ArticleSensors (Basel, Switzerland)2022
IMU Motion Capture Method with Adaptive Tremor Attenuation in Teleoperation Robot System.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Conversion of Upper-Limb Inertial Measurement Unit Data to Joint Angles: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Predicting Subjective Usability from Kinematic Data in IMU-Based Robotic Teleoperation.Sensors (Basel, Switzerland) · 2026Article
- Review
- Technical Validation of a Multimodal Cognitive-Haptic Sudoku Platform Under Simulated Tremor Conditions.Bioengineering (Basel, Switzerland) · 2025Article
- Using a wearable system combining inertial and force sensing for simultaneous detection of limb motion and grasping actions in the workplace.Wearable technologies · 2025Article
- Biosignal-integrated robotic systems with emerging trends in visual interfaces: A systematic review.Biophysics reviews · 2024Review
- Collider-based movement detection and control of wearable soft robots for visually augmenting dance performance.Frontiers in robotics and AI · 2024Article
- Upper limb movement quality measures: comparing IMUs and optical motion capture in stroke patients performing a drinking task.Frontiers in digital health · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Teleoperation robot systems can help humans perform tasks in unstructured environments. However, non-intuitive control interfaces using only a keyboard or joystick and physiological tremor reduce the performance of teleoperation. This paper presents an intuitive control interface based on the wearable device gForcePro+ armband. Two gForcePro+ armbands are worn at the centroid of the upper arm and forearm, respectively. Firstly, the kinematics model of the human arm is established, and the inertial measurement units (IMUs) are used to capture the position and orientation information of the end of the arm. Then, a regression model of angular transformation is developed for the phenomenon that the rotation axis of the torsion joint is not perfectly aligned with the limb segment during motion, which can be applied to different individuals. Finally, to attenuate the physiological tremor, a variable gain extended Kalman filter (EKF) fusing sEMG signals is developed. The described control interface shows good attitude estimation accuracy compared to the VICON optical capture system, with an average angular RMSE of 4.837° ± 1.433°. The performance of the described filtering method is tested using the xMate3 Pro robot, and the results show it can improve the tracking performance of the robot and reduce the tremor.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.