Abstract
Vital signals like Electroencephalogram (EEG), Electrooculography (EOG), and Electroretinogram (ERG) have been used in many areas due to their effectiveness and accuracy. Electrodes can obtain the signals, and then they can be amplified and processed. This study helps people with reduced mobility like paralysis and Amyotrophic Lateral Sclerosis (ALS) using EOG signals. EOG signal is effective in this case because these people can use their eyes without any obstacles. EOG aid system can enable them to rely on themselves in the use of smart devices. This is one of the first studies to present a detailed analysis of the signal acquisition and processing and the results were promising with a result that scored 95% rate.
Highlights
Helping people with disabilities is one of the most important and humane jobs
The experiment on people with reduced mobility like paralysis and (ALS) using EOG signals is effective in this case because these people can use their eyes without any obstacles, which allows them to extend their physical capabilities with the help of technology
There have been useful case studies in this field that discussed various methodologies and applications, for instance, the article written by Manuel Merino (2010) [1], included developing an EOG signal processing algorithm method to detect the direction of eye movements
Summary
Helping people with disabilities is one of the most important and humane jobs. Supporting disabled people can help transient them from an inactive status in the community to active individuals who can perform daily activities independently and eventually contribute to society's building. The experiment on people with reduced mobility like paralysis and (ALS) using EOG signals is effective in this case because these people can use their eyes without any obstacles, which allows them to extend their physical capabilities with the help of technology. Such as giving commands to a computer through a mouse cursor without having direct physical contact with it. Another article written by Octavio Rivera, et al (2013) [2], used an algorithm that captures the EOG signal and converts this vital signal into a mechanical one [3], which helped study and design a motorized wheelchair with EOG control for disabled people. Vertical and horizontal eye movement is processed by a dedicated microprocessor device, and another customized
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