Browsing University of Waterloo by Author "Sheng, Xinjun"
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Decoding covert somatosensory attention by a BCI system calibrated with tactile sensation
Yao, Lin; Sheng, Xinjun; Mrachacz-Kersting, Natalie; Zhu, Xiangyang; Farina, Dario; Jiang, Ning (Institute of Electrical and Electronics Engineers, 2017-10-12)Objective: We propose a novel calibration strategy to facilitate the decoding of covert somatosensory attention by exploring the oscillatory dynamics induced by tactile sensation. Methods: It was hypothesized that the ... -
Fast Recognition of BCI-Inefficient Users Using Physiological Features from EEG Signals: A Screening Study of Stroke Patients
Shu, Xiaokang; Chen, Shugeng; Yao, Lin; Sheng, Xinjun; Zhang, Dingguo; Jiang, Ning; Jia, Jie; Zhu, Xiangyang (Frontiers, 2018-02-21)Motor imagery (MI) based brain-computer interface (BCI) has been developed as an alternative therapy for stroke rehabilitation. However, experimental evidence demonstrates that a significant portion (10% to 50%) of subjects ... -
Improving robustness against electrode shift of high density EMG for myoelectric control through common spatial patterns
Pan, Lizhi; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Zhu, Xiangyang (BioMed Central, 2015-12-02)Background: Most prosthetic myoelectric control studies have concentrated on low density (less than 16 electrodes, LD) electromyography (EMG) signals, due to its better clinical applicability and low computation complexity ... -
A Multi-class BCI based on Somatosensory Imagery
Yao, Lin; Mrachacz-Kersting, Natalie; Sheng, Xinjun; Zhu, Xiangyang; Farina, Dario; Jiang, Ning (Institute of Electrical and Electronics Engineers, 2018-06-18)In this study, we investigated the performance of a multi-class brain-computer interface (BCI). The BCI system is based on the concept of somatosensory attentional orientation (SAO), in which the user shifts and maintains ... -
A multi-class tactile brain-computer interface based on stimulus-induced oscillatory dynamics
Yao, Lin; Chen, Mei Lin; Sheng, Xinjun; Mrachacz-Kersting, Natalie; Zhu, Xiangyang; Farina, Dario; Jiang, Ning (Elsevier, 2017-07-24)We proposed a multi-class tactile brain-computer interface that utilizes stimulus-induced oscillatory dynamics. It was hypothesized that somatosensory attention can modulate tactile induced oscillation changes, which can ... -
Performance of Brain-Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery
Yao, Lin; Sheng, Xinjun; Mrachacz-Kersting, Natalie; Zhu, Xiangyang; Farina, Dario; Jiang, Ning (Institute of Electrical and Electronics Engineers, 2017-11-03)A large proportion of users do not achieve adequate control using current non-invasive Brain-computer Interfaces (BCI). This issue has being coined “BCI-Illiteracy”, and is observed among BCI modalities. Here, we compare ... -
Sensory Stimulation Training for BCI System based on Somatosensory Attentional Orientation
Yao, Lin; Sheng, Xinjun; Mrachacz-Kersting, Natalie; Zhu, Xiangyang; Farina, Dario; Jiang, Ning (Institute of Electrical and Electronics Engineers, 2018-07-04)In this study, we propose a sensory stimulation training (SST) approach to improve the performance of a brain-computer interface (BCI) based on somatosensory attentional orientation (SAO). In this BCI, subjects imagine the ... -
Spatial Information Enhances Myoelectric Control Performance with Only Two Channels
He, Jiayuan; Sheng, Xinjun; Zhu, Xiangyang; Jiang, Chaozhe; Jiang, Ning (Institute of Electrical and Electronics Engineers, 2018-09-10)Automatic gesture recognition (AGR) is investigated as an effortless human-machine interaction method, potentially applied in many industrial sectors. When using surface electromyogram (sEMG) for AGR, i.e. myoelectric ...