Graduate School of Information Science and Engineering, Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu 525-8577, Shiga, Japan.
Strategic Creation Research Promotion Project (PRESTO), Japan Science and Technology Agency (JST), 4-1-8 Honmachi, Kawaguchi 332-0012, Saitama, Japan.
Sensors (Basel). 2022 Jan 31;22(3):1090. doi: 10.3390/s22031090.
With the increasing use of wearable devices equipped with various sensors, information on human activities, biometrics, and surrounding environments can be obtained via sensor data at any time and place. When such devices are attached to arbitrary body parts and multiple devices are used to capture body-wide movements, it is important to estimate where the devices are attached. In this study, we propose a method that estimates the load positions of wearable devices without requiring the user to perform specific actions. The proposed method estimates the time difference between a heartbeat obtained by an ECG sensor and a pulse wave obtained by a pulse sensor, and it classifies the pulse sensor position from the estimated time difference. Data were collected at 12 body parts from four male subjects and one female subject, and the proposed method was evaluated in both user-dependent and user-independent environments. The average F-value was 1.0 when the number of target body parts was from two to five.
随着配备各种传感器的可穿戴设备的使用日益增多，通过传感器数据，可以随时随地获取有关人体活动、生物特征和周围环境的信息。当这些设备附着在任意身体部位上，并且使用多个设备来捕捉全身运动时，估计设备附着的位置就变得很重要。在这项研究中，我们提出了一种无需用户执行特定动作即可估计可穿戴设备负载位置的方法。该方法通过估计心电图传感器获取的心跳与脉搏传感器获取的脉搏之间的时间差，并根据估计的时间差对脉搏传感器的位置进行分类。从四名男性和一名女性受试者的 12 个身体部位收集了数据，并在用户依赖和用户独立的环境中对所提出的方法进行了评估。当目标身体部位的数量从两个到五个时，平均 F 值为 1.0。
