Motor imagery EEG analysis for home appliance control

Older adults who stay alone at home have to carry out their daily routine independently. With assistive technology, they can complete the work without using a lot of energy and without moving around frequently in the house. Neuro-based electronic home appliances that can assist the older adults to perform multitasking operation have not been developed. This paper describes the analysis of motor imagery electroencephalogram (EEG) to identify the suitable parameters from the signal that can be used for controlling home appliances. A protocol for recording EEG that can extract the significant motor imagery movements was designed. The EEG signals were recorded from adults using optimum electrode placements and analysed using Fast Fourier transform. It was found that the grasping hands and number of times grasping can be used to activate devices. The imagined hand grasping information can be observed clearly from EEG signal in time domain during eye closing and opening.