Developing algorithms for automated motion sensing

XCO是一家体育和健康科学公司，通过基于集线器和多个无线电信号标签的运动跟踪系统开发硬件和算法，以提供用于体育和医疗保健应用的数据。XCO有兴趣进一步开发这些算法和新的算法，以分析运动和医疗应用中人体运动的特征。机器学习技术，特别是深度学习神经网络的应用，不仅将自动化昂贵的时间序列数据集成，还将允许对这些数据进行更有洞察力的分析，并改进现有的运动员和患者评估制度。该项目将利用Jeremy Seaman博士和他的团队的数据流分析和机器学习专业知识，加快XCO跟踪系统的有意义输出的开发，为体育、运动医学和临床神经科学的分析和诊断提供好处。

XCO is a sport and health sciences company developing hardware and algorithms to provide data for use in sport and health care applications through a motion tracking system based on a hub and multiple radio signal tags. XCO is interested in further developing those algorithms, and new ones, to analyze the characteristics of human motion for sport and medical applications. The application of machine learning techniques, in particular deep learning neural networks, will not only automate costly time-series data integration, but allow more insightful analysis of this data, and improve existing athlete and patient assessment regimes. This project will leverage the data stream analysis and machine learning expertise of Dr. Jeremy Seaman's and his team to accelerate the development of meaningful outputs from XCO's tracking system, providing benefits to analytics and diagnosis in athletics, sports medicine, and clinical neuroscience.