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An open vibration and pressure platform for fall prevention with a reinforcement learning agent
Personal and Ubiquitous Computing Pub Date : 2020-05-26 , DOI: 10.1007/s00779-020-01416-0
Virgile Lafontaine , Patrick Lapointe , Kevin Bouchard , Jean-Michel Gagnon , Mathieu Dallaire , Sébastien Gaboury , Rubens A. da Silva , Louis-David Beaulieu

The risk of falls among the elderly population is one that may lead to dire consequences. It can significantly affect the quality of life of the victims and even lead to their premature death. Many technological tools have been proposed in the literature to detect falls, but little effort has been done regarding their prevention. In this paper, our research team proposes an inexpensive open vibration platform equipped with pressure sensors. The platform is built from easily available electronic components to be used as a tool by physiotherapists in order to help them in their evaluation of the postural control of individuals at risk of postural imbalance. The platform has been built to be easily reproducible by the scientific community. Moreover, the computer code necessary to make it work is fully open source and can be used in any non-commercial applications. A first version of the platform was tested with 7 healthy human participants. A simple reinforcement learning agent was deployed and tested to automatically calibrate the vibration motors for optimal stimulation. The agent exploited computer vision to capture the data from a force platform commercially available and use it as ground truth. Finally, a second version of the platform was built and is presented in the paper. That version is currently being validated clinically with both healthy and impaired human participants. The preliminary data are presented in this paper.



中文翻译:

开放式振动和压力平台,可通过增强学习剂防止跌倒

老年人口跌倒的风险可能会导致严重后果。它会严重影响受害者的生活质量,甚至导致他们过早死亡。文献中已经提出了许多技术手段来检测跌倒,但是在预防跌倒方面却付出了很少的努力。在本文中,我们的研究团队提出了一种配备有压力传感器的廉价开放式振动平台。该平台由易于获得的电子组件构建而成,可被物理治疗师用作工具,以帮助他们评估处于姿势不平衡风险中的个体的姿势控制。该平台的构建使其易于被科学界复制。此外,使它正常工作所需的计算机代码是完全开源的,可以在任何非商业应用程序中使用。该平台的第一个版本已由7位健康的人类参与者进行了测试。部署并测试了一种简单的增强学习剂,以自动校准振动电机以获得最佳刺激。特工利用计算机视觉从可商购的部队平台捕获数据,并将其用作基本事实。最后,构建了该平台的第二个版本,并在本文中进行了介绍。该版本目前正通过健康和残障人类参与者进行临床验证。本文提供了初步数据。部署并测试了一种简单的增强学习剂,以自动校准振动电机以获得最佳刺激。特工利用计算机视觉从可商购的部队平台捕获数据,并将其用作基本事实。最后,构建了该平台的第二个版本,并在本文中进行了介绍。该版本目前正通过健康和残障人类参与者进行临床验证。本文提供了初步数据。部署并测试了一种简单的增强学习剂,以自动校准振动电机以获得最佳刺激。特工利用计算机视觉从可商购的部队平台捕获数据,并将其用作基本事实。最后,构建了该平台的第二个版本,并在本文中进行了介绍。该版本目前正通过健康和残障人类参与者进行临床验证。本文提供了初步数据。该版本目前正通过健康和残障人类参与者进行临床验证。本文提供了初步数据。该版本目前正通过健康和残障人类参与者进行临床验证。本文提供了初步数据。

更新日期:2020-05-26
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