Solar-Rechargeable Brain-Controlled Wheel-Chair for Paralytic Patients Using Emotiv Epoc+

Ahmad Muhammad Faruk, A. Bakry Hussein, Marwan A. Rashed, Sohair F. Rezeka, Mohamed El-Habrouk

Abstract


This paper presents the mechanical design and construction of the solar power rechargeable brain controlled wheel-chair with signal acquisition, feature extraction, processing and control methods. It provides the research performed on building a relatively cheap solar rechargeable brain controlled wheel-chair. In the proposed system, the authors aim to augment the abilities of handicapped people such as moving from one place to another, standing up, as well as hands-free control through several artificial techniques. In order to accomplish this task, the proposed system reads and analyses the patient’s brain waves (EEG signals) and turns them into actions to control the proposed wheel chair for moving and standing.

The signals acquired from the EEG were used after filtration, feature extraction, and classification. Furthermore, the signals are passed to the control system of the wheel-chair which consists of motor drivers and linear actuators. An alternative Joystick input is also present in the proposed system for normal use of the wheel-chair. Processing and control are all handled by an Intel based computer and an Arduino Mega 2560-R3 board. The Integration of the system is based on a PID controller and complementary filters leading to high efficient wheel-chair operation.

The system improves the power efficiency by using two solar panels fitted to the rooftop of the wheel-chair in order to trickle charge the batteries of the wheel-chair when it is present under appropriate solar irradiance for the purpose of extending the operating time of the wheel-chair batteries. This led to almost an extra hour of usage as compared to over three hours of usage without the solar panel. The electrical and mechanical designs were all constrained by economical means as well as market availability. The overall cost of the system was around $2000.


Keywords


Electroencephalogram (EEG); Brain Control Interface (BCI); Arduino Mega 2560-R3; Wheel-chair; Solar Powered; Paralytic Patients;

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DOI: http://dx.doi.org/10.21535%2Fijrm.v5i1.984

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