用于开发交互式增强现实(AR)康复系统——mirrARbilitation的效果。
这项工作提出了一种基于ISB标准的AR康复系统,该系统能够根据治疗需求进行交互和配置。利用了Kinect(TM)骨骼跟踪技术,并开发了一种新的运动识别方法来识别和分类生物力学运动。此外,我们的mirrARbilitation系统在为患者提供锻炼指导的同时,还能激发患者的积极性。该系统在33名患者、物理治疗师和软件开发人员进行肩部外展治疗锻炼时进行了评估。测试在三个阶段进行:(i)用户在没有系统帮助的情况下进行锻炼,直到感到疲劳;(ii)同样进行锻炼,但使用mirrARbilitation进行激励和指导;(iii)用户再次在没有系统的情况下进行锻炼。在没有系统帮助下进行运动的用户作为基线参考。
我们证明,当用户与mirrARbilitation交互时,通过我们开发的运动分析方法测量的正确锻炼百分比从69.02%提高到了93.73%。锻炼重复次数也从34.06次增加到了66.09次,这表明我们的系统提高了用户的积极性。该系统还防止用户以完全错误的方式进行锻炼。最后,在我们系统的帮助下,用户最差的结果是正确完成73.68%的康复动作。除了参与度之外,这些结果表明,使用生物力学标准来识别运动在康复锻炼中指导用户是有价值的。
所提出的系统通过提高用户参与度和锻炼表现结果证明是有效的。结果还表明,使用生物力学标准来识别运动在康复锻炼中指导用户是有价值的。