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Real-time OpenSim via IMUs for Full Body Kinematics

- Citation Author(s):
- Submitted by:
- Chenquan Xu
- Last updated:
- Mon, 03/24/2025 - 00:07
- DOI:
- 10.21227/n452-qv40
- License:
- Categories:
- Keywords:
Abstract
We present a comprehensive dataset developed as part of a study to compute real-time kinematics using a full-body wearable approach incorporating up to 12 IMUs. This dataset includes optical and inertial measurements from 22 subjects engaged in a diverse set of 9 activities: walking, running, squatting, boxing, yoga, dance, badminton, stair climbing, and seated extremity exercises. The dataset features ground truth kinematics, offline predicted kinematics, online predicted kinematics, and IMU-simulated offline predicted kinematics.
The approach leverages the tools in OpenSim to derive joint angles from IMU orientations in real time at a frequency of 20 Hz using optimization algorithms. The inverse kinematics calculation can be performed on a personal computer (PC) or on a SageMotion hub, which facilitates data exchange between IMU nodes and cellphones/PCs, enabling real-time joint angle computation in scenarios that require a larger range of motion.
To utilize the dataset, follow these steps:
1. Download the dataset.
2. Load the CSV files into your preferred data analysis tool (e.g., Python, R).
3. Refer to the data dictionary for details on each variable.
4. Perform your analysis as required.