AIMC Topic: Movement

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Role of Muscle Synergies in Real-Time Classification of Upper Limb Motions using Extreme Learning Machines.

Journal of neuroengineering and rehabilitation
BACKGROUND: Myoelectric signals offer significant insights in interpreting the motion intention and extent of effort involved in performing a movement, with application in prostheses, orthosis and exoskeletons. Feature extraction plays a vital role, ...

The Role of Audio-Visual Feedback in a Thought-Based Control of a Humanoid Robot: A BCI Study in Healthy and Spinal Cord Injured People.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The efficient control of our body and successful interaction with the environment are possible through the integration of multisensory information. Brain-computer interface (BCI) may allow people with sensorimotor disorders to actively interact in th...

EEG Analysis During Active and Assisted Repetitive Movements: Evidence for Differences in Neural Engagement.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Two key ingredients of a successful neuro-rehabilitative intervention have been identified as intensive and repetitive training and subject's active participation, which can be coupled in an active robot-assisted training. To exploit these two elemen...

Neural correlates of motor recovery after robot-assisted stroke rehabilitation: a case series study.

Neurocase
Robot-assisted bilateral arm therapy (RBAT) has shown promising results in stroke rehabilitation; however, connectivity mapping of the sensorimotor networks after RBAT remains unclear. We used fMRI before and after RBAT and a dose-matched control int...

Adaptive local learning in sampling based motion planning for protein folding.

BMC systems biology
BACKGROUND: Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms, such as Probabilistic Roadmap Methods, have been successful in modeling the folding landscape. Probabilistic Roadmap Methods ...

Daily changes of individual gait patterns identified by means of support vector machines.

Gait & posture
Despite the common knowledge about the individual character of human gait patterns and about their non-repeatability, little is known about their stability, their interactions and their changes over time. Variations of gait patterns are typically des...

Improving the recognition of grips and movements of the hand using myoelectric signals.

BMC medical informatics and decision making
BACKGROUND: People want to live independently, but too often disabilities or advanced age robs them of the ability to do the necessary activities of daily living (ADLs). Finding relationships between electromyograms measured in the arm and movements ...

On the other hand: Increased cortical activation to human versus mechanical hands in infants.

NeuroImage
There is a large body of work demonstrating that infants are sensitive to the distinction between human and mechanical entities from the early months of life, and have different expectations for the way these entities move and interact. The current w...

Motor Imagery Classification Based on Bilinear Sub-Manifold Learning of Symmetric Positive-Definite Matrices.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In motor imagery brain-computer interfaces (BCIs), the symmetric positive-definite (SPD) covariance matrices of electroencephalogram (EEG) signals carry important discriminative information. In this paper, we intend to classify motor imagery EEG sign...

Neuro-fuzzy models for hand movements induced by functional electrical stimulation in able-bodied and hemiplegic subjects.

Medical engineering & physics
Functional Electrical Stimulation (FES) may be effective as a therapeutic treatment for improving functional reaching and grasping. Upper-limb FES models for predicting joint torques/angles from stimulation parameters can be useful to support the ite...