论文标题
人体电容/身体区域电场对个人和协作活动识别的贡献
The Contribution of Human Body Capacitance/Body-Area Electric Field To Individual and Collaborative Activity Recognition
论文作者
论文摘要
当前主导的可穿戴身体运动传感器是IMU。这项工作提出了一种替代性可穿戴运动传感方法：人体电容（HBC，通常也被定义为身体面积电场）。 HBC虽然在跟踪姿势和轨迹方面的坚固努力较低，但具有两种使其具有吸引力的属性。首先，在被跟踪的身体部位上的传感节点的部署不是HBC传感方法的要求。其次，HBC对人体与周围环境的相互作用很敏感，包括触摸和直接接近人和物体。我们首先描述了HBC，传感器体系结构和实现的传感原理以及评估方法。然后，我们提出了两项案例研究，证明了HBC作为IMU的补充/替代方案。首先，我们探讨了七个无机腿部锻炼的运动识别和重复计数，以及HBC和IMU的信号来源的11次通用健身房锻炼。 HBC传感在分类中显示出明显的优势（在F-评分中为0.89 vs 0.78）和仅腿部练习的计数（准确性0.982 vs 0.938）。对于一般的健身房锻炼，HBC仅显示出对某些锻炼（例如内收锻炼）的识别改善，仅腿部就可以完成运动。而且，它还为IMU提供更好的效果，以进行锻炼（0.800 vs. 0.756戴在手腕上时）。在第二种情况下，我们试图通过使用腕上的HBC传感单元来识别与用户之间的对象和物理协作有关的操作。当从单个用户接收数据时，我们检测到用户之间的协作，从两个用户接收到0.78时，我们检测到了协作。电容式传感器可以通过16 \％通过F-评分在单个腕上加速度计方法上提高对协作活动的识别。
The current dominated wearable body motion sensor is IMU. This work presented an alternative wearable motion-sensing approach: human body capacitance (HBC, also commonly defined as body-area electric field). While being less robust in tracking the posture and trajectory, HBC has two properties that make it an attractive. First, the deployment of the sensing node on the being tracked body part is not a requirement for HBC sensing approach. Second, HBC is sensitive to the body's interaction with its surroundings, including both touching and being in the immediate proximity of people and objects. We first described the sensing principle for HBC, sensor architecture and implementation, and methods for evaluation. We then presented two case studies demonstrating the usefulness of HBC as a complement/alternative to IMUs. First, we explored the exercise recognition and repetition counting of seven machine-free leg-only exercises and eleven general gym workouts with the signal source of HBC and IMU. The HBC sensing shows significant advantages over the IMU signals in classification(0.89 vs 0.78 in F-score) and counting(0.982 vs 0.938 in accuracy) of the leg-only exercises. For the general gym workouts, HBC only shows recognition improvement for certain workouts like adductor where legs alone complete the movement. And it also supplies better results over the IMU for workouts counting(0.800 vs. 0.756 when wearing the sensors on the wrist). In the second case, we tried to recognize actions related to manipulating objects and physical collaboration between users by using a wrist-worn HBC sensing unit. We detected collaboration between the users with 0.69 F-score when receiving data from a single user and 0.78 when receiving data from both users. The capacitive sensor can improve the recognition of collaborative activities with an F-score over a single wrist accelerometer approach by 16\%.
