Human activity recognition is a key to a lot of applications such as healthcare and smart home. In this study, we provide a comprehensive survey on recent advances and challenges in human activity recognition (HAR) with deep learning. Although there are many surveys on HAR, they focused mainly on the taxonomy of HAR and reviewed the state-of-the-art HAR systems implemented with conventional machine learning methods. Recently, several works have also been done on reviewing studies that use deep models for HAR, whereas these works cover few deep models and their variants. There is still a need for a comprehensive and in-depth survey on HAR with recently developed deep learning methods.

中文翻译：

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用于人类活动识别的深度学习调查

人类活动识别是医疗保健和智能家居等许多应用的关键。在这项研究中，我们对深度学习在人类活动识别 (HAR) 方面的最新进展和挑战进行了全面调查。尽管有很多关于 HAR 的调查，但他们主要关注 HAR 的分类，并回顾了使用传统机器学习方法实现的最先进的 HAR 系统。最近，还进行了几项工作来回顾使用深度模型进行 HAR 的研究，而这些工作几乎没有涉及深度模型及其变体。仍然需要使用最近开发的深度学习方法对 HAR 进行全面而深入的调查。