Figure 3: Wearable forehead-EEG based BCIs and their medical applications (IMAGE)

Health Data Science

Figure 3: Wearable forehead-EEG based BCIs and their medical applications

Caption

(a) Brain Research Center of National Chiao Tung University developed Mindo 4S EEG device. (b) Shenzhen Macrotellect Company designed BrainLink Lite. (c) NeuroSky Company developed MindWave Mobile. (d) Chiu et al. from University of Technology built an SSVEP-based BCI eating assistive system. (e) Li et al. from Xi’an Jiaotong University introduced a BCI system for wrist rehabilitation. (f) Salih et al. designed a BCI-based visual keyboard using the MindWave Mobile headset. With the QWERTY virtual keyboard (left) and ABC virtual keyboard (right), an average text entry speed of about 1.55-1.8 words per minute and an error rate of 5-5.25% were obtained.

Credit

(a) ©2017 IEEE. Reprinted, with permission, from Lin et al., Forehead EEG in support of future feasible personal healthcare solutions: sleep management, headache prevention, and depression treatment. IEEE Access. 2017;5:10612-10621. DOI: 10.1109/ACCESS.2017.2675884 (b) https://www.epihunter.com/brainlink-headset (c) ©2020 IEEE. Reprinted, with permission, from Tiwari et al., Sensitive brain-computer interface to help manoeuvre a miniature wheelchair using electroencephalography. 2020 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). 2020:1-6. DOI: 10.1109/SCEECS48394.2020.73 (d) ©2017 IEEE. Reprinted, with permission, from Chiu et al., A wireless steady state visually evoked potential-based BCI eating assistive system. 2017 International Joint Conference on Neural Networks (IJCNN). 2017:3003-3007. DOI: 10.1109/IJCNN.2017.7966228 (e) Used with permission of IEEE, from Attention-controlled assistive wrist rehabilitation using a low-cost EEG sensor, Li et al., 19(15), 2019; permission conveyed through Copyright Clearance Center, Inc (f) ©2020 UAD. Reprinted, with permission, from Salih et al.

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