A brain-computer interface system for smart home control based on single trial motor imagery EEG. (7th December 2020)

• Record Type: Journal Article
• Authors: Zhuang, Wei; Shen, Yixian; Li, Lu; Gao, Chunming; Dai, Dong
• Is Part Of: International journal of sensor networks. Volume 34:Number 4(2020)
• Page Start: 214
• Page End: 225
• Publication Date: 2020-12-07
• Subjects: EEG recognition -- EEG features -- EEG detection -- blinking detection -- wearable EEG device -- STM32 embedded control -- TGAM -- ThinkGear Asic module -- smart home control; Sensor networks -- Periodicals; 681.2
• Languages: English
• ISSNs: 1748-1279

Abstract

In recent years, researches on brain signal recognition and brain-computer interface control have made great progress. By analysing electroencephalogram (EEG), a specific brain activity can be detected and the signal can be used to control smart devices and help people to complete difficult and complicated tasks, especially for people with disabilities. This paper presents the design and implementation of a novel brain-computer interface system for smart home control using single trial motor imagery EEG. The system adopts STM32 Microcontroller Unit (MCU) and ThinkGear Asic Module (TGAM) to realise the acquisition and recognition of EEG signals. It can transfer the signals to portable devices through Bluetooth modules. Three main EEG features including Alpha, Beta, and Gamma waves are discussed. It is tested during simple actions such as blinking in various situations. The experimental results show that the implemented system is suitable for extracting specific EEG signals to control smart home devices.