Motor imagery training of goal-directed reaching in relation to imagery of reaching and grasping in healthy people.

The study aimed to determine whether four weeks of motor imagery training (MIT) of goal-directed reaching (reaching to grasp task) would affect the cortical activity during motor imagery of reaching (MIR) and grasping (MIG) in the same way. We examined cortical activity regarding event-related potentials (ERPs) in healthy young participants. Our study also evaluated the subjective vividness of the imagery.

Motor Imagery Training of Reaching-to-Grasp Movement Supplemented by a Virtual Environment in an Individual With Congenital Bilateral Transverse Upper-Limb Deficiency.

This study explored the effect of kinesthetic motor imagery training on reaching-to-grasp movement supplemented by a virtual environment in a patient with congenital bilateral transverse upper-limb deficiency. Based on a theoretical assumption, it is possible to conduct such training in this patient. The aim of this study was to evaluate whether cortical activity related to motor imagery of reaching and motor imagery of grasping of the right upper limb was changed by computer-aided imagery training (CAIT) in a patient who was born without upper limbs compared to a healthy control subject, as characterized by multi-channel electroencephalography (EEG) signals recorded before and 4, 8, and 12 weeks after CAIT.

Computer-aided training sensorimotor cortex functions in humans before the upper limb transplantation using virtual reality and sensory feedback.

One of the biggest problems of upper limb transplantation is lack of certainty as to whether a patient will be able to control voluntary movements of transplanted hands. Based on findings of the recent research on brain cortex plasticity, a premise can be drawn that mental training supported with visual and sensory feedback can cause structural and functional reorganization of the sensorimotor cortex, which leads to recovery of function associated with the control of movements performed by the upper limbs. In this study, authors - based on the above observations - propose the computer-aided training (CAT) system, which generating visual and sensory stimuli, should enhance the effectiveness of mental training applied to humans before upper limb transplantation.

Multiclassifier system with hybrid learning applied to the control of bioprosthetic hand.

In this paper the problem of recognition of the intended hand movements for the control of bio-prosthetic hand is addressed. The proposed method is based on recognition of electromiographic (EMG) and mechanomiographic (MMG) biosignals using a multiclassifier system (MCS) working in a two-level structure with a dynamic ensemble selection (DES) scheme and original concepts of competence function. Additionally, feedback information coming from bioprosthesis sensors on the correct/incorrect classification is applied to the adjustment of the combining mechanism during MCS operation through adaptive tuning competences of base classifiers depending on their decisions.

Control of dexterous bio-prosthetic hand via sequential recognition of EMG signals using fuzzy relations.

The paper presents a concept of bio-prosthesis control via recognition of user intent on the basis of myopotentials acquired of his body. We assume that in the control process each prosthesis operation consists of specific sequence of elementary actions. The contextual (sequential) recognition is considered in which the fuzzy relation approach is applied to the construction of a classifying algorithm.