International Journal of Advance Research and Innovative Ideas in Education, 2017
People who are unable to walk and are using wheel chairs exert great amounts of energy using phys... more People who are unable to walk and are using wheel chairs exert great amounts of energy using physical strength to turn and steer the wheels. With eyesight being their guide, the disabled would save energy and could use their hands and arms for other activities. The purpose of this paper is to develop a wheelchair that will be controlled by the eyes of the person seated in the wheelchair. This will allow people without full use of their limbs the freedom to move about and provide a level of autonomy. The paper will consist of three main parts.
International Journal of Advance Research and Innovative Ideas in Education, 2017
People who are unable to walk and are using wheel chairs exert great amounts of energy using phys... more People who are unable to walk and are using wheel chairs exert great amounts of energy using physical strength to turn and steer the wheels. With eyesight being their guide, the disabled would save energy and could use their hands and arms for other activities. The purpose of this paper is to develop a wheelchair that will be controlled by the eyes of the person seated in the wheelchair. This will allow people without full use of their limbs the freedom to move about and provide a level of autonomy. The paper will consist of three main parts.
International Journal of Scientific Research in Science and Technology
Electroencephalogram (EEG) signals represent functioning of the brain, and assist in identificati... more Electroencephalogram (EEG) signals represent functioning of the brain, and assist in identification of multiple brain-related disorders including Epilepsy, Alzheimer’s disease, emotional states, Parkinson’s disease, strokes, etc. To design such models, a wide variety of machine learning & deep learning approaches are proposed by researchers. But these approaches use a black-box generic model for EEG classification, due to which their scalability is limited. To enhance this scalability, a novel feature augmented extraction model is proposed in this text. The model uses wavelet compression on input EEG data, and processes the compressed signal using a variance-based selection approach. Due to which, the model is capable of low-delay, and high accuracy classification for different brain-diseases. It evaluates wavelet-based features from input EEG data, and performs ensemble feature selection for improving feature variance. The wavelet features are able to convert input EEG data into di...
International Journal of Advance Research and Innovative Ideas in Education, 2017
People who are unable to walk and are using wheel chairs exert great amounts of energy using phys... more People who are unable to walk and are using wheel chairs exert great amounts of energy using physical strength to turn and steer the wheels. With eyesight being their guide, the disabled would save energy and could use their hands and arms for other activities. The purpose of this paper is to develop a wheelchair that will be controlled by the eyes of the person seated in the wheelchair. This will allow people without full use of their limbs the freedom to move about and provide a level of autonomy. The paper will consist of three main parts.
International Journal of Advance Research and Innovative Ideas in Education, 2017
People who are unable to walk and are using wheel chairs exert great amounts of energy using phys... more People who are unable to walk and are using wheel chairs exert great amounts of energy using physical strength to turn and steer the wheels. With eyesight being their guide, the disabled would save energy and could use their hands and arms for other activities. The purpose of this paper is to develop a wheelchair that will be controlled by the eyes of the person seated in the wheelchair. This will allow people without full use of their limbs the freedom to move about and provide a level of autonomy. The paper will consist of three main parts.
International Journal of Scientific Research in Science and Technology
Electroencephalogram (EEG) signals represent functioning of the brain, and assist in identificati... more Electroencephalogram (EEG) signals represent functioning of the brain, and assist in identification of multiple brain-related disorders including Epilepsy, Alzheimer’s disease, emotional states, Parkinson’s disease, strokes, etc. To design such models, a wide variety of machine learning & deep learning approaches are proposed by researchers. But these approaches use a black-box generic model for EEG classification, due to which their scalability is limited. To enhance this scalability, a novel feature augmented extraction model is proposed in this text. The model uses wavelet compression on input EEG data, and processes the compressed signal using a variance-based selection approach. Due to which, the model is capable of low-delay, and high accuracy classification for different brain-diseases. It evaluates wavelet-based features from input EEG data, and performs ensemble feature selection for improving feature variance. The wavelet features are able to convert input EEG data into di...
Uploads
Papers by dinesh chandak