Construction of real-time BMI control system based on motor imagery

Yoshioka, Masataka; Zhu, Chi; Yoshikawa, Youichiro; Nishikawa, Takeshi; Shimazu, Shota; Imamura, Kazuyuki; Wang, Feng; Huang, Yu; Yao, Yan

doi:10.1109/robio.2011.6181285

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…A required control of the robotic arm was achieved experimentally with 100ms control period. 32 A onejoint robot arm was controlled in this experiment. EEG signals to lift an arm was obtained and divided with shot-time FFT window to get the power spectra.…”

Section: Figure 11mentioning

confidence: 99%

Human machine interface: robotizing the instinctive living

Tahir

Iqbal

Aized³

2018

IRATJ

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The advancement in medical science and technology has revolutionized human interaction with machines, crafting one of the most promising state-of-the-art technological fields of today's world. This innovation has made doors opened to rehabilitation beyond patient assistance-Brain Computer Interface (BCI) has stepped forward towards life automation (brain controlled daily life actions), and entertainment (hands-free gaming). This paper reviews key techniques and sensors vital to this technological paramount, along with an appraisal to the commercially available sensors. An exclusive appraisal on state of-the-art BCI technologies has also been discussed conferring their application specific importance. The methodical study of these technologies and comparison of corresponding techniques and sensors is potentially useful to demonstrate the significance of brain machine interface.

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Section: Figure 11mentioning

confidence: 99%

Human machine interface: robotizing the instinctive living

Tahir

Iqbal

Aized³

2018

IRATJ

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“…Among these rhythms, the frequencies of Delta rhythms are the lowest, and they are most apparent in deep sleep states. Zhu [22] utilized the short-time FFT method to analyze the Mu and Beta rhythms generated by different tasks, and the developed BCI system can control a robot arm successfully.…”

Section: Introductionmentioning

confidence: 99%

Design of a Multimodal EEG-based Hybrid BCI System with Visual Servo Module

Duan

Lin

et al. 2015

IEEE Trans. Auton. Mental Dev.

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Construction of real-time BMI control system based on motor imagery

Cited by 2 publications

References 13 publications

Human machine interface: robotizing the instinctive living

Human machine interface: robotizing the instinctive living

Design of a Multimodal EEG-based Hybrid BCI System with Visual Servo Module

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