Name
Abstract | ||
|---|---|---|
Inertial measurement units (IMUs) increasingly function as a basic component of a wearable sensor network (WSN). The IMU-based joint angle estimation (JAE) is a typical usage of IMUs for WSN, with extensive applications. However, the issue that IMUs move with respect to their original placement during JAE is still a research gap and limits the robustness of deploying the technique in real-world application scenarios. In this study, we propose to detect and correct the IMU movement online in a computationally lightweight manner. In particular, we first experimentally investigate the influence of IMU movements. Second, we design the metrics for detecting IMU movements by mathematically formulating how the IMU movement affects the IMU's measurements. Third, we determine the optimal thresholds of metrics by synthetic IMU data from a significantly amended simulation model. Finally, a correction method is proposed to correct the effects of IMU movements. We demonstrate our method on both synthetic data and real-user data. Our proposed method achieves a detection rate of 94.8%, a misdetection rate of 9.8%, and the calculation time of 2.15 ms for detecting IMU movements and can restore the accuracy of JAE. All of the results significantly outperform the intuitive method. The results demonstrate our method is a promising solution to detect and correct IMU movements during JAE. This study will aid the deployment of IMU-based JAE in real-world applications. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TIM.2022.3167771 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT |
Keywords | DocType | Volume |
Measurement, Calibration, Estimation, Wireless sensor networks, Data models, Performance evaluation, Mathematical models, Fault tolerance, inertial measurement unit (IMU) movement, joint angle estimation (JAE), wearable sensors | Journal | 71 |
ISSN | Citations | PageRank |
0018-9456 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunzhi Yi | 1 | 0 | 2.03 |
| Seungmin Rho | 2 | 411 | 46.45 |
| Baichun Wei | 3 | 0 | 0.34 |
| Chifu Yang | 4 | 12 | 7.65 |
| Zhen Ding | 5 | 0 | 3.04 |
| Zhiyuan Chen | 6 | 0 | 0.34 |
| Feng Jiang | 7 | 304 | 37.75 |