Towards optimization of wearable sensor technology to measure human movement in real world settings

优化可穿戴传感器技术以测量现实世界中的人体运动

• 批准号: RGPIN-2019-04514
• 负责人: Hunt, Michael
• 金额: $ 2.04万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=682922
• 关键词: Towards; optimization; wearable; sensor; technology

The market for wearable sensors to measure and track human function has exploded in recent years. More and more people are using such devices to monitor many different aspects of everyday life. This explosion has been brought on by advances in technology such as reduced size and cost of such sensors, as well as increased battery life and storage capabilities, and has been facilitated by an ever-growing public desire to better understand how one's body is working. Unfortunately, this growth in availability and demand for these devices has far outgrown the science of the data in which they create. Very little information exists to inform decisions related to best sensor configuration, appropriateness of certain variables, and which activities are best measured. The proposed research will directly address these gaps, and will lead to a novel classification algorithm designed to detect changes in movement parameters in the real world using wearable technology. These are necessary steps to achieve my long-term vision of a better understanding of fundamental human movement through the development of innovative detection algorithms and best practice policies for the collection of movement data using wearable technologies.******The immediate short-term objectives of the research will be to improve the quantification of human movement patterns using wearable sensor technology during common activities of daily living. I will lead a research program over the next five years that will advance our ability to understand human movement in real world settings. We will improve sensor configuration and key parameters related to the collection of human movement data from wearable sensors using sophisticated analysis techniques. Our hypotheses and advances will first be informed and tested using current gold-standard motion capture systems to ensure accuracy and validity of our new sensor configurations. We will then translate our findings to the real world by developing a novel detection algorithm aiming to classify movement changes in real-world settings. ******Our novel contributions from this research will provide researchers with better knowledge for how to best incorporate wearable movement technology into their studies. This knowledge will help facilitate a transition from reliance on expensive laboratory-based movement assessment that may not accurately depict real world functioning. Industry will use the contributions from this research to refine the development of new and existing commercially-available wearable movement sensors that will result in more accurate and reliable products used in the general population. Finally, the general public will benefit from this work. Users ranging from athletes and coaches who use these devices to assess movement to improve athletic performance, to everyday individuals who are interested in simply tracking their movement performance for overall well-being, will stand to benefit.

近年来，用于测量和跟踪人体功能的可穿戴传感器市场爆炸式增长。越来越多的人使用这些设备来监控日常生活的许多不同方面。这种爆炸式增长是由技术进步带来的，比如这种传感器的尺寸和成本减少，电池寿命和存储能力增加，以及公众对更好地了解身体如何工作的日益增长的愿望。不幸的是，这些设备的可用性和需求的增长远远超过了它们所创建的数据的科学。关于最佳传感器配置、某些变量的适当性以及最好测量哪些活动的决策信息很少。提出的研究将直接解决这些空白，并将导致一种新的分类算法，旨在使用可穿戴技术检测现实世界中运动参数的变化。这些都是实现我的长期愿景的必要步骤，通过开发创新的检测算法和使用可穿戴技术收集运动数据的最佳实践政策，更好地理解基本的人类运动。******该研究的近期短期目标将是在日常生活的常见活动中使用可穿戴传感器技术改善人类运动模式的量化。我将在未来五年领导一个研究项目，以提高我们在现实世界中理解人类运动的能力。我们将使用复杂的分析技术改进传感器配置和与可穿戴传感器收集人体运动数据相关的关键参数。我们的假设和进展将首先使用当前的金标准动作捕捉系统进行通知和测试，以确保我们的新传感器配置的准确性和有效性。然后，我们将通过开发一种新的检测算法，将我们的发现转化为现实世界，旨在对现实世界环境中的运动变化进行分类。******我们在这项研究中的新贡献将为研究人员提供更好的知识，如何最好地将可穿戴运动技术纳入他们的研究中。这一知识将有助于促进从依赖昂贵的基于实验室的运动评估的转变，这种评估可能无法准确描述现实世界的功能。工业界将利用这项研究的贡献来改进新的和现有的商业可穿戴运动传感器的开发，这将导致在普通人群中使用更准确和可靠的产品。最后，公众将从这项工作中受益。从使用这些设备来评估运动以提高运动成绩的运动员和教练，到对简单跟踪自己的运动表现以获得整体健康感兴趣的日常个人，用户都将从中受益。