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An IR and RF Based System for Functional Gait Analysis in a Multi-Resident Smart-Home

机译：基于红外和射频的多驻地智能家居功能步态分析系统

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摘要

Changes in the gait characteristics, such as walking speed and stride length, of a person living at home can be used to presage cognitive decline, predict fall potential, monitor long-term changes in cognitive impairment, test drug regimens, and more. This thesis presents a novel approach to gait analysis in a smart-home environment by leveraging new advances in inexpensive sensors and embedded systems to create novel solutions for in-home gait analysis. Using a simple, non-invasive hardware system consisting entirely of wall-mounted infrared and radio frequency sensor arrays, data is collected on the gait of subjects as they pass by. This data is then analyzed and sent to a clinician for further study. The system is non-invasive in that it does not use cameras and could be built into the molding of a home so that it would be nearly invisible. In a finished prototype version, the system presented in this thesis could be used to analyze the gait characteristics of one or more subjects living in a home environment while ignoring the data of visitors and other non-subject cohabitants. The ability to constantly collect data from a home environment could provide thousands of observations per year for clinical analysis. Providing such a robust data set may allow people with gait impairment to live at home longer and more safely before transitioning to a care facility, have a reduced fall risk due to better prediction, and live a healthier life in old age.
机译：在家中某个人的步态特征的变化，例如步行速度和步幅，可用于预示认知能力下降，预测跌倒的可能性，监测认知障碍的长期变化，测试药物治疗方案等。本文通过利用廉价传感器和嵌入式系统的新进展为家庭步态分析创建新颖的解决方案，提出了一种在智能家庭环境中进行步态分析的新颖方法。使用完全由壁挂式红外和射频传感器阵列组成的简单，非侵入性硬件系统，可以在受试者经过时通过步态收集数据。然后将这些数据进行分析并发送给临床医生以进行进一步研究。该系统是非侵入性的，因为它不使用相机，并且可以内置在房屋的造型中，因此几乎是不可见的。在完成的原型版本中，本文提出的系统可用于分析一个或多个生活在家庭环境中的受试者的步态特征，而忽略了访客和其他非受试者同居者的数据。不断从家庭环境收集数据的能力每年可为临床分析提供数千个观察结果。提供这样一个可靠的数据集可以使步态不佳的人在过渡到护理机构之前在家里更长寿和更安全，由于更好的预测而降低跌倒风险，并在老年人中过上更健康的生活。

著录项

  • 作者

    Schafermeyer, Erich Reinhardt.;

  • 作者单位

    Portland State University.;

  • 授予单位 Portland State University.;
  • 学科 Electrical engineering.;Biomedical engineering.
  • 学位 M.S.
  • 年度 2017
  • 页码 112 p.
  • 总页数 112
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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