Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient

Brain-Computer Interface (BCI) is a direct communication pathway between a human and external device. Integrated wheelchair controlled with human brainwave using a BCI system was designed and studied to help people with disabilities, especially for people who suffer from motor disorders such as peripheral nerves and muscles. The invention aims to develop an integrated wheelchair which can be controlled by a paralyzed person using only a single electrode. In this research, the efficiency of the brainwave integrated wheelchair has been improved using human attention value, blink detection and eyebrow movement of the user to control the wheelchair. An encephalography (EEG) device called Mindwave Mobile Plus (MW+) has been employed to obtain attention value for the wheelchair movement, eye blink to change the mode of the wheelchair to move forward (F), to the right (R), backward (B) and to the left (L). Eyebrow movement was used to stop the wheelchair when using human brainwave as the signal quality value of 26 or 51 is produced. Analysis on the human attention value in different gender and age category also has been done. Male is easier to focus compared to the female. Teenagers have the highest attention value followed by the children while the adults have the lowest attention value among all age categories studied. The EEG of the human were analyzed by using Arduino Integrated Development Environment (IDE) software. The development of the integrated wheelchair is improved by using human’s attention value, blink detection and eyebrow movement and the threshold value of the attention level was set according to the gender and age category of the user. From the results and analysis, the threshold value for male children is 60, male teenager (70), male adult (40) while for the female children is 50, female teenager (50) and female adult (30)

Brainwave analysis for robot movement depending on age and sex differences

A Brain-Computer Interface (BCI) is a direct communication pathway between a human and external device. This system is very useful especially for disabled people as their brainwave still can emit electrical activity and can move the machine even with severe motor impairments. This research aims to investigate the brain waves produced by humans in terms of attention level for robot movement based on sex and age category of children (6-12 years), teenagers (18-25 years old) and adult (30 years and over). An Electroencephalography (EEG) device called Neurosky Mindwave Mobile has been used to obtain brainwave signals produced by humans. There were five aspects of robot movement namely forward (F), right (R), left (L), backward (B) and stop (S). From the analysis, the subject is less focus when doing the backward movement compared to another aspect of movements. Based on sex difference, the male has a higher attention level than female in every aspect of movement except for the left movement. The age group that has the highest attention level is teenager and the lowest is adult. It can be concluded that the attention level produced by human varies depending on age and sex difference of the individual itself

The Brain Wave Analysis for Robot Movement Using One Electrode

Brain-Computer Interface (BCI) is a system that uses a network of communication between the nervous system of the human brain with machines or robots. Through this system, people will move the machine without using a computer or a member of his body. The system is very useful especially for people with disabilities such as paralysis and stroke. The aim of this project is to create a study conducted on brain waves produced by humans according to age category of children (6-12 years), teenagers (18-22 years old) and adult (30 years and over). A device called Neurosky Mindwave Mobile is a single electroencephalogram (EEG) electrode. Each respondent was required to use the device to test the resulting attention when they were thinking of the robot movements. There were five thoughts of robot movement; forward (F), right (R), left (L), backward (B) and stop (S). The extracted levels from Neurosky ThinkGear software were recorded and set as an input command to move a robot. Through the analysis, the age group that has the highest attention level is teenagers and the lowest is women. It can be concluded that the level of attention that resulted in moving the robot varies according to an individual's age and gender category. Major implications in doing this project were to move the robot using only the power of the mind

Analysis of Human’s Attention Value in Gender and Age Category using Mindwave Mobile

Brainwave-controlled robot using a Brain-Computer Interface (BCI) system was designed and studied to help people with disabilities, especially for people who suffer from motor disorders such as Amyotrophic Lateral Sclerosis (ALS). BCI is a communication system that does not depend on peripheral nerves and muscles. However, the integrated robot controlled by the human mind has less efficiency due to the different type of brainwaves generated by a user. The purpose of this paper is to analyze the human’s attention value in age and gender category for improving the mind-controlled robot movement. An electroencephalography (EEG) device called Mindwave Mobile is used to get the attention value generated by humans in the different type of gender (male, female) and age category (children, teenager, adult). There are five aspects of thought movement generated by human which is forward (F), right (R), left (L), backward (B) and stop (S). For statistical analysis, the main effect of gender on the attention value was analyzed by using independent sample t-test and the main effect of age category was analyzed by oneway ANOVA test while the interaction effect between these two factors was analyzed by two-way ANOVA test. The results show that male has a higher attention value than female for every aspect of thought movement except for the left and backward movement. This is due to the different size of the frontal lobe in gender. For the age category, the teenager is more focused than children and adult while the adult has the lowest attention value in every aspect of the movement. From the analysis, only in the forward movement shows that there was a significantly different in gender difference while there was no significant difference in the main effect of age category and the interaction effect between the gender and age category on the attention value for every movement. By doing this research, the movement of a mindcontrolled robot can be improved by setting the threshold value depending on the gender and age category of the user

Wheelchair controlled by human brainwave using brain computer interface system for paralyzed patient

Integrated wheelchair controlled by human brainwave using a brain-computer interface (BCI) system was designed to help disabled people. The invention aims to improve the development of integrated wheelchair using a BCI system, depending on the ability individual brain attention level. An electroencephalography (EEG) device called mindwave mobile plus (MW+) has been employed to obtain the attention value for wheelchair movement, eye blink to change the mode of the wheelchair to move forward (F), to the right (R), backward (B) and to the left (L). Stop mode (S) is selected when doing eyebrow movement as the signal quality value of 26 or 51 is produced. The development of the wheelchair controlled by human brainwave using a BCI system for helping a paralyzed patient shows the efficiency of the brainwave integrated wheelchair and improved using human attention value, eye blink detection and eyebrow movement. Also, analysis of the human attention value in different gender and age category also have been done to improve the accuracy of the brainwave integrated wheelchair. The threshold value for male children is 60, male teenager (70), male adult (40) while for female children is 50, female teenager (50) and female adult (30)