Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
نویسندگان
چکیده
WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve participants performed lifting series in which the object's weight (165, 330, or 660 g), surface friction (sandpaper, suede, or silk surface), or both, were changed unpredictably between trials, thus enforcing changes in fingertip force coordination. In each of a total of 3,936 trials, the participant was cued to reach for the object, grasp it with the thumb and index finger, lift it and hold it for a couple of seconds, put it back on the support surface, release it, and, lastly, to return the hand to a designated rest position. We recorded EEG (32 channels), EMG (five arm and hand muscles), the 3D position of both the hand and object, and force/torque at both contact plates. For each trial we provide 16 event times (e.g., 'object lift-off') and 18 measures that characterize the behaviour (e.g., 'peak grip force').
منابع مشابه
EEG Based Brain Computer Interface Hand Grasp Control: Feature Extraction Method MTCSP
Brain-Computer Interfaces (BCIs) are communication systems, which enable users to send commands to computers by using brain activity only; this activity being generally measured by Electroencephalography (EEG). BCIs are generally designed according to a pattern recognition approach, i.e., by extracting features from EEG signals, and by using a classifier to identify the user’s mental state from...
متن کاملEEG Based Brain Computer Interface Hand Grasp Control: Feature Extraction Method MTCSP
Brain-Computer Interfaces (BCIs) are communication systems, which enable users to send commands to computers by using brain activity only; this activity being generally measured by Electroencephalography (EEG). BCIs are generally designed according to a pattern recognition approach, i.e., by extracting features from EEG signals, and by using a classifier to identify the user’s mental state from...
متن کاملControl of grasp stability in humans under different frictional conditions during multidigit manipulation.
Control of grasp stability under different frictional conditions has primarily been studied in manipulatory tasks involving two digits only. Recently we found that many of the principles for control of forces originally demonstrated for two-digit grasping also apply to various three-digit grasps. Here we examine the control of grasp stability in a multidigit task in which subjects used the tips...
متن کاملPredicting the Effect of Surface Texture on the Qualitative Form of Prehension
Reach-to-grasp movements change quantitatively in a lawful (i.e. predictable) manner with changes in object properties. We explored whether altering object texture would produce qualitative changes in the form of the precontact movement patterns. Twelve participants reached to lift objects from a tabletop. Nine objects were produced, each with one of three grip surface textures (high-friction, ...
متن کاملTitle Analysis of time-varying synchronization of multi-channel EEG
This paper proposes a novel method based on the time-frequency coherent representation for quantifying synchronization of multi-channel signals with high resolution. The presented wavelet-coherent technique provides the information regarding both the degree of coherence and the relation of phase difference. The wavelet coherence enables to provide the synchronization and the direction of inform...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 1 شماره
صفحات -
تاریخ انتشار 2014