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Electroencephalogram (EEG) Controlled Anatomical Robot Hand

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Abstract

According to the World Health Organization (WHO), over one billion people are globally experience disabilities. In Sri Lanka, there exist thousands of people who are suffering from varieties of disabilities. Sri Lankan Ministry of Health state that the number of disabled persons in Sri Lanka will be increased by 24.2% by 2025. The aim of this project is to develop an EEG (Electroencephalogram) control robot hand model which is working same as the anatomy of the human hand.
Student Academic Conference - 2018 Faculty of Engineering Technology
The Open University of Sri Lanka
28th August 2019
- 73 - The Open University of Sri Lanka, Proceedings of FET Student Academic Conference 2018
ELECTROENCEPHALOGRAM (EEG) CONTROLLED
ANATOMICAL ROBOT HAND
HMKKMB Herath,WR de Mel
Department of Mechanical Engineering, The Open University of Sri Lanka
kasunherathlive@gmail.com
ABSTRACT
Today, millions of people are suffering due to the lack of a functional arm to perform tasks. In Sri
Lanka, there exist thousands of people who are suffering from varieties of disabilities. The Sri Lankan
Ministry of Health states that the number of disabled persons in Sri Lanka will be increased by 24.2%
by 2025. The aim of this project is to develop an EEG (Electroencephalogram) control robot hand
model which is working the same as the anatomy of the human hand.
The primary motor cortex (M1) is mainly responsible for the finger movements of the human hand. For
this project, eight EEG electrodes were attached to cover the primary motor cortex of the human brain
(FC3, FC4, C1, C2, C3, C4, Cz, and CPZ). The MATLAB developed signal pre-processing function
was used to process the EEG signals to detect the presence of 50Hz line noise, Removal of the 0Hz
offset, Suppression of high frequency noise and very low frequency noise. MATLAB Classifier
Training plugin was used to classify signals according to the motor imagery. According to the outputs
of Classifier Trainer, A set of commands were generated within the Decision Controller function.
Motor-Driven plastic strings were used to set the bending angle of the DIP, PIP and MCP joints of the
robot hand model according to the instruction given by Decision Controller.
According to the observations and results, eight electrodes are sufficient to catch the motor imagery for
flexion and extension of finger movements. But movements like a real human hand are not possible
with this practice. The flexion angle for the distal, intermediate and proximal phalanges cannot be
captured accurately.
Keywords: EEG Sensors, Bio Signal, Robotic Hand, Bio signal Control, Anatomy, Primary motor
cortex, Motor imagery, MATLAB, Signal Processing
... The elderly population, identified as those aged 65 and over, has risen significantly over the past 45 years (Maduwage, 2019) due to advancements and improved access to healthcare services (Maduwage, 2019). Fourteen percent of the world's population is now older than 65 (Herath & de Mel, 2019) for the first time in history. In the European Union, 11.5% of the population was old in 1970. ...
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... The elderly population, identified as those aged 65 and over, has risen significantly over the past 45 years (Maduwage, 2019) due to advancements and improved access to healthcare services (Maduwage, 2019). Fourteen percent of the world's population is now older than 65 (Herath & de Mel, 2019) for the first time in history. In the European Union, 11.5% of the population was old in 1970. ...
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... The elderly population, identified as those aged 65 and over, has risen significantly over the past 45 years (Maduwage, 2019) due to advancements and improved access to healthcare services (Maduwage, 2019). Fourteen percent of the world's population is now older than 65 (Herath & de Mel, 2019) for the first time in history. In the European Union, 11.5% of the population was old in 1970. ...
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... The elderly population, identified as those aged 65 and over, has risen significantly over the past 45 years (Maduwage, 2019) due to advancements and improved access to healthcare services (Maduwage, 2019). Fourteen percent of the world's population is now older than 65 (Herath & de Mel, 2019) for the first time in history. In the European Union, 11.5% of the population was old in 1970. ...
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... The elderly population, identified as those aged 65 and over, has risen significantly over the past 45 years (Maduwage, 2019) due to advancements and improved access to healthcare services (Maduwage, 2019). Fourteen percent of the world's population is now older than 65 (Herath & de Mel, 2019) for the first time in history. In the European Union, 11.5% of the population was old in 1970. ...
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Full-text available
The elderly population, identified as those aged 65 and over, has risen significantly over the past 45 years due to advancements and improved access to healthcare services. Fourteen percent of the world’s population is now older than 65 for the first time in history. In the European Union, 11.5% of the population was old in 1970. But the figure had risen to 20.5% by 2016. All signs are that this pattern will continue. The implications are that an ever-growing number of people face disabilities such as reduced mobility or diminished cognitive ability, all sorts of chronic diseases, and very often loneliness and social isolation. Coping with these clinical and social concerns is often associated with high and dynamic costs and realistic difficulties. Robots were primarily built for routine, rough, or other dangerous activities in factories and hazardous field conditions until recently. In these implementations, robots did not occupy the same workspace as humans, and all communications were facilitated by machine interfaces, control panels, joysticks, etc. However, the development of service robots, i.e. robots conducting functional human or equipment roles outside of industrial automation, has been rendered feasible by technical improvements. Because service robots are expected to operate in individuals’ vicinity, there is also a need for social interaction skills. There are many difficulties in designing physical systems that can work virtually near us and have motivated creating a dedicated discipline known as human-robot interaction.
... Due to population aging and the country's civil war, the prevalence of disability in Sri Lanka rose between 1981 and 2001 [1,2]. In the 2001 census, it was estimated that 0.3 million people had a disability. ...
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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. e 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. e 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. e 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.
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