Brain Waves Classification Using a Single-Channel Dry EEG Headset: An Application for Controlling an Intelligent Wheelchair.

Assistive technologies such as Intelligent Wheelchairs (IWs) can improve mobility and independence among elders and disabled people. To achieve this, various adapted sensors can be employed. In this study, the NeuroSky Mindwave Mobile 2 sensor is utilized to interpret the user’s intentions into one of four commands: forward, right turn, left turn, or stop. By collecting brainwave data, specifically rhythms associated with imagining specific actions, the sensor enables the recognition of user desires. Data acquisition experiments were conducted, where individuals imagined different directions under four distinct conditions. Among the four datasets, the most effective classification was achieved when participants imagined the desired direction after being presented with the respective cue. Feature standardization leads to higher performances when compared to other scaling techniques. In conclusion, the findings suggest promising prospects for the control of intelligent wheelchairs through brainwave analysis.