论文标题
使用惯性，生理和环境传感器的人类活动识别：一项全面调查
Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey
论文作者
论文摘要
在过去的十年中，人类活动识别（HAR）已成为一个充满活力的研究领域，尤其是由于我们日常生活中存在的电子设备（例如智能手机，智能手表和摄像机）的传播。此外，深度学习和其他机器学习算法的进步使研究人员可以在包括体育，健康和福祉应用在内的各个领域中使用HAR。例如，HAR被认为是通过日常活动来监测其认知和身体功能来支持老年人日常生活的最有前途的辅助技术工具之一。这项调查着重于机器学习在基于惯性传感器以及生理和环境传感器结合使用的基于惯性传感器的HAR应用中的关键作用。
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area, especially due to the spread of electronic devices such as smartphones, smartwatches and video cameras present in our daily lives. In addition, the advance of deep learning and other machine learning algorithms has allowed researchers to use HAR in various domains including sports, health and well-being applications. For example, HAR is considered as one of the most promising assistive technology tools to support elderly's daily life by monitoring their cognitive and physical function through daily activities. This survey focuses on critical role of machine learning in developing HAR applications based on inertial sensors in conjunction with physiological and environmental sensors.
