AN EYE INPUT DEVICE FOR PERSONS WITH THE MOTOR NEURON DISEASES

2013 ◽  
Vol 25 (01) ◽  
pp. 1350006 ◽  
Author(s):  
Chung-Min Wu ◽  
Chueh Yu Chuang ◽  
Ming-Che Hsieh ◽  
Shei-Hsi Chang
Keyword(s):  
Motor Neuron ◽  
Recognition Rate ◽  
Disabled Persons ◽  
Recognition Algorithm ◽  
Input Device ◽  
Motor Neuron Diseases ◽  
The Disabled ◽  
Novice Users ◽  
Fuzzy Recognition ◽  
Logic Level

This study proposes an Eye input device by electro-oculogram (EOG) recognition for individuals with the motor neuron diseases (MNDs). In this study, the level of the unstable EOG signal is transformed into standard logic level signal by using the baseline tracing algorithm. The standard logic level signal is used as Morse code sequences which is recognized by the sliding fuzzy recognition algorithm embedded in a microprocessor. The result demonstrates that the unstable EOG signals can be successfully transformed into alphanumeric characters and the recognition rate is approximately 99% for the novice users. Accordingly, we designed an inexpensive user computer interface for helping the disabled persons to communicate with others, the user can input text with their eyes to access the computer and household appliances, such as lamps, fans and TV sets.

scholarly journals Vision Controlled Robotic System

2019 ◽  
Vol 9 (1S) ◽  
pp. 188-191
Keyword(s):  
Motor Neuron ◽  
Touch Screen ◽  
Dc Motor ◽  
Disabled Persons ◽  
Robotic System ◽  
Future Generations ◽  
Eye Tracker ◽  
Highly Efficient ◽  
The World ◽  
The Disabled

The field of robotics is changing the world in which we live today and the future generations will be largely served by various robotic services which will be highly efficient and dynamic. Offering affordable and efficient robotic services to the society is the need of the hour and this project is highly inclined towards this theme. The latest touch screen technology and the use of mechanical components like joysticks can be replaced by Gesture Controlled Robotics. The product is aimed at improving the conditions of motor neuron disabled persons using OpenCV libraries of Processing3 software and Arduino Uno (Atmega328 microcontroller). The vision of the disabled person is sensed using a Glass Eye Tracker and every 25th frame of the picture (here it is the pupil) is sent to the Processing3 software. This software processes the image based on the algorithm. The ports of Processing3 software and Arduino are serially communicated. Now the Arduino performs the output part with the help of L293D motor driver and 24V DC motor.

scholarly journals Design of a Code-Maker Translator Assistive Input Device with a Contest Fuzzy Recognition Algorithm for the Severely Disabled

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Chung-Min Wu ◽  
Jyun-Slan Liou
Keyword(s):  
Modular Design ◽  
Physical Disabilities ◽  
Recognition Algorithm ◽  
Computer Applications ◽  
Input Device ◽  
Tablet Pcs ◽  
Morse Code ◽  
Brain Artery ◽  
Fuzzy Recognition ◽  
E Mail

This study developed an assistive system for the severe physical disabilities, named “code-maker translator assistive input device” which utilizes a contest fuzzy recognition algorithm and Morse codes encoding to provide the keyboard and mouse functions for users to access a standard personal computer, smartphone, and tablet PC. This assistive input device has seven features that are small size, easy installing, modular design, simple maintenance, functionality, very flexible input interface selection, and scalability of system functions, when this device combined with the computer applications software or APP programs. The users with severe physical disabilities can use this device to operate the various functions of computer, smartphone, and tablet PCs, such as sending e-mail, Internet browsing, playing games, and controlling home appliances. A patient with a brain artery malformation participated in this study. The analysis result showed that the subject could make himself familiar with operating of the long/short tone of Morse code in one month. In the future, we hope this system can help more people in need.

scholarly journals A Motion-based User Interface for the Control of Virtual Humans Performing Sports

2011 ◽  
Vol 10 (3) ◽  
pp. 1-8
Author(s):  
Xiubo Liang ◽  
Zhen Wang ◽  
Weidong Geng ◽  
Franck Multon
Keyword(s):  
User Interface ◽  
Markov Models ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Interactive Simulation ◽  
Virtual Humans ◽  
Novel Approach ◽  
Human Computer Interfaces ◽  
Average Recognition Rate ◽  
Novice Users

Traditional human computer interfaces are not intuitive and natural for the choreography of human motions in the field of VR and video games. In this paper we present a novel approach to control virtual humans performing sports with a motion-based user interface. The process begins by asking the user to draw some gestures in the air with a Wii Remote. The system then recognizes the gestures with pre-trained hidden Markov models. Finally, the recognized gestures are employed to choreograph the simulated sport motions of a virtual human. The average recognition rate of the recognition algorithm is more than 90% on our test set of 20 gestures. Results on the interactive simulation of several kinds of sport motions are given to show the efficiency and interestingness of our system, which is easy-to-use especially for novice users

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

Correlate the NCS and Needle EMG of Motor Neuron Diseases Using FIS System

2020 ◽  
Author(s):  
Amit Mayavanshi ◽  
Himanshu A Patel ◽  
Palak A Parikh
Keyword(s):  
Motor Neuron ◽  
Motor Neuron Diseases

Machine-Printed Invoice Number Based on Fuzzy Recognition

2012 ◽  
Vol 214 ◽  
pp. 705-710 ◽  
Author(s):  
Xiao Ping Xian
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Recognition Rate ◽  
Real System ◽  
Recognition Method ◽  
Recognition Time ◽  
Recognition Ability ◽  
System Requirements ◽  
Fuzzy Recognition ◽  
Detection And Separation

A new fuzzy recognition method of machine-printed invoice number based on neural network is presented. This method includes ten links: invoice number detection and separation of right on top of invoice, binarization, denoising, incline correction, extraction of invoice code numerals, window scaling, location standardization, thinning, extraction of numeral feature and fuzzy recognition based on BP neural network. Through testing, the recognition rate of this method can be over 99%.The recognition time of characters for character is less than 1 second, which means that the method is of more effective recognition ability and can better satisfy the real system requirements.

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