OFFLINE STUDY FOR IMPLEMENTING HUMAN COMPUTER INTERFACE FOR ELDERLY PARALYZED PATIENTS USING ELECTROOCULOGRAPHY AND NEURAL NETWORKS

2019 ◽  
Vol 6 (3) ◽  
pp. 1 ◽  
Author(s):  
K. Maheswari ◽  
S. Ramkumar ◽  
K.Sathesh Kumar ◽  
P.Packia Amutha Priya ◽  
G. Emayavaramban ◽  
...  
Keyword(s):  
Neural Networks ◽  
Computer Interface ◽  
Human Computer Interface

Offline study for implementing human computer interface for elderly paralysed patients using electrooculography and neural networks

2020 ◽  
Vol 7 (1/2/3) ◽  
pp. 306 ◽  
Author(s):  
S. Ramkumar ◽  
K. Sathesh Kumar ◽  
K. Maheswari ◽  
P. Packia Amutha Priya ◽  
G. Emayavaramban ◽  
...  
Keyword(s):  
Neural Networks ◽  
Computer Interface ◽  
Human Computer Interface

Design of an Accelerometer-Controlled Myoelectric Human Computer Interface

2011 ◽  
Vol 403-408 ◽  
pp. 3973-3979
Author(s):  
Anusha Lalitha ◽  
Nitish V. Thakor
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Artificial Neural Networks ◽  
Position Control ◽  
Computer Interface ◽  
Input Device ◽  
Two Dimensional ◽  
Human Computer Interface ◽  
Finger Movements ◽  
Mouse Cursor

The purpose of this study is to develop an alternate in-air input device which is intended to make interaction with computers easier for amputees. This paper proposes the design and utility of accelerometer controlled Myoelectric Human Computer Interface (HCI). This device can function as a PC mouse. The two dimensional position control of the mouse cursor is done by an accelerometer-based method. The left click and right click and other extra functions of this device are controlled by the Electromyographic (EMG) signals. Artificial Neural Networks (ANNs) are used to decode the intended movements during run-time. ANN is a pattern recognition based classification. An amputee can control it using phantom wrist gestures or finger movements.

SEMG for Human Computer Interface Using Ann to Navigate Wheel Chair

2010 ◽  
Vol 5 (2) ◽  
pp. 11-19
Author(s):  
V. Rajesh ◽  
P. Rajesh Kumar
Keyword(s):  
Neural Networks ◽  
Muscle Activity ◽  
Back Propagation ◽  
Computer Interface ◽  
Hand Gesture ◽  
Human Computer Interface ◽  
Prime Mover ◽  
Hand Gestures ◽  
Propagation Analysis ◽  
Wheel Chair

This paper presents an approach to identify hand gestures with muscle activity separated from electromyogram (EMG) using Back Propagation analysis with the goal of using hand gestures for human-computer interaction. While there are a number of previous reported works where EMG has been used to identify movement, the limitation of these works is that the systems are suitable for gross actions and when there is one prime-mover muscle involved. This paper reports overcoming the difficulty by using independent component analysis to separate muscle activity from different muscles and classified using back propagation neural networks. The experimental results show that the system was accurately able to identify the hand gesture using this technique (95%). The advantage of this system is that it is easy to train one to use it and can easily be implemented in real time.

Neural networks for classification and recognition of individual users in adaptive human-computer interface

2002 ◽  
Author(s):  
M. Dimitrova ◽  
M. Hubert ◽  
D. Boyadjiev ◽  
A. Nabout ◽  
N.J. Zaprianov ◽  
...  
Keyword(s):  
Neural Networks ◽  
Computer Interface ◽  
Human Computer Interface

MESO-Adaptation Based on Model Oriented Reengineering Process for Human-Computer Interface (MESOMORPH)

2004 ◽  
Author(s):  
Melody Moore ◽  
David Yu ◽  
Cen Shi ◽  
Gnan Hoang
Keyword(s):  
Computer Interface ◽  
Human Computer Interface

Tactical Tomahawk Weapon Control System v6 Land Attack Combat System Prototype Human-Computer Interface

2004 ◽  
Author(s):  
James Pharmer ◽  
Kevin Cropper ◽  
Jennifer McKneely ◽  
Earl Williams
Keyword(s):  
Control System ◽  
Computer Interface ◽  
Human Computer Interface ◽  
System Prototype

Human–computer interface design issues for a multi-cultural and multi-lingual English speaking country — Botswana

2001 ◽  
Vol 13 (4) ◽  
pp. 497-512 ◽  
Author(s):  
E.A Onibere ◽  
S Morgan ◽  
E.M Busang ◽  
D Mpoeleng
Keyword(s):  
Interface Design ◽  
Computer Interface ◽  
Human Computer Interface ◽  
Design Issues ◽  
English Speaking

scholarly journals Addressing the eye fixation problem in gaze tracking for human computer interface using the vestibulo-ocular reflex

2020 ◽  
Vol 21 ◽  
pp. 100488
Author(s):  
Adam Pantanowitz ◽  
Kimoon Kim ◽  
Chelsey Chewins ◽  
Isabel N.K. Tollman ◽  
David M. Rubin
Keyword(s):  
Computer Interface ◽  
Human Computer Interface ◽  
Gaze Tracking ◽  
Eye Fixation ◽  
Ocular Reflex ◽  
Vestibulo Ocular Reflex
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