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This paper presents a biometric authentication system using brain signature to identify individuals. Research on brain signals has shown that each individual has a unique brain wave pattern for similar activities. EEG signals are recorded for three mental tasks from different subjects to extract the distinctive brain signature of the individual. 15 subjects(More)
Motor imagery is the mental simulation of a motor act which can be used to design brain machine interfaces [BMI]. A BMI is a digital communication system, which connects the human brain directly to an external device bypassing the peripheral nervous system and muscular system. Thus a BMI opens up possibilities for a new communication channel for people with(More)
Patients with neurodegenerative diseases loose all motor movements including impairment of speech, leaving the patients totally locked-in. One possible option for rehabilitation of such patients is using a brain machine interfaces (BMI) which uses their active cognition capabilities to control external devices and their environment. BMIs are designed using(More)
In this paper we present a stereo vision system for segmentation of partially occluded objects and computation of object grasping point in bin picking environments. The stereo vision system was interfaced with an adept SCARA robot to perform bin picking operations. Most researches on bin picking involve combination of vision and force sensors, however in(More)
Hypoacusis is the most prevalent sensory disability in the world and consequently, it can lead to impede speech in human beings. One best approach to tackle this issue is to conduct early and effective hearing screening test using Electroencephalogram (EEG). EEG based hearing threshold level determination is most suitable for persons who lack verbal(More)
The computation of a mobile robot position and orientation is a common task in the area of computer vision and image processing. For a successful application, it is important that the position and orientation of a mobile robot must be determined properly. In this paper, a simple procedure for determining the orientation of the mobile robot using two cameras(More)
A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is based on only two electrodes and operated by motor imagery of four states. A recurrent neural classifier is proposed for the(More)
A Brain Machine Interface is a communication system which connects the human brain activity to an external device bypassing the peripheral nervous system and muscular system. It provides a communication channel for the people who are suffering with neuromuscular disorders such as amyotrophic lateral sclerosis, brain stem stroke, quadriplegics and spinal(More)
Classification of EEG mental task signals is a technique in the design of Brain machine interface [BMI]. A BMI can provide a digital channel for communication in the absence of the biological channels and are used to rehabilitate patients with neurodegenerative diseases, a condition in which all motor movements are impaired including speech leaving the(More)
  • C. R. Hema
  • 2010 6th International Colloquium on Signal…
  • 2010
Recognition of Motor Imagery (MI) using a dynamic cascade feed-forward neural network (CFNN) is presented. MI is the mental simulation of a motor act that includes preparation for movement and mental operations of motor representations implicitly or explicitly. The ability of an individual to control his EEG through imaginary motor tasks enables him to(More)