Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled
The human–machine interface with head control can be applied in many domains. This technology has the valuable application of helping people who cannot use their hands, enabling them to use a computer or speak. This study combines several image processing and computer vision technologies, a digital...
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doaj-bfb02c848f49411fb910f69601e89b792020-11-25T03:50:54ZengMDPI AGApplied Sciences2076-34172020-10-01107005700510.3390/app10197005Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely DisabledChe-Ming Chang0Chern-Sheng Lin1Wei-Cheng Chen2Chung-Ting Chen3Yu-Liang Hsu4Program of Electrical and Communications Engineering, Feng Chia University, Taichung 40724, TaiwanDepartment of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanMaster’s Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung 40724, TaiwanDepartment of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei 106335, TaiwanDepartment of Automatic Control Engineering, Feng Chia University, Taichung 40724, TaiwanThe human–machine interface with head control can be applied in many domains. This technology has the valuable application of helping people who cannot use their hands, enabling them to use a computer or speak. This study combines several image processing and computer vision technologies, a digital camera, and software to develop the following system: image processing technologies are adopted to capture the features of head motion; the recognized head gestures include forward, upward, downward, leftward, rightward, right-upper, right-lower, left-upper, and left-lower; corresponding sound modules are used so that patients can communicate with others through a phonetic system and numeric tables. Innovative skin color recognition technology can obtain head features in images. The barycenter of pixels in the feature area is then quickly calculated, and the offset of the barycenter is observed to judge the direction of head motion. This architecture can substantially reduce the distraction of non-targeted objects and enhance the accuracy of systematic judgment.https://www.mdpi.com/2076-3417/10/19/7005computer visionhead gesturesnumeric tables |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Che-Ming Chang Chern-Sheng Lin Wei-Cheng Chen Chung-Ting Chen Yu-Liang Hsu |
spellingShingle |
Che-Ming Chang Chern-Sheng Lin Wei-Cheng Chen Chung-Ting Chen Yu-Liang Hsu Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled Applied Sciences computer vision head gestures numeric tables |
author_facet |
Che-Ming Chang Chern-Sheng Lin Wei-Cheng Chen Chung-Ting Chen Yu-Liang Hsu |
author_sort |
Che-Ming Chang |
title |
Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled |
title_short |
Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled |
title_full |
Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled |
title_fullStr |
Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled |
title_full_unstemmed |
Development and Application of a Human–Machine Interface Using Head Control and Flexible Numeric Tables for the Severely Disabled |
title_sort |
development and application of a human–machine interface using head control and flexible numeric tables for the severely disabled |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2020-10-01 |
description |
The human–machine interface with head control can be applied in many domains. This technology has the valuable application of helping people who cannot use their hands, enabling them to use a computer or speak. This study combines several image processing and computer vision technologies, a digital camera, and software to develop the following system: image processing technologies are adopted to capture the features of head motion; the recognized head gestures include forward, upward, downward, leftward, rightward, right-upper, right-lower, left-upper, and left-lower; corresponding sound modules are used so that patients can communicate with others through a phonetic system and numeric tables. Innovative skin color recognition technology can obtain head features in images. The barycenter of pixels in the feature area is then quickly calculated, and the offset of the barycenter is observed to judge the direction of head motion. This architecture can substantially reduce the distraction of non-targeted objects and enhance the accuracy of systematic judgment. |
topic |
computer vision head gestures numeric tables |
url |
https://www.mdpi.com/2076-3417/10/19/7005 |
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