IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
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IEEE Trans Neural Syst Rehabil Eng · Jan 2015
Characterization of a benchmark database for myoelectric movement classification.
In this paper, we characterize the Ninapro database and its use as a benchmark for hand prosthesis evaluation. The database is a publicly available resource that aims to support research on advanced myoelectric hand prostheses. The database is obtained by jointly recording surface electromyography signals from the forearm and kinematics of the hand and wrist while subjects perform a predefined set of actions and postures. ⋯ Furthermore, statistical analysis of these results shows that classification accuracy is negatively correlated with the subject's Body Mass Index. The analysis and the results described in this paper aim to be a strong baseline for the Ninapro database. Thanks to the Ninapro database (and the characterization described in this paper), the scientific community has the opportunity to converge to a common position on hand movement recognition by surface electromyography, a field capable to strongly affect hand prosthesis capabilities.
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IEEE Trans Neural Syst Rehabil Eng · Jan 2015
Motor imagery learning induced changes in functional connectivity of the default mode network.
Numerous studies provide evidences that motor skill learning changes the activity of some brain regions during task as well as some resting networks during rest. However, it is still unclear how motor learning affects the resting-state default-mode network (DMN). Using functional magnetic resonance imaging, this study investigated the alteration of the DMN after motor skill learning with mental imagery practice. ⋯ For the experimental group, interregional connectivity, estimated by the graph theory method, between the medial temporal lobe, lateral temporal, and lateral parietal cortex within the DMN was increased after learning, whereas activity of the DMN network, estimated by the independent component analysis method, remained stable. Moreover, the experimental group showed significant improvement in motor performance after learning and a negative correlation between the alteration of the execution rate and changes in activity in the lateral parietal cortex. These results indicate that the DMN could be sculpted by motor learning in a manner of altering interregional connectivity and may imply that the DMN plays a role in improving behavioral performance.