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

近年来，用于测量和跟踪人体功能的可穿戴传感器市场呈爆炸式增长。越来越多的人使用这种设备来监控日常生活的许多不同方面。这种爆炸是由技术进步引起的，比如缩小了这类传感器的尺寸和成本，以及延长了电池寿命和存储能力，而且公众越来越希望更好地了解一个人的身体是如何工作的，这也是促成这一爆炸的原因。不幸的是，这些设备的可用性和需求的增长已经远远超过了它们所创建的数据的科学研究。有关最佳传感器配置、某些变量的适当性以及最佳测量活动的决策所需的信息非常少。这项拟议的研究将直接解决这些差距，并将产生一种新的分类算法，旨在利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最佳实践政策来使用可穿戴技术收集运动数据，从而更好地了解基本的人体运动。*这项研究的短期目标将是在日常生活中使用可穿戴传感器技术改进人类运动模式的量化。在接下来的五年里，我将领导一个研究项目，该项目将提高我们理解现实世界中人类运动的能力。我们将使用复杂的分析技术改进传感器配置和与从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黄金标准的运动捕获系统进行通知和测试，以确保我们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旨在对现实世界中的运动变化进行分类的新型检测算法，将我们的发现转化为现实世界。*我们这项研究的新贡献将为研究人员提供更好的知识，帮助他们最好地将可穿戴运动技术融入他们的研究中。这种知识将有助于促进从依赖昂贵的基于实验室的运动评估过渡，这种评估可能不能准确地描述真实世界的运行情况。工业界将利用这项研究的贡献来完善新的和现有的商业可穿戴运动传感器的开发，这些传感器将产生更准确和可靠的产品，用于普通人群。最后，广大公众将从这项工作中受益。从使用这些设备评估运动以提高运动成绩的运动员和教练，到只对跟踪自己的运动表现以获得整体福祉感兴趣的日常个人，用户都将受益。

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.