Characteristics of EEG Response Evoked by Postural Perturbation During Standing with Upper Limb Support
He Feng1,2, Zhang Jie1,2, Jiang Shenglong1,2, Qi Hongzhi1,2, Xu Rui1,2, Meng Lin1,2, Ming Dong1,2#*
1(School of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072,China) 2(Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072,China)
Abstract This study investigated the characteristics of EEG response evoked by postural perturbation during standing with upper limb support, aiming to provide a new idea for detecting the instability of patients with lower extremity motor dysfunction. The experimental equipment was designed to apply rapid and sudden change of upper limb supporting force on random side of human body to simulate the perturbation during upper limb assisted standing. The EEG of 64 channels, two sides of supporting force andsurface electromyogram (sEMG) of smaller forearm extensors on both sides of 20 subjects were recorded synchronously. We analyzed the neural response characteristics of EEG evoked potential, and the behavioral response characteristics of mechanical signal and sEMG. Results: After the postural perturbation was applied, the supporting force on the perturbed side suddenly decreased in the time of (200.5±15.4) ms. Meanwhile, sEMG of smaller forearm extensors on both sides increased, and the sEMG of perturbed side was higher than the other side. Following postural perturbation onset, N1 potentials were observed with a peak latency of (62.3±5.5) ms and the peak activity was located at FCz electrode with a peak amplitude of (15.6±6.1) μV. The peak latency of P2 potentials were (167.4±12.4) ms and peak amplitude were (5.2±4.5) μV. The findings of this study provided a feasibility of detecting human unsteady state through neural response process.
He Feng,Zhang Jie,Jiang Shenglong, et al. Characteristics of EEG Response Evoked by Postural Perturbation During Standing with Upper Limb Support[J]. Chinese Journal of Biomedical Engineering, 2019, 38(6): 672-678.
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