Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery
More than one billion people face disabilities worldwide, according to the World Health Organization (WHO). In Sri Lanka, there are thousands of people suffering from a variety of disabilities, especially hand disabilities, due to the civil war in the country. The Ministry of Health of Sri Lanka rep...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Human-Computer Interaction |
| Online Access: | http://dx.doi.org/10.1155/2021/5515759 |
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| author | H. M. K. K. M. B. Herath W.R. de Mel |
| author_facet | H. M. K. K. M. B. Herath W.R. de Mel |
| author_sort | H. M. K. K. M. B. Herath |
| collection | DOAJ |
| description | More than one billion people face disabilities worldwide, according to the World Health Organization (WHO). In Sri Lanka, there are thousands of people suffering from a variety of disabilities, especially hand disabilities, due to the civil war in the country. The Ministry of Health of Sri Lanka reports that by 2025, the number of people with disabilities in Sri Lanka will grow by 24.2%. In the field of robotics, new technologies for handicapped people are now being built to make their lives simple and effective. The aim of this research is to develop a 3-finger anatomical robot hand model for handicapped people and control (flexion and extension) the robot hand using motor imagery. Eight EEG electrodes were used to extract EEG signals from the primary motor cortex. Data collection and testing were performed for a period of 42 s timespan. According to the test results, eight EEG electrodes were sufficient to acquire the motor imagery for flexion and extension of finger movements. The overall accuracy of the experiments was found at 89.34% (mean = 22.32) at the 0.894 precision. We also observed that the proposed design provided promising results for the performance of the task (grab, hold, and release activities) of hand-disabled persons. |
| format | Article |
| id | doaj-art-7621a9fe07394aa89528dae0a21bcbba |
| institution | Kabale University |
| issn | 1687-5893 1687-5907 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Human-Computer Interaction |
| spelling | doaj-art-7621a9fe07394aa89528dae0a21bcbba2025-02-03T01:24:51ZengWileyAdvances in Human-Computer Interaction1687-58931687-59072021-01-01202110.1155/2021/55157595515759Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor ImageryH. M. K. K. M. B. Herath0W.R. de Mel1Department of Mechanical Engineering, The Open University of Sri Lanka, Colombo, Sri LankaDepartment of Materials and Mechanical Technology, University of Sri Jayewardenepura, Nugegoda, Sri LankaMore than one billion people face disabilities worldwide, according to the World Health Organization (WHO). In Sri Lanka, there are thousands of people suffering from a variety of disabilities, especially hand disabilities, due to the civil war in the country. The Ministry of Health of Sri Lanka reports that by 2025, the number of people with disabilities in Sri Lanka will grow by 24.2%. In the field of robotics, new technologies for handicapped people are now being built to make their lives simple and effective. The aim of this research is to develop a 3-finger anatomical robot hand model for handicapped people and control (flexion and extension) the robot hand using motor imagery. Eight EEG electrodes were used to extract EEG signals from the primary motor cortex. Data collection and testing were performed for a period of 42 s timespan. According to the test results, eight EEG electrodes were sufficient to acquire the motor imagery for flexion and extension of finger movements. The overall accuracy of the experiments was found at 89.34% (mean = 22.32) at the 0.894 precision. We also observed that the proposed design provided promising results for the performance of the task (grab, hold, and release activities) of hand-disabled persons.http://dx.doi.org/10.1155/2021/5515759 |
| spellingShingle | H. M. K. K. M. B. Herath W.R. de Mel Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery Advances in Human-Computer Interaction |
| title | Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery |
| title_full | Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery |
| title_fullStr | Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery |
| title_full_unstemmed | Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery |
| title_short | Controlling an Anatomical Robot Hand Using the Brain-Computer Interface Based on Motor Imagery |
| title_sort | controlling an anatomical robot hand using the brain computer interface based on motor imagery |
| url | http://dx.doi.org/10.1155/2021/5515759 |
| work_keys_str_mv | AT hmkkmbherath controllingananatomicalrobothandusingthebraincomputerinterfacebasedonmotorimagery AT wrdemel controllingananatomicalrobothandusingthebraincomputerinterfacebasedonmotorimagery |