A Wheelchair Control System Using Human-Machine Interaction: Single-Modal and Multimodal Approaches

Abstract

Recent research studies showed that brain-controlled systems/devices are breakthrough technology. Such devices can provide disabled people with the power to control the movement of the wheelchair using different signals (e.g. EEG signals, head movements, and facial expressions). With this technology, disabled people can remotely steer a wheelchair, a computer, or a tablet. This paper introduces a simple, low-cost human-machine interface system to help chaired people to control their wheelchair using several control sources. To achieve this paper’s aim, a laptop was installed on a wheelchair in front of the sitting person, and the 14-electrode Emotiv EPOC headset was used to collect the person’s head impressions from the skull surface. The superficially picked-up signals, containing the brain thoughts, head gestures, and facial emotions, were electrically encoded and then wirelessly sent to a personal computer to be interpreted and then translated into useful control instructions. Using these signals, two wheelchair control modes were proposed: automatic (using single-modal and multimodal approaches) and manual control. The automatic mode controller was accomplished using a software controller (Arduino), whereas a simple hardware controller was used for the manual mode. The proposed solution was designed using wheelchair, Emotiv EPOC EEG headset, Arduino microcontroller, and Processing language. It was then tested by totally chaired volunteers under different levels of trajectories. The results showed that the person’s thoughts can be used to seamlessly control his/her wheelchair and the proposed system can be configured to suit many levels and degrees of disability.

Development of an Autonomous Wheelchair for The Disabled and Performance Analysis Using ANFIS Model

“…Recall that Weight, (1) This implies that the frame must be able to carry a load of 981 N , (Khurmi & Gupta, 2005)…”

“…Selfpropelled wheel-chairs with some form of intelligence such as ability to measure and regulate velocity, sense the presence of obstacles amongst others is gradually becoming the focus of the literature on interactive wheel-chairs. According to [1] there are certain categories of people who have not been able to fully benefit and fit into the social groups since they cannot easily access basic skill acquisition centres due to unavailability of self-mobility devices. This has somewhat affected quite a number of paraplegics who very often take to street begging for survival in most developing countries.…”

Design of Control System of Human-Computer Interactive Agv Robot Using Double Photoelectric Encoder Positioning

“…OpenGUI has excellent built-in function modules and can be programmed with C + +. In addition, it is also compatible with many peripheral event modules, and its application is simple and fast [15].…”

Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM

“…These systems require specific illumination conditions and are expensive, so it is not viable for large-scale applications [ 14 ]. Brain–computer interface (BCI) technology has been employed in human–wheelchair interactions previously [ 15 , 16 , 17 , 18 ]. The acquisition of Electroencephalogram (EEG) signals is usually realized by invasive electrodes, which brings great difficulty to implementation and may impact the physical health of the user [ 19 ].…”