AIMC Topic: Motor Activity

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Common spatial pattern and wavelet decomposition for motor imagery EEG- fTCD brain-computer interface.

Journal of neuroscience methods
BACKGROUND: Recently, hybrid brain-computer interfaces (BCIs) combining more than one modality have been investigated with the aim of boosting the performance of the existing single-modal BCIs in terms of accuracy and information transfer rate (ITR)....

Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.

Parkinsonism & related disorders
INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkin...

Semisupervised Deep Stacking Network with Adaptive Learning Rate Strategy for Motor Imagery EEG Recognition.

Neural computation
Practical motor imagery electroencephalogram (EEG) data-based applications are limited by the waste of unlabeled samples in supervised learning and excessive time consumption in the pretraining period. A semisupervised deep stacking network with an a...

Upper limb motor pre-clinical assessment in Parkinson's disease using machine learning.

Parkinsonism & related disorders
INTRODUCTION: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. For example, idiopathic hyposmia (IH), which is a reduced olfactory sensitivity, is typical in >95% of PD patients ...

A Single Session of Robot-Controlled Proprioceptive Training Modulates Functional Connectivity of Sensory Motor Networks and Improves Reaching Accuracy in Chronic Stroke.

Neurorehabilitation and neural repair
BACKGROUND: Passive robot-generated arm movements in conjunction with proprioceptive decision making and feedback modulate functional connectivity (FC) in sensory motor networks and improve sensorimotor adaptation in normal individuals. This proof-of...

Covariance Matrix Adaptation for Multiobjective Multiarmed Bandits.

IEEE transactions on neural networks and learning systems
Upper confidence bound (UCB) is a successful multiarmed bandit for regret minimization. The covariance matrix adaptation (CMA) for Pareto UCB (CMA-PUCB) algorithm considers stochastic reward vectors with correlated objectives. We upper bound the cumu...

Sensorimotor Robotic Measures of tDCS- and HD-tDCS-Enhanced Motor Learning in Children.

Neural plasticity
Transcranial direct-current stimulation (tDCS) enhances motor learning in adults. We have demonstrated that anodal tDCS and high-definition (HD) tDCS of the motor cortex can enhance motor skill acquisition in children, but behavioral mechanisms remai...

Robot-assisted gait training effectively improved lateropulsion in subacute stroke patients: a single-blinded randomized controlled trial.

European journal of physical and rehabilitation medicine
BACKGROUND: Some stroke patients are known to use nonparetic extremities to push toward the paretic side, a movement known as lateropulsion. Lateropulsion impairs postural balance and interferes with rehabilitation.

Toward a motor signature in autism: Studies from human-machine interaction.

L'Encephale
BACKGROUND: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders which core symptoms are impairments in socio-communication and repetitive symptoms and stereotypies. Although not cardinal symptoms per se, motor impa...

Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate.

Computational intelligence and neuroscience
Electrocorticogram (ECoG) is a well-known recording method for the less invasive brain machine interface (BMI). Our previous studies have succeeded in predicting muscle activities and arm trajectories from ECoG signals. Despite such successful studie...