Trial reportPloS one2015
Assessing movement factors in upper limb kinematics decoding from EEG signals.
Trial report in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
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Who cites it
11 citing papers in PubMed, 27 citations in OpenAlex.
- Exploring Kinematics Information Decoding from EEG Slow Cortical Potentials During Movement Imagination and Observation.Sensors (Basel, Switzerland) · 2026Article
- Electroencephalography Enables Continuous Decoding of Hand Motion Angles in Polar Coordinates.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Modeling the cortical response elicited by wrist manipulation via a nonlinear delay differential embedding.Physical and engineering sciences in medicine · 2024Article
- Literature review of stroke assessment for upper-extremity physical function via EEG, EMG, kinematic, and kinetic measurements and their reliability.Journal of neuroengineering and rehabilitation · 2023Review
- Reconstructing Synergy-Based Hand Grasp Kinematics from Electroencephalographic Signals.Sensors (Basel, Switzerland) · 2022Article
- Response of the Cerebral Cortex to Resistance and Non-resistance Exercise Under Different Trajectories: A Functional Near-Infrared Spectroscopy Study.Frontiers in neuroscience · 2021Article
- Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury.Scientific reports · 2019Article
- Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review.Frontiers in computational neuroscience · 2019Review
- Characteristics of Kinematic Parameters in Decoding Intended Reaching Movements Using Electroencephalography (EEG).Frontiers in neuroscience · 2019Article
- Estimation of Neuromuscular Primitives from EEG Slow Cortical Potentials in Incomplete Spinal Cord Injury Individuals for a New Class of Brain-Machine Interfaces.Frontiers in computational neuroscience · 2018Article
- Classification of upper limb center-out reaching tasks by means of EEG-based continuous decoding techniques.Journal of neuroengineering and rehabilitation · 2017Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The past decades have seen the rapid development of upper limb kinematics decoding techniques by performing intracortical recordings of brain signals. However, the use of non-invasive approaches to perform similar decoding procedures is still in its early stages. Recent studies show that there is a correlation between electroencephalographic (EEG) signals and hand-reaching kinematic parameters. From these studies, it could be concluded that the accuracy of upper limb kinematics decoding depends, at least partially, on the characteristics of the performed movement. In this paper, we have studied upper limb movements with different speeds and trajectories in a controlled environment to analyze the influence of movement variability in the decoding performance. To that end, low frequency components of the EEG signals have been decoded with linear models to obtain the position of the volunteer's hand during performed trajectories grasping the end effector of a planar manipulandum. The results confirm that it is possible to obtain kinematic information from low frequency EEG signals and show that decoding performance is significantly influenced by movement variability and tracking accuracy as continuous and slower movements improve the accuracy of the decoder. This is a key factor that should be taken into account in future experimental designs.
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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.