Haptic Brain-Computer-Interfaces (BCI) in Stroke
نویسندگان
چکیده
2 Chronic stroke patients without residual movements of the paretic side do not respond to any available rehabilitation strategy. Recently BCI technology has been proposed for as a neurorehabilitation tool after stroke. It has been shown that learning of brain control (MEG-sensorimotor rhythm, SMR) in chronic stroke is possible but no substantial improvements in motor control and no generalization to functional recovery were accomplished. Previous work of this group demonstrated how BCI could be used as a tool in chronic stroke motor rehabilitation when linking contingently and online brain activity (due to movement intention) and movement (the same intentioned movement assisted by robotic orthoses). In this work 32 chronic stroke patients without residual finger extension underwent BCI training coupled with behavioral physical therapy. The patients were divided in two groups. The e[SHULPHQWDO JURXS UHFHLYHG § VHVVLRQV RI FRQWLQJHQW BCI-training: ipsilesional SMR-desynchronisation was linked to movements of robotic orthoses (arm/hand) fixed to the paralysed limb. The control group (sham) received the same training but movement of the orthotic device was randomized and independent of SMR-change. Both groups received identical behavioral physiotherapy related to the same movements trained after every BCI-session. The experimental group showed a significant continuous improvement in EMG activity and control in the paralyzed hand and arm during the intervention.
منابع مشابه
Comparison of Different Linear Filter Design Methods for Handling Ocular Artifacts in Brain Computer Interface System
Brain-computer interfaces (BCI) record brain signals, analyze and translate them into control commands which are relayed to output devices that carry out desired actions. These systems do not use normal neuromuscular output pathways. Actually, the principal goal of BCI systems is to provide better life style for physically-challenged people which are suffered from cerebral palsy, amyotrophic l...
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 کاملCombining Brain-Computer Interfaces and Haptics: Detecting Mental Workload to Adapt Haptic Assistance
In this paper we introduce the combined use of BrainComputer Interfaces (BCI) and Haptic interfaces. We propose to adapt haptic guides based on the mental activity measured by a BCI system. This novel approach is illustrated within a proof-of-concept system: haptic guides are toggled during a path-following task thanks to a mental workload index provided by a BCI. The aim of this system is to p...
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 کاملClosing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery.
The combination of brain-computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it i...
متن کامل