A Review on Body Movement Classification Using Motor Imagery EEG
نویسنده
چکیده
Imagination of various limb movements for patient suffering from several physical hindrances, Brain computer interfaces (BCI) offers analysis of motor imagery EEG which can be shown a new way of communication. Motor imagery data for body movement classification like left hand, right hand, toe, and tongue movement are available on Physionet ATM or BCI competition datasetIII. Using different Feature extraction and classification method we can get best result for body movement classification.
منابع مشابه
Classification of EEG-based motor imagery BCI by using ECOC
AbstractAccuracy in identifying the subjects’ intentions for moving their different limbs from EEG signals is regarded as an important factor in the studies related to BCI. In fact, the complexity of motor-imagination and low amount of signal-to-noise ratio for EEG signal makes this identification as a difficult task. In order to overcome these complexities, many techniques such as variou...
متن کاملClassification of Right/Left Hand Motor Imagery by Effective Connectivity Based on Transfer Entropy in EEG Signal
The right and left hand Motor Imagery (MI) analysis based on the electroencephalogram (EEG) signal can directly link the central nervous system to a computer or a device. This study aims to identify a set of robust and nonlinear effective brain connectivity features quantified by transfer entropy (TE) to characterize the relationship between brain regions from EEG signals and create a hierarchi...
متن کاملCommon Spatial Patterns Feature Extraction and Support Vector Machine Classification for Motor Imagery with the SecondBrain
Recently, a large set of electroencephalography (EEG) data is being generated by several high-quality labs worldwide and is free to be used by all researchers in the world. On the other hand, many neuroscience researchers need these data to study different neural disorders for better diagnosis and evaluating the treatment. However, some format adaptation and pre-processing are necessary before ...
متن کاملAn Analysis of the Effect of EEG Frequency Bands on the Classification of Motor Imagery Signals
The EEG frequency bands are brain rhythms that indicate the activity level of the brain. This paper investigates the effects of the sub-band frequency on the classification of motor imagery of hand movements. Ten sub-bands of 10Hz width between 0 to 100 Hz are chosen. Band power features of the sub-bands are classified using a neural classifier. Motor imagery signals recorded from the C3 and C4...
متن کاملNeuro-Fuzzy based Motor Imagery Classification for a Four Class Brain Machine Interface
Brain Machine Interface (BMI) provides a digital link between the brain and a device such as a computer, robot or wheelchair. This paper presents a BMI design using Neuro-Fuzzy classifiers for controlling a wheelchair using EEG signals. EEG signals during motor imagery (MI) of left and right hand movements are recorded noninvasively at the sensorimotor cortex. Four mental task signals are analy...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016