IDLab-Faculty of Applied Engineering, University of Antwerp-imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium.
Sensors (Basel). 2021 Apr 19;21(8):2875. doi: 10.3390/s21082875.
Inertial Measurement Units (IMUs) are frequently implemented in wearable devices. Thanks to advances in signal processing and machine learning, applications of IMUs are not limited to those explicitly addressing body movements such as Activity Recognition (AR). On the other hand, wearing IMUs on the chest offers a few advantages over other body positions. AR and posture analysis, cardiopulmonary parameters estimation, voice and swallowing activity detection and other measurements can be approached through chest-worn inertial sensors. This survey tries to introduce the applications that come with the chest-worn IMUs and summarizes the existing methods, current challenges and future directions associated with them. In this regard, this paper references a total number of 57 relevant studies from the last 10 years and categorizes them into seven application areas. We discuss the inertial sensors used as well as their placement on the body and their associated validation methods based on the application categories. Our investigations show meaningful correlations among the studies within the same application categories. Then, we investigate the data processing architectures of the studies from the hardware point of view, indicating a lack of effort on handling the main processing through on-body units. Finally, we propose combining the discussed applications in a single platform, finding robust ways for artifact cancellation, and planning optimized sensing/processing architectures for them, to be taken more seriously in future research.
惯性测量单元（IMU）经常被应用在可穿戴设备中。由于信号处理和机器学习的进步，IMU 的应用不仅限于明确针对身体运动的应用，如活动识别（AR）。另一方面，与其他身体位置相比，在胸部佩戴 IMU 有一些优势。通过佩戴在胸部的惯性传感器，可以进行 AR 和姿势分析、心肺参数估计、语音和吞咽活动检测以及其他测量。本综述试图介绍与胸部佩戴的 IMU 相关的应用，并总结了与之相关的现有方法、当前挑战和未来方向。在这方面，本文参考了过去 10 年中总共 57 项相关研究，并根据应用领域将其分类为七个应用领域。我们讨论了用作传感器的惯性传感器及其在身体上的位置以及基于应用类别相关的验证方法。我们的研究表明，在同一应用领域内的研究之间存在有意义的相关性。然后，我们从硬件的角度调查了研究的数据处理架构，表明在通过身体单元进行主要处理方面缺乏努力。最后，我们提出将讨论的应用结合到一个单一的平台中，找到稳健的方法来消除伪影，并为它们规划优化的感应/处理架构，以便在未来的研究中得到更认真的对待。
